Development of a digital method for neutron/gamma-ray discrimination based on matched filtering

NASA Astrophysics Data System (ADS)

Korolczuk, S.; Linczuk, M.; Romaniuk, R.; Zychor, I.

2016-09-01

Neutron/gamma-ray discrimination is crucial for measurements with detectors sensitive to both neutron and gamma-ray radiation. Different techniques to discriminate between neutrons and gamma-rays based on pulse shape analysis are widely used in many applications, e.g., homeland security, radiation dosimetry, environmental monitoring, fusion experiments, nuclear spectroscopy. A common requirement is to improve a radiation detection level with a high detection reliability. Modern electronic components, such as high speed analog to digital converters and powerful programmable digital circuits for signal processing, allow us to develop a fully digital measurement system. With this solution it is possible to optimize digital signal processing algorithms without changing any electronic components in an acquisition signal path. We report on results obtained with a digital acquisition system DNG@NCBJ designed at the National Centre for Nuclear Research. A 2'' × 2'' EJ309 liquid scintillator was used to register mixed neutron and gamma-ray radiation from PuBe sources. A dedicated algorithm for pulse shape discrimination, based on real-time filtering, was developed and implemented in hardware.

Application of Fourier transform infrared spectroscopy and chemometrics for differentiation of Salmonella enterica serovar Enteritidis phage types.

PubMed

Preisner, Ornella; Guiomar, Raquel; Machado, Jorge; Menezes, José Cardoso; Lopes, João Almeida

2010-06-01

Fourier transform infrared (FT-IR) spectroscopy and chemometric techniques were used to discriminate five closely related Salmonella enterica serotype Enteritidis phage types, phage type 1 (PT1), PT1b, PT4b, PT6, and PT6a. Intact cells and outer membrane protein (OMP) extracts from bacterial cell membranes were subjected to FT-IR analysis in transmittance mode. Spectra were collected over a wavenumber range from 4,000 to 600 cm(-1). Partial least-squares discriminant analysis (PLS-DA) was used to develop calibration models based on preprocessed FT-IR spectra. The analysis based on OMP extracts provided greater separation between the Salmonella Enteritidis PT1-PT1b, PT4b, and PT6-PT6a groups than the intact cell analysis. When these three phage type groups were considered, the method based on OMP extract FT-IR spectra was 100% accurate. Moreover, complementary local models that considered only the PT1-PT1b and PT6-PT6a groups were developed, and the level of discrimination increased. PT1 and PT1b isolates were differentiated successfully with the local model using the entire OMP extract spectrum (98.3% correct predictions), whereas the accuracy of discrimination between PT6 and PT6a isolates was 86.0%. Isolates belonging to different phage types (PT19, PT20, and PT21) were used with the model to test its robustness. For the first time it was demonstrated that FT-IR analysis of OMP extracts can be used for construction of robust models that allow fast and accurate discrimination of different Salmonella Enteritidis phage types.

Exploring high-resolution magic angle spinning (HR-MAS) NMR spectroscopy for metabonomic analysis of apples.

PubMed

Vermathen, Martina; Marzorati, Mattia; Vermathen, Peter

2012-01-01

Classical liquid-state high-resolution (HR) NMR spectroscopy has proved a powerful tool in the metabonomic analysis of liquid food samples like fruit juices. In this paper the application of (1)H high-resolution magic angle spinning (HR-MAS) NMR spectroscopy to apple tissue is presented probing its potential for metabonomic studies. The (1)H HR-MAS NMR spectra are discussed in terms of the chemical composition of apple tissue and compared to liquid-state NMR spectra of apple juice. Differences indicate that specific metabolic changes are induced by juice preparation. The feasibility of HR-MAS NMR-based multivariate analysis is demonstrated by a study distinguishing three different apple cultivars by principal component analysis (PCA). Preliminary results are shown from subsequent studies comparing three different cultivation methods by means of PCA and partial least squares discriminant analysis (PLS-DA) of the HR-MAS NMR data. The compounds responsible for discriminating organically grown apples are discussed. Finally, an outlook of our ongoing work is given including a longitudinal study on apples.

[Fast Detection of Camellia Sinensis Growth Process and Tea Quality Informations with Spectral Technology: A Review].

PubMed

Peng, Ji-yu; Song, Xing-lin; Liu, Fei; Bao, Yi-dan; He, Yong

2016-03-01

The research achievements and trends of spectral technology in fast detection of Camellia sinensis growth process information and tea quality information were being reviewed. Spectral technology is a kind of fast, nondestructive, efficient detection technology, which mainly contains infrared spectroscopy, fluorescence spectroscopy, Raman spectroscopy and mass spectroscopy. The rapid detection of Camellia sinensis growth process information and tea quality is helpful to realize the informatization and automation of tea production and ensure the tea quality and safety. This paper provides a review on its applications containing the detection of tea (Camellia sinensis) growing status(nitrogen, chlorophyll, diseases and insect pest), the discrimination of tea varieties, the grade discrimination of tea, the detection of tea internal quality (catechins, total polyphenols, caffeine, amino acid, pesticide residual and so on), the quality evaluation of tea beverage and tea by-product, the machinery of tea quality determination and discrimination. This paper briefly introduces the trends of the technology of the determination of tea growth process information, sensor and industrial application. In conclusion, spectral technology showed high potential to detect Camellia sinensis growth process information, to predict tea internal quality and to classify tea varieties and grades. Suitable chemometrics and preprocessing methods is helpful to improve the performance of the model and get rid of redundancy, which provides the possibility to develop the portable machinery. Future work is to develop the portable machinery and on-line detection system is recommended to improve the further application. The application and research achievement of spectral technology concerning about tea were outlined in this paper for the first time, which contained Camellia sinensis growth, tea production, the quality and safety of tea and by-produce and so on, as well as some problems to be solved and its future applicability in modern tea industrial.

Discrimination of inflammatory bowel disease using Raman spectroscopy and linear discriminant analysis methods

NASA Astrophysics Data System (ADS)

Ding, Hao; Cao, Ming; DuPont, Andrew W.; Scott, Larry D.; Guha, Sushovan; Singhal, Shashideep; Younes, Mamoun; Pence, Isaac; Herline, Alan; Schwartz, David; Xu, Hua; Mahadevan-Jansen, Anita; Bi, Xiaohong

2016-03-01

Inflammatory bowel disease (IBD) is an idiopathic disease that is typically characterized by chronic inflammation of the gastrointestinal tract. Recently much effort has been devoted to the development of novel diagnostic tools that can assist physicians for fast, accurate, and automated diagnosis of the disease. Previous research based on Raman spectroscopy has shown promising results in differentiating IBD patients from normal screening cases. In the current study, we examined IBD patients in vivo through a colonoscope-coupled Raman system. Optical diagnosis for IBD discrimination was conducted based on full-range spectra using multivariate statistical methods. Further, we incorporated several feature selection methods in machine learning into the classification model. The diagnostic performance for disease differentiation was significantly improved after feature selection. Our results showed that improved IBD diagnosis can be achieved using Raman spectroscopy in combination with multivariate analysis and feature selection.

Classification of smoke tainted wines using mid-infrared spectroscopy and chemometrics.

PubMed

Fudge, Anthea L; Wilkinson, Kerry L; Ristic, Renata; Cozzolino, Daniel

2012-01-11

In this study, the suitability of mid-infrared (MIR) spectroscopy, combined with principal component analysis (PCA) and linear discriminant analysis (LDA), was evaluated as a rapid analytical technique to identify smoke tainted wines. Control (i.e., unsmoked) and smoke-affected wines (260 in total) from experimental and commercial sources were analyzed by MIR spectroscopy and chemometrics. The concentrations of guaiacol and 4-methylguaiacol were also determined using gas chromatography-mass spectrometry (GC-MS), as markers of smoke taint. LDA models correctly classified 61% of control wines and 70% of smoke-affected wines. Classification rates were found to be influenced by the extent of smoke taint (based on GC-MS and informal sensory assessment), as well as qualitative differences in wine composition due to grape variety and oak maturation. Overall, the potential application of MIR spectroscopy combined with chemometrics as a rapid analytical technique for screening smoke-affected wines was demonstrated.

Spectral Mining for Discriminating Blood Origins in the Presence of Substrate Interference via Attenuated Total Reflection Fourier Transform Infrared Spectroscopy: Postmortem or Antemortem Blood?

PubMed

Takamura, Ayari; Watanabe, Ken; Akutsu, Tomoko; Ikegaya, Hiroshi; Ozawa, Takeaki

2017-09-19

Often in criminal investigations, discrimination of types of body fluid evidence is crucially important to ascertain how a crime was committed. Compared to current methods using biochemical techniques, vibrational spectroscopic approaches can provide versatile applicability to identify various body fluid types without sample invasion. However, their applicability is limited to pure body fluid samples because important signals from body fluids incorporated in a substrate are affected strongly by interference from substrate signals. Herein, we describe a novel approach to recover body fluid signals that are embedded in strong substrate interferences using attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy and an innovative multivariate spectral processing. This technique supported detection of covert features of body fluid signals, and then identified origins of body fluid stains on substrates. We discriminated between ATR FT-IR spectra of postmortem blood (PB) and those of antemortem blood (AB) by creating a multivariate statistics model. From ATR FT-IR spectra of PB and AB stains on interfering substrates (polyester, cotton, and denim), blood-originated signals were extracted by a weighted linear regression approach we developed originally using principal components of both blood and substrate spectra. The blood-originated signals were finally classified by the discriminant model, demonstrating high discriminant accuracy. The present method can identify body fluid evidence independently of the substrate type, which is expected to promote the application of vibrational spectroscopic techniques in forensic body fluid analysis.

Raman spectroscopy of bio fluids: an exploratory study for oral cancer detection

NASA Astrophysics Data System (ADS)

Brindha, Elumalai; Rajasekaran, Ramu; Aruna, Prakasarao; Koteeswaran, Dornadula; Ganesan, Singaravelu

2016-03-01

ion for various disease diagnosis including cancers. Oral cancer is one of the most common cancers in India and it accounts for one third of the global oral cancer burden. Raman spectroscopy of tissues has gained much attention in the diagnostic oncology, as it provides unique spectral signature corresponding to metabolic alterations under different pathological conditions and micro-environment. Based on these, several studies have been reported on the use of Raman spectroscopy in the discrimination of diseased conditions from their normal counterpart at cellular and tissue level but only limited studies were available on bio-fluids. Recently, optical characterization of bio-fluids has also geared up for biomarker identification in the disease diagnosis. In this context, an attempt was made to study the metabolic variations in the blood, urine and saliva of oral cancer patients and normal subjects using Raman spectroscopy. Principal Component based Linear Discriminant Analysis (PC-LDA) followed by Leave-One-Out Cross-Validation (LOOCV) was employed to find the statistical significance of the present technique in discriminating the malignant conditions from normal subjects.

Fourier transform near-infrared spectroscopy application for sea salt quality evaluation.

PubMed

Galvis-Sánchez, Andrea C; Lopes, João Almeida; Delgadillo, Ivonne; Rangel, António O S S

2011-10-26

Near-infrared (NIR) spectroscopy in diffuse reflectance mode was explored with the objective of discriminating sea salts according to their quality type (traditional salt vs "flower of salt") and geographical origin (Atlantic vs Mediterranean). Sea salts were also analyzed in terms of Ca(2+), Mg(2+), K(+), alkalinity, and sulfate concentrations to support spectroscopic results. High concentrations of Mg(2+) and K(+) characterized Atlantic samples, while a high Ca(2+) content was observed in traditional sea salts. A partial least-squares discriminant analysis model considering the 8500-7500 cm(-1) region permitted the discrimination of salts by quality types. The regions 4650-4350 and 5900-5500 cm(-1) allowed salts classification according to their geographical origin. It was possible to classify correctly 85.3 and 94.8% of the analyzed samples according to the salt type and to the geographical origin, respectively. These results demonstrated that NIR spectroscopy is a suitable and very efficient tool for sea salt quality evaluation.

[Discrimination of Rice Syrup Adulterant of Acacia Honey Based Using Near-Infrared Spectroscopy].

PubMed

Zhang, Yan-nan; Chen, Lan-zhen; Xue, Xiao-feng; Wu, Li-ming; Li, Yi; Yang, Juan

2015-09-01

At present, the rice syrup as a low price of the sweeteners was often adulterated into acacia honey and the adulterated honeys were sold in honey markets, while there is no suitable and fast method to identify honey adulterated with rice syrup. In this study, Near infrared spectroscopy (NIR) combined with chemometric methods were used to discriminate authenticity of honey. 20 unprocessed acacia honey samples from the different honey producing areas, mixed? with different proportion of rice syrup, were prepared of seven different concentration gradient? including 121 samples. The near infrared spectrum (NIR) instrument and spectrum processing software have been applied in the? spectrum? scanning and data conversion on adulterant samples, respectively. Then it was analyzed by Principal component analysis (PCA) and canonical discriminant analysis methods in order to discriminating adulterated honey. The results showed that after principal components analysis, the first two principal components accounted for 97.23% of total variation, but the regionalism of the score plot of the first two PCs was not obvious, so the canonical discriminant analysis was used to make the further discrimination, all samples had been discriminated correctly, the first two discriminant functions accounted for 91.6% among the six canonical discriminant functions, Then the different concentration of adulterant samples can be discriminated correctly, it illustrate that canonical discriminant analysis method combined with NIR spectroscopy is not only feasible but also practical for rapid and effective discriminate of the rice syrup adulterant of acacia honey.

Early discrimination of nasopharyngeal carcinoma based on tissue deoxyribose nucleic acid surface-enhanced Raman spectroscopy analysis

NASA Astrophysics Data System (ADS)

Qiu, Sufang; Li, Chao; Lin, Jinyong; Xu, Yuanji; Lu, Jun; Huang, Qingting; Zou, Changyan; Chen, Chao; Xiao, Nanyang; Lin, Duo; Chen, Rong; Pan, Jianji; Feng, Shangyuan

2016-12-01

Surface-enhanced Raman spectroscopy (SERS) was employed to detect deoxyribose nucleic acid (DNA) variations associated with the development of nasopharyngeal carcinoma (NPC). Significant SERS spectral differences between the DNA extracted from early NPC, advanced NPC, and normal nasopharyngeal tissue specimens were observed at 678, 729, 788, 1337, 1421, 1506, and 1573 cm-1, which reflects the genetic variations in NPC. Principal component analysis combined with discriminant function analysis for early NPC discrimination yielded a diagnostic accuracy of 86.8%, 92.3%, and 87.9% for early NPC, advanced NPC, and normal nasopharyngeal tissue DNA, respectively. In this exploratory study, we demonstrated the potential of SERS for early detection of NPC based on the DNA molecular study of biopsy tissues.

The effect of nutrient media water purity on LIBS based identification of bacteria

USDA-ARS?s Scientific Manuscript database

Single pulse laser induced breakdown spectroscopy (LIBS) is used as the basis for discrimination between 3 genera of Gram-negative bacteria and 2 genera of gram-positive bacteria representing pathogenic threats commonly found in poultry processing rinse waters. Because LIBS-based discrimination reli...

Progress in the detection of neoplastic progress and cancer by Raman spectroscopy

NASA Astrophysics Data System (ADS)

Bakker Schut, Tom C.; Stone, Nicholas; Kendall, Catherine A.; Barr, Hugh; Bruining, Hajo A.; Puppels, Gerwin J.

2000-05-01

Early detection of cancer is important because of the improved survival rates when the cancer is treated early. We study the application of NIR Raman spectroscopy for detection of dysplasia because this technique is sensitive to the small changes in molecular invasive in vivo detection using fiber-optic probes. The result of an in vitro study to detect neoplastic progress of esophageal Barrett's esophageal tissue will be presented. Using multivariate statistics, we developed three different linear discriminant analysis classification models to predict tissue type on the basis of the measured spectrum. Spectra of normal, metaplastic and dysplasia tissue could be discriminated with an accuracy of up to 88 percent. Therefore Raman spectroscopy seems to be a very suitable technique to detect dysplasia in Barrett's esophageal tissue.

Laguerre-based method for analysis of time-resolved fluorescence data: application to in-vivo characterization and diagnosis of atherosclerotic lesions.

PubMed

Jo, Javier A; Fang, Qiyin; Papaioannou, Thanassis; Baker, J Dennis; Dorafshar, Amir H; Reil, Todd; Qiao, Jian-Hua; Fishbein, Michael C; Freischlag, Julie A; Marcu, Laura

2006-01-01

We report the application of the Laguerre deconvolution technique (LDT) to the analysis of in-vivo time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data and the diagnosis of atherosclerotic plaques. TR-LIFS measurements were obtained in vivo from normal and atherosclerotic aortas (eight rabbits, 73 areas), and subsequently analyzed using LDT. Spectral and time-resolved features were used to develop four classification algorithms: linear discriminant analysis (LDA), stepwise LDA (SLDA), principal component analysis (PCA), and artificial neural network (ANN). Accurate deconvolution of TR-LIFS in-vivo measurements from normal and atherosclerotic arteries was provided by LDT. The derived Laguerre expansion coefficients reflected changes in the arterial biochemical composition, and provided a means to discriminate lesions rich in macrophages with high sensitivity (>85%) and specificity (>95%). Classification algorithms (SLDA and PCA) using a selected number of features with maximum discriminating power provided the best performance. This study demonstrates the potential of the LDT for in-vivo tissue diagnosis, and specifically for the detection of macrophages infiltration in atherosclerotic lesions, a key marker of plaque vulnerability.

Laguerre-based method for analysis of time-resolved fluorescence data: application to in-vivo characterization and diagnosis of atherosclerotic lesions

NASA Astrophysics Data System (ADS)

Jo, Javier A.; Fang, Qiyin; Papaioannou, Thanassis; Baker, J. Dennis; Dorafshar, Amir; Reil, Todd; Qiao, Jianhua; Fishbein, Michael C.; Freischlag, Julie A.; Marcu, Laura

2006-03-01

We report the application of the Laguerre deconvolution technique (LDT) to the analysis of in-vivo time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data and the diagnosis of atherosclerotic plaques. TR-LIFS measurements were obtained in vivo from normal and atherosclerotic aortas (eight rabbits, 73 areas), and subsequently analyzed using LDT. Spectral and time-resolved features were used to develop four classification algorithms: linear discriminant analysis (LDA), stepwise LDA (SLDA), principal component analysis (PCA), and artificial neural network (ANN). Accurate deconvolution of TR-LIFS in-vivo measurements from normal and atherosclerotic arteries was provided by LDT. The derived Laguerre expansion coefficients reflected changes in the arterial biochemical composition, and provided a means to discriminate lesions rich in macrophages with high sensitivity (>85%) and specificity (>95%). Classification algorithms (SLDA and PCA) using a selected number of features with maximum discriminating power provided the best performance. This study demonstrates the potential of the LDT for in-vivo tissue diagnosis, and specifically for the detection of macrophages infiltration in atherosclerotic lesions, a key marker of plaque vulnerability.

Laguerre-based method for analysis of time-resolved fluorescence data: application to in-vivo characterization and diagnosis of atherosclerotic lesions

PubMed Central

Jo, Javier A.; Fang, Qiyin; Papaioannou, Thanassis; Baker, J. Dennis; Dorafshar, Amir H.; Reil, Todd; Qiao, Jian-Hua; Fishbein, Michael C.; Freischlag, Julie A.; Marcu, Laura

2007-01-01

We report the application of the Laguerre deconvolution technique (LDT) to the analysis of in-vivo time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data and the diagnosis of atherosclerotic plaques. TR-LIFS measurements were obtained in vivo from normal and atherosclerotic aortas (eight rabbits, 73 areas), and subsequently analyzed using LDT. Spectral and time-resolved features were used to develop four classification algorithms: linear discriminant analysis (LDA), stepwise LDA (SLDA), principal component analysis (PCA), and artificial neural network (ANN). Accurate deconvolution of TR-LIFS in-vivo measurements from normal and atherosclerotic arteries was provided by LDT. The derived Laguerre expansion coefficients reflected changes in the arterial biochemical composition, and provided a means to discriminate lesions rich in macrophages with high sensitivity (>85%) and specificity (>95%). Classification algorithms (SLDA and PCA) using a selected number of features with maximum discriminating power provided the best performance. This study demonstrates the potential of the LDT for in-vivo tissue diagnosis, and specifically for the detection of macrophages infiltration in atherosclerotic lesions, a key marker of plaque vulnerability. PMID:16674179

Application of infrared spectroscopy and pyrolysis gas chromatography for characterisation of adhesive tapes

NASA Astrophysics Data System (ADS)

Zięba-Palus, Janina; Nowińska, Sabina; Kowalski, Rafał

2016-12-01

Infrared spectroscopy and pyrolysis GC/MS were applied in the comparative analysis of adhesive tapes. By providing information about the polymer composition, it was possible to classify both backings and adhesives of tapes into defined chemical classes. It was found that samples of the same type (of backings and adhesives) and similar infrared spectra can in most cases be effectively differentiated using Py-GC/MS, sometimes based only on the presence of peaks of very low intensity originating from minor components. The results obtained enabled us to draw the conclusion that Py-GC/MS appears to be a valuable analytical technique for examining tapes, which is complementary to infrared spectroscopy. Identification of pyrolysis products enables discrimination of samples. Both methods also provide crucial information that is useful for identification of adhesive tapes found at the crime scene.

Near-field photothermal microspectroscopy for adult stem-cell identification and characterization.

PubMed

Grude, Olaug; Hammiche, Azzedine; Pollock, Hubert; Bentley, Adam J; Walsh, Michael J; Martin, Francis L; Fullwood, Nigel J

2007-12-01

The identification of stem cells in adult tissue is a challenging problem in biomedicine. Currently, stem cells are identified by individual epitopes, which are generally tissue specific. The discovery of a stem-cell marker common to other adult tissue types could open avenues in the development of therapeutic stem-cell strategies. We report the use of the novel technique of Fourier transform infrared near-field photothermal microspectroscopy (FTIR-PTMS) for the characterization of stem cells, transit amplifying (TA) cells and terminally differentiated (TD) cells in the corneal epithelium. Principal component analysis (PCA) data demonstrate excellent discrimination of cell type by spectra. PCA in combination with linear discriminant analysis (PCA-LDA) shows that FTIR-PTMS very effectively discriminates between the three cell populations. Statistically significant differences above the 99% confidence level between IR spectra from stem cells and TA cells suggest that nucleic acid conformational changes are an important component of the differences between spectral data from the two cell types. FTIR-PTMS is a new addition to existing spectroscopy methods based on the concept of interfacing a conventional FTIR spectrometer with an atomic force microscope equipped with a near-field thermal sensing probe. FTIR-PTMS spectroscopy currently has spatial resolution that is similar to that of diffraction-limited optical detection FTIR spectroscopy techniques, but as a near-field probing technique has considerable potential for further improvement. Our work also suggests that FTIR-PTMS is potentially more sensitive than synchrotron radiation FTIR spectroscopy for some applications. Microspectroscopy techniques like FTIR-PTMS provide information about the entire molecular composition of cells, in contrast to epitope recognition that only considers the presence or absence of individual molecules. Our results with FTIR-PTMS on corneal stem cells are promising for the potential development of an IR spectral fingerprint for stem cells.

Significance of clustering and classification applications in digital and physical libraries

NASA Astrophysics Data System (ADS)

Triantafyllou, Ioannis; Koulouris, Alexandros; Zervos, Spiros; Dendrinos, Markos; Giannakopoulos, Georgios

2015-02-01

Applications of clustering and classification techniques can be proved very significant in both digital and physical (paper-based) libraries. The most essential application, document classification and clustering, is crucial for the content that is produced and maintained in digital libraries, repositories, databases, social media, blogs etc., based on various tags and ontology elements, transcending the traditional library-oriented classification schemes. Other applications with very useful and beneficial role in the new digital library environment involve document routing, summarization and query expansion. Paper-based libraries can benefit as well since classification combined with advanced material characterization techniques such as FTIR (Fourier Transform InfraRed spectroscopy) can be vital for the study and prevention of material deterioration. An improved two-level self-organizing clustering architecture is proposed in order to enhance the discrimination capacity of the learning space, prior to classification, yielding promising results when applied to the above mentioned library tasks.

Potential and limits of Raman spectroscopy for carotenoid detection in microorganisms: implications for astrobiology

PubMed Central

Jehlička, Jan; Edwards, Howell G. M.; Osterrothová, Kateřina; Novotná, Julie; Nedbalová, Linda; Kopecký, Jiří; Němec, Ivan; Oren, Aharon

2014-01-01

In this paper, it is demonstrated how Raman spectroscopy can be used to detect different carotenoids as possible biomarkers in various groups of microorganisms. The question which arose from previous studies concerns the level of unambiguity of discriminating carotenoids using common Raman microspectrometers. A series of laboratory-grown microorganisms of different taxonomic affiliation was investigated, such as halophilic heterotrophic bacteria, cyanobacteria, the anoxygenic phototrophs, the non-halophilic heterotrophs as well as eukaryotes (Ochrophyta, Rhodophyta and Chlorophyta). The data presented show that Raman spectroscopy is a suitable tool to assess the presence of carotenoids of these organisms in cultures. Comparison is made with the high-performance liquid chromatography approach of analysing pigments in extracts. Direct measurements on cultures provide fast and reliable identification of the pigments. Some of the carotenoids studied are proposed as tracers for halophiles, in contrast with others which can be considered as biomarkers of other genera. The limits of application of Raman spectroscopy are discussed for a few cases where the current Raman spectroscopic approach does not allow discriminating structurally very similar carotenoids. The database reported can be used for applications in geobiology and exobiology for the detection of pigment signals in natural settings. PMID:25368348

Development and Testing of an LED-Based Near-Infrared Sensor for Human Kidney Tumor Diagnostics

PubMed Central

Zabarylo, Urszula; Kirsanov, Dmitry; Belikova, Valeria; Ageev, Vladimir; Usenov, Iskander; Galyanin, Vladislav; Minet, Olaf; Sakharova, Tatiana; Danielyan, Georgy; Feliksberger, Elena; Artyushenko, Viacheslav

2017-01-01

Optical spectroscopy is increasingly used for cancer diagnostics. Tumor detection feasibility in human kidney samples using mid- and near-infrared (NIR) spectroscopy, fluorescence spectroscopy, and Raman spectroscopy has been reported (Artyushenko et al., Spectral fiber sensors for cancer diagnostics in vitro. In Proceedings of the European Conference on Biomedical Optics, Munich, Germany, 21–25 June 2015). In the present work, a simplification of the NIR spectroscopic analysis for cancer diagnostics was studied. The conventional high-resolution NIR spectroscopic method of kidney tumor diagnostics was replaced by a compact optical sensing device constructively represented by a set of four light-emitting diodes (LEDs) at selected wavelengths and one detecting photodiode. Two sensor prototypes were tested using 14 in vitro clinical samples of 7 different patients. Statistical data evaluation using principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) confirmed the general applicability of the LED-based sensing approach to kidney tumor detection. An additional validation of the results was performed by means of sample permutation. PMID:28825612

Chiral discrimination of α-hydroxy acids and N-Ts-α-amino acids induced by tetraaza macrocyclic chiral solvating agents by using 1H NMR spectroscopy.

PubMed

Lv, Caixia; Feng, Lei; Zhao, Hongmei; Wang, Guo; Stavropoulos, Pericles; Ai, Lin

2017-02-21

In the field of chiral recognition, reported chiral discrimination by 1 H NMR spectroscopy has mainly focused on various chiral analytes with a single chiral center, regarded as standard chiral substrates to evaluate the chiral discriminating abilities of a chiral auxiliary. Among them, chiral α-hydroxy acids, α-amino acids and their derivatives are chiral organic molecules involved in a wide variety of biological processes, and also play an important role in the area of preparation of pharmaceuticals, as they are part of the synthetic process in the production of chiral drug intermediates and protein-based drugs. In this paper, several α-hydroxy acids and N-Ts-α-amino acids were used to evaluate the chiral discriminating abilities of tetraaza macrocyclic chiral solvating agents (TAMCSAs) 1a-1d by 1 H NMR spectroscopy. The results indicate that α-hydroxy acids and N-Ts-α-amino acids were successfully discriminated in the presence of TAMCSAs 1a-1d by 1 H NMR spectroscopy in most cases. The enantiomers of the α-hydroxy acids and N-Ts-α-amino acids were assigned based on the change of integration of the 1 H NMR signals of the corresponding protons. The enantiomeric excesses (ee) of N-Ts-α-amino acids 11 with different optical compositions were calculated based on the integration of the 1 H NMR signals of the CH 3 protons (Ts group) of the enantiomers of (R)- and (S)-11 in the presence of TAMCSA 1b. At the same time, the possible chiral discriminating behaviors have been discussed by means of the Job plots of (±)-2 with TAMCSAs 1b and proposed theoretical models of the enantiomers of 2 and 6 with TAMCSA 1a, respectively.

Modulated Raman spectroscopy for enhanced identification of bladder tumor cells in urine samples.

PubMed

Canetta, Elisabetta; Mazilu, Michael; De Luca, Anna Chiara; Carruthers, Antonia E; Dholakia, Kishan; Neilson, Sam; Sargeant, Harry; Briscoe, Tina; Herrington, C Simon; Riches, Andrew C

2011-03-01

Standard Raman spectroscopy (SRS) is a noninvasive technique that is used in the biomedical field to discriminate between normal and cancer cells. However, the presence of a strong fluorescence background detracts from the use of SRS in real-time clinical applications. Recently, we have reported a novel modulated Raman spectroscopy (MRS) technique to extract the Raman spectra from the background. In this paper, we present the first application of MRS to the identification of human urothelial cells (SV-HUC-1) and bladder cancer cells (MGH) in urine samples. These results are compared to those obtained by SRS. Classification using the principal component analysis clearly shows that MRS allows discrimination between Raman spectra of SV-HUC-1 and MGH cells with high sensitivity (98%) and specificity (95%). MRS is also used to distinguish between SV-HUC-1 and MGH cells after exposure to urine for up to 6 h. We observe a marked change in the MRS of SV-HUC-1 and MGH cells with time in urine, indicating that the conditions of sample collection will be important for the application of this methodology to clinical urine samples.

The analysis of colored acrylic, cotton, and wool textile fibers using micro-Raman spectroscopy. Part 2: comparison with the traditional methods of fiber examination.

PubMed

Buzzini, Patrick; Massonnet, Genevieve

2015-05-01

In the second part of this survey, the ability of micro-Raman spectroscopy to discriminate 180 fiber samples of blue, black, and red cottons, wools, and acrylics was compared to that gathered with the traditional methods for the examination of textile fibers in a forensic context (including light microscopy methods, UV-vis microspectrophotometry and thin-layer chromatography). This study shows that the Raman technique plays a complementary and useful role to obtain further discriminations after the application of light microscopy methods and UV-vis microspectrophotometry and assure the nondestructive nature of the analytical sequence. These additional discriminations were observed despite the lower discriminating powers of Raman data considered individually, compared to those of light microscopy and UV-vis MSP. This study also confirms that an instrument equipped with several laser lines is necessary for an efficient use as applied to the examination of textile fibers in a forensic setting. © 2015 American Academy of Forensic Sciences.

Evaluation of portable Raman spectroscopy and handheld X-ray fluorescence analysis (hXRF) for the direct analysis of glyptics

NASA Astrophysics Data System (ADS)

Lauwers, D.; Candeias, A.; Coccato, A.; Mirao, J.; Moens, L.; Vandenabeele, P.

2016-03-01

In archaeometry, the advantages of a combined use of Raman spectroscopy and X-ray fluorescence spectroscopy are extensively discussed for applications such as the analysis of paintings, manuscripts, pottery, etc. Here, we demonstrate for the first time the advantage of using both techniques for analysing glyptics. These engraved gemstones or glass materials were originally used as stamps, to identify the owner, for instance on letters, but also on wine vessels. For this research, a set of 64 glyptics (42 Roman glass specimens and 22 modern ones), belonging to the collection of the museum 'Quinta das Cruzes' in Funchal (Madeira, Portugal), was analysed with portable Raman spectroscopy and handheld X-ray fluorescence (hXRF). These techniques were also used to confirm the gemological identification of these precious objects and can give extra information about the glass composition. Raman spectroscopy identifies the molecular composition as well as on the crystalline phases present. On the other hand, hXRF results show that the antique Roman glass samples are characterised with low Pb and Sn levels and that the modern specimens can be discriminated in two groups: lead-based and non-lead-based ones.

Determination of HER2 amplification status in breast cancer cells using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Bi, Xiaohong; Rexer, Brent; Arteaga, Carlos L.; Guo, Mingsheng; Li, Ming; Mahadevan-Jansen, Anita

2010-02-01

The overexpression of HER2 (human epidermal growth factor receptor 2) in breast cancer is associated with increased disease recurrence and worse prognosis. Current diagnosis of HER2 positive breast cancer is time consuming with an estimated 20% inaccuracy. Raman spectroscopy is a proven method for pathological diagnosis based on the molecular composition of tissues. This study aimed to determine the feasibility of Raman spectroscopy to differentially identify the amplification of HER2 in cells. Three cell lines including BT474 (HER2 overexpressing breast cancer cell), MCF-10A (human breast epithelial cell), and MCF-10A with overexpressing HER2, were investigated using a bench top confocal Raman system. A diagnostic algorithm based on generalized linear model (GLM) with elastic-net penalties was established to discriminate 318 spectra collected from the cells, and to identify the spectra regions that differentiate the cell lines. The algorithm was able to differentially identify BT474 breast cancer cells with an overall sensitivity of 100% and specificity of 99%. The results demonstrate the capability of Raman spectroscopy to determine HER2 status in cells. Raman spectroscopy shows promise for application in the diagnosis of HER2 positive breast cancer in clinical practice.

Pharmaceutical Raw Material Identification Using Miniature Near-Infrared (MicroNIR) Spectroscopy and Supervised Pattern Recognition Using Support Vector Machine

PubMed Central

Hsiung, Chang; Pederson, Christopher G.; Zou, Peng; Smith, Valton; von Gunten, Marc; O’Brien, Nada A.

2016-01-01

Near-infrared spectroscopy as a rapid and non-destructive analytical technique offers great advantages for pharmaceutical raw material identification (RMID) to fulfill the quality and safety requirements in pharmaceutical industry. In this study, we demonstrated the use of portable miniature near-infrared (MicroNIR) spectrometers for NIR-based pharmaceutical RMID and solved two challenges in this area, model transferability and large-scale classification, with the aid of support vector machine (SVM) modeling. We used a set of 19 pharmaceutical compounds including various active pharmaceutical ingredients (APIs) and excipients and six MicroNIR spectrometers to test model transferability. For the test of large-scale classification, we used another set of 253 pharmaceutical compounds comprised of both chemically and physically different APIs and excipients. We compared SVM with conventional chemometric modeling techniques, including soft independent modeling of class analogy, partial least squares discriminant analysis, linear discriminant analysis, and quadratic discriminant analysis. Support vector machine modeling using a linear kernel, especially when combined with a hierarchical scheme, exhibited excellent performance in both model transferability and large-scale classification. Hence, ultra-compact, portable and robust MicroNIR spectrometers coupled with SVM modeling can make on-site and in situ pharmaceutical RMID for large-volume applications highly achievable. PMID:27029624

A reliable Raman-spectroscopy-based approach for diagnosis, classification and follow-up of B-cell acute lymphoblastic leukemia

NASA Astrophysics Data System (ADS)

Managò, Stefano; Valente, Carmen; Mirabelli, Peppino; Circolo, Diego; Basile, Filomena; Corda, Daniela; de Luca, Anna Chiara

2016-04-01

Acute lymphoblastic leukemia type B (B-ALL) is a neoplastic disorder that shows high mortality rates due to immature lymphocyte B-cell proliferation. B-ALL diagnosis requires identification and classification of the leukemia cells. Here, we demonstrate the use of Raman spectroscopy to discriminate normal lymphocytic B-cells from three different B-leukemia transformed cell lines (i.e., RS4;11, REH, MN60 cells) based on their biochemical features. In combination with immunofluorescence and Western blotting, we show that these Raman markers reflect the relative changes in the potential biological markers from cell surface antigens, cytoplasmic proteins, and DNA content and correlate with the lymphoblastic B-cell maturation/differentiation stages. Our study demonstrates the potential of this technique for classification of B-leukemia cells into the different differentiation/maturation stages, as well as for the identification of key biochemical changes under chemotherapeutic treatments. Finally, preliminary results from clinical samples indicate high consistency of, and potential applications for, this Raman spectroscopy approach.

[Applications of near-infrared spectroscopy to analysis of traditional Chinese herbal medicine].

PubMed

Li, Yan-Zhou; Min, Shun-Geng; Liu, Xia

2008-07-01

Analysis of traditional Chinese herbal medicine is of great importance to its quality control Conventional analysis methods can not meet the requirement of rapid and on-line analysis because of complex process more experiences or needed. In recent years, near-infrared spectroscopy technique has been used for rapid determination of active components, on-line quality control, identification of counterfeit and discrimination of geographical origins of herbal medicines and so on, due to its advantages of simple pretreatment, high efficiency, convenience to use solid diffuse reflection spectroscopy and fiber. In the present paper, the principles and methods of near-infrared spectroscopy technique are introduced concisely. Especially, the applications of this technique in quantitative analysis and qualitative analysis of traditional Chinese herbal medicine are reviewed.

On the Identification of Rayon/Viscose as a Major Fraction of Microplastics in the Marine Environment: Discrimination between Natural and Manmade Cellulosic Fibers Using Fourier Transform Infrared Spectroscopy

PubMed Central

Comnea-Stancu, Ionela Raluca; Wieland, Karin; Ramer, Georg; Schwaighofer, Andreas

2016-01-01

This work was sparked by the reported identification of man-made cellulosic fibers (rayon/viscose) in the marine environment as a major fraction of plastic litter by Fourier transform infrared (FT-IR) transmission spectroscopy and library search. To assess the plausibility of such findings, both natural and man-made fibers were examined using FT-IR spectroscopy. Spectra acquired by transmission microscopy, attenuated total reflection (ATR) microscopy, and ATR spectroscopy were compared. Library search was employed and results show significant differences in the identification rate depending on the acquisition method of the spectra. Careful selection of search parameters and the choice of spectra acquisition method were found to be essential for optimization of the library search results. When using transmission spectra of fibers and ATR libraries it was not possible to differentiate between man-made and natural fibers. Successful differentiation of natural and man-made cellulosic fibers has been achieved for FT-IR spectra acquired by ATR microscopy and ATR spectroscopy, and application of ATR libraries. As an alternative, chemometric methods such as unsupervised hierarchical cluster analysis, principal component analysis, and partial least squares-discriminant analysis were employed to facilitate identification based on intrinsic relationships of sample spectra and successful discrimination of the fiber type could be achieved. Differences in the ATR spectra depending on the internal reflection element (Ge versus diamond) were observed as expected; however, these did not impair correct classification by chemometric analysis. Moreover, the effects of different levels of humidity on the IR spectra of natural and man-made fibers were investigated, too. It has been found that drying and re-humidification leads to intensity changes of absorption bands of the carbohydrate backbone, but does not impair the identification of the fiber type by library search or cluster analysis. PMID:27650982

Endoscopy-coupled Raman spectroscopy for in vivo discrimination of inflammatory bowel disease

NASA Astrophysics Data System (ADS)

Pence, I. J.; Nguyen, Q. T.; Bi, X.; Herline, A. J.; Beaulieu, D. M.; Horst, S. N.; Schwartz, D. A.; Mahadevan-Jansen, A.

2014-03-01

Inflammatory bowel disease (IBD), including ulcerative colitis (UC) and Crohn's colitis (CC), affects nearly 2 million Americans, and the incidence is increasing worldwide. It has been established that UC and CC are distinct forms of IBD and require different medical care, however the distinction made between UC and CC is based upon inexact clinical, radiological, endoscopic, and pathologic features. A diagnosis of indeterminate colitis occurs in up to 15% of patients when UC and CC features overlap and cannot be differentiated; in these patients, diagnosis relies on long term followup, success or failure of existing treatment, and recurrence of the disease. Thus, there is need for a tool that can improve the sensitivity and specificity for fast, accurate and automated diagnosis of IBD. Here we present colonoscopy-coupled fiber probe-based Raman spectroscopy as a novel in vivo diagnostic tool for IBD. This in vivo study of both healthy control (NC, N=10) and diagnosed IBD patients with UC (N=15) and CC (N=26) aims to characterize spectral signatures of NC, UC, and CC. Samples are correlated with tissue pathology markers and endoscopic evaluation. Optimal collection parameters for detection have been identified based upon the new, application specific instrument design. The collected spectra are processed and analyzed using multivariate statistical techniques to identify spectral markers and discriminate NC, UC, and CC. Development of spectral markers to discriminate disease type is a necessary first step in the development of real-time, accurate and automated in vivo detection of IBD during colonoscopy procedures.

ASTM clustering for improving coal analysis by near-infrared spectroscopy.

PubMed

Andrés, J M; Bona, M T

2006-11-15

Multivariate analysis techniques have been applied to near-infrared (NIR) spectra coals to investigate the relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding predictor variables. In this work, a whole set of coal samples was grouped into six more homogeneous clusters following the ASTM reference method for classification prior to the application of calibration methods to each coal set. The results obtained showed a considerable improvement of the error determination compared with the calibration for the whole sample set. For some groups, the established calibrations approached the quality required by the ASTM/ISO norms for laboratory analysis. To predict property values for a new coal sample it is necessary the assignation of that sample to its respective group. Thus, the discrimination and classification ability of coal samples by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) in the NIR range was also studied by applying Soft Independent Modelling of Class Analogy (SIMCA) and Linear Discriminant Analysis (LDA) techniques. Modelling of the groups by SIMCA led to overlapping models that cannot discriminate for unique classification. On the other hand, the application of Linear Discriminant Analysis improved the classification of the samples but not enough to be satisfactory for every group considered.

Blood identification and discrimination between human and nonhuman blood using portable Raman spectroscopy.

PubMed

Fujihara, J; Fujita, Y; Yamamoto, T; Nishimoto, N; Kimura-Kataoka, K; Kurata, S; Takinami, Y; Yasuda, T; Takeshita, H

2017-03-01

Raman spectroscopy is commonly used in chemistry to identify molecular structure. This technique is a nondestructive analysis and needs no sample preparation. Recently, Raman spectroscopy has been shown to be effective as a multipurpose analytical method for forensic applications. In the present study, blood identification and discrimination between human and nonhuman blood were performed by a portable Raman spectrometer, which can be used at a crime scene. To identify the blood and to discriminate between human and nonhuman blood, Raman spectra of bloodstains from 11 species (human, rat, mouse, cow, horse, sheep, pig, rabbit, cat, dog, and chicken) were taken using a portable Raman spectrometer. Raman peaks for blood (742, 1001, 1123, 1247, 1341, 1368, 1446, 1576, and 1619 cm -1 ) could be observed by the portable Raman spectrometer in all 11 species, and the human bloodstain could be distinguished from the nonhuman ones by using a principal component analysis. This analysis can be performed on a bloodstain sample of at least 3 months old. The portable Raman spectrometer can be used at a crime scene, and this analysis is useful for forensic examination.

Optimisation of wavelength modulated Raman spectroscopy: towards high throughput cell screening.

PubMed

Praveen, Bavishna B; Mazilu, Michael; Marchington, Robert F; Herrington, C Simon; Riches, Andrew; Dholakia, Kishan

2013-01-01

In the field of biomedicine, Raman spectroscopy is a powerful technique to discriminate between normal and cancerous cells. However the strong background signal from the sample and the instrumentation affects the efficiency of this discrimination technique. Wavelength Modulated Raman spectroscopy (WMRS) may suppress the background from the Raman spectra. In this study we demonstrate a systematic approach for optimizing the various parameters of WMRS to achieve a reduction in the acquisition time for potential applications such as higher throughput cell screening. The Signal to Noise Ratio (SNR) of the Raman bands depends on the modulation amplitude, time constant and total acquisition time. It was observed that the sampling rate does not influence the signal to noise ratio of the Raman bands if three or more wavelengths are sampled. With these optimised WMRS parameters, we increased the throughput in the binary classification of normal human urothelial cells and bladder cancer cells by reducing the total acquisition time to 6 s which is significantly lower in comparison to previous acquisition times required for the discrimination between similar cell types.

Rapid discrimination and determination of antibiotics drugs in plastic syringes using near infrared spectroscopy with chemometric analysis: Application to amoxicillin and penicillin.

PubMed

Lê, Laetitia Minh Mai; Eveleigh, Luc; Hasnaoui, Ikram; Prognon, Patrice; Baillet-Guffroy, Arlette; Caudron, Eric

2017-05-10

The aim of this study was to investigate near infrared spectroscopy (NIRS) combined to chemometric analysis to discriminate and quantify three antibiotics by direct measurement in plastic syringes.Solutions of benzylpenicillin (PENI), amoxicillin (AMOX) and amoxicillin/clavulanic acid (AMOX/CLAV) were analyzed at therapeutic concentrations in glass vials and plastic syringes with NIR spectrometer by direct measurement. Chemometric analysis using partial least squares regression and discriminative analysis was conducted to develop qualitative and quantitative calibration models. Discrimination of the three antibiotics was optimal for concentrated solutions with 100% of accuracy. For quantitative analysis, the three antibiotics furnished a linear response (R²>0.9994) for concentrations ranging from 0.05 to 0.2 g/mL for AMOX, 0.1 to 1.0 MUI/mL for PENI and 0.005 to 0.05 g/mL for AMOX/CLAV with excellent repeatability (maximum 1.3%) and intermediate precision (maximum of 3.2%). Based on proposed models, 94.4% of analyzed AMOX syringes, 80.0% of AMOX/CLAV syringes and 85.7% of PENI syringes were compliant with a relative error including the limit of ± 15%.NIRS as rapid, non-invasive and non-destructive analytical method represents a potentially powerful tool to further develop for securing the drug administration circuit of healthcare institutions to ensure that patients receive the correct product at the right dose. Copyright © 2017 Elsevier B.V. All rights reserved.

Changes in hemp secondary fiber production related to technical fiber variability revealed by light microscopy and attenuated total reflectance Fourier transform infrared spectroscopy

PubMed Central

Fernandez-Tendero, Eva; Day, Arnaud; Legros, Sandrine; Habrant, Anouck; Hawkins, Simon

2017-01-01

Interest in hemp (Cannabis sativa L.) is increasing due to the development of a new range of industrial applications based on bast fibers. However the variability of bast fiber yield and quality represents an important barrier to further exploitation. Primary and secondary fiber content was examined in two commercial hemp varieties (Fedora 17, Santhica 27) grown under contrasted sowing density and irrigation conditions. Both growing conditions and hemp varieties impact stem tissue architecture with a large effect on the proportion of secondary fibers but not primary fibers. Attenuated total reflectance infrared spectroscopy allowed the discrimination of manually-isolated native primary fibers and secondary fibers but did not reveal any clustering according to growing conditions and variety. Infrared data were confirmed by wet chemistry analyses that revealed slight but significant differences between primary and secondary fiber cell wall composition. Infrared spectroscopy of technical fibers obtained after mechanical defibering revealed differences with native primary, but not secondary fibers and also discriminated samples obtained from plants grown under different conditions. Altogether the results suggested that the observed variability of hemp technical fibers could be partially explained by i) differences in secondary fiber production and ii) differential behavior during mechanical defibering resulting in unequal separation of primary and secondary fibers. PMID:28640922

Changes in hemp secondary fiber production related to technical fiber variability revealed by light microscopy and attenuated total reflectance Fourier transform infrared spectroscopy.

PubMed

Fernandez-Tendero, Eva; Day, Arnaud; Legros, Sandrine; Habrant, Anouck; Hawkins, Simon; Chabbert, Brigitte

2017-01-01

Interest in hemp (Cannabis sativa L.) is increasing due to the development of a new range of industrial applications based on bast fibers. However the variability of bast fiber yield and quality represents an important barrier to further exploitation. Primary and secondary fiber content was examined in two commercial hemp varieties (Fedora 17, Santhica 27) grown under contrasted sowing density and irrigation conditions. Both growing conditions and hemp varieties impact stem tissue architecture with a large effect on the proportion of secondary fibers but not primary fibers. Attenuated total reflectance infrared spectroscopy allowed the discrimination of manually-isolated native primary fibers and secondary fibers but did not reveal any clustering according to growing conditions and variety. Infrared data were confirmed by wet chemistry analyses that revealed slight but significant differences between primary and secondary fiber cell wall composition. Infrared spectroscopy of technical fibers obtained after mechanical defibering revealed differences with native primary, but not secondary fibers and also discriminated samples obtained from plants grown under different conditions. Altogether the results suggested that the observed variability of hemp technical fibers could be partially explained by i) differences in secondary fiber production and ii) differential behavior during mechanical defibering resulting in unequal separation of primary and secondary fibers.

Fecal Near Infrared Spectroscopy to Discriminate Physiological Status in Giant Pandas

PubMed Central

Wiedower, Erin E.; Kouba, Andrew J.; Vance, Carrie K.; Hansen, Rachel L.; Tolleson, Douglas R.

2012-01-01

Giant panda (Ailuropoda melanoleuca) monitoring and research often require accurate estimates of population size and density. However, obtaining these estimates has been challenging. Innovative technologies, such as fecal near infrared reflectance spectroscopy (FNIRS), may be used to differentiate between sex, age class, and reproductive status as has been shown for several other species. The objective of this study was to determine if FNIRS could be similarly used for giant panda physiological discriminations. Based on samples from captive animals in four U.S. zoos, FNIRS calibrations correctly identified 78% of samples from adult males, 81% from adult females, 85% from adults, 89% from juveniles, 75% from pregnant and 70% from non-pregnant females. However, diet had an impact on the success of the calibrations. When diet was controlled for plant part such that “leaf only” feces were evaluated, FNIRS calibrations correctly identified 93% of samples from adult males and 95% from adult females. These data show that FNIRS has the potential to differentiate between the sex, age class, and reproductive status in the giant panda and may be applicable for surveying wild populations. PMID:22719982

Metabolic fingerprinting of fresh lymphoma samples used to discriminate between follicular and diffuse large B-cell lymphomas.

PubMed

Barba, Ignasi; Sanz, Carolina; Barbera, Angels; Tapia, Gustavo; Mate, José-Luis; Garcia-Dorado, David; Ribera, Josep-Maria; Oriol, Albert

2009-11-01

To investigate if proton nuclear magnetic resonance ((1)H NMR) spectroscopy-based metabolic profiling was able to differentiate follicular lymphoma (FL) from diffuse large B-cell lymphoma (DLBCL) and to study which metabolites were responsible for the differences. High-resolution (1)H NMR spectra was obtained from fresh samples of lymph node biopsies obtained consecutively at one center (14 FL and 17 DLBCL). Spectra were processed using pattern-recognition methods. Discriminant models were able to differentiate between the two tumor types with a 86% sensitivity and a 76% specificity; the metabolites that most contributed to the discrimination were a relative increase of alanine in the case of DLBCL and a relative increase of taurine in FL. Metabolic models had a significant but weak correlation with Ki67 expression (r(2)=0.42; p=0.002) We have proved that it is possible to differentiate between FL and DLBCL based on their NMR metabolic profiles. This approach may potentially be applicable as a noninvasive tool for diagnostic and treatment follow-up in the clinical setting using conventional magnetic resonance systems.

Hybrid interferometric/dispersive atomic spectroscopy of laser-induced uranium plasma

DOE PAGES

Morgan, Phyllis K.; Scott, Jill R.; Jovanovic, Igor

2015-12-19

An established optical emission spectroscopy technique, laser-induced breakdown spectroscopy (LIBS), holds promise for detection and rapid analysis of elements relevant for nuclear safeguards, nonproliferation, and nuclear power, including the measurement of isotope ratios. One such important application of LIBS is the measurement of uranium enrichment ( 235U/ 238U), which requires high spectral resolution (e.g., 25 pm for the 424.4 nm U II line). High-resolution dispersive spectrometers necessary for such measurements are typically bulky and expensive. We demonstrate the use of an alternative measurement approach, which is based on an inexpensive and compact Fabry–Perot etalon integrated with a low to moderatemore » resolution Czerny–Turner spectrometer, to achieve the resolution needed for isotope selectivity of LIBS of uranium in ambient air. Furthermore, spectral line widths of ~ 10 pm have been measured at a center wavelength 424.437 nm, clearly discriminating the natural from the highly enriched uranium.« less

Selectivity/Specificity Improvement Strategies in Surface-Enhanced Raman Spectroscopy Analysis

PubMed Central

Wang, Feng; Cao, Shiyu; Yan, Ruxia; Wang, Zewei; Wang, Dan; Yang, Haifeng

2017-01-01

Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for the discrimination, identification, and potential quantification of certain compounds/organisms. However, its real application is challenging due to the multiple interference from the complicated detection matrix. Therefore, selective/specific detection is crucial for the real application of SERS technique. We summarize in this review five selective/specific detection techniques (chemical reaction, antibody, aptamer, molecularly imprinted polymers and microfluidics), which can be applied for the rapid and reliable selective/specific detection when coupled with SERS technique. PMID:29160798

Combination of laser-induced breakdown spectroscopy and Raman spectroscopy for multivariate classification of bacteria

NASA Astrophysics Data System (ADS)

Prochazka, D.; Mazura, M.; Samek, O.; Rebrošová, K.; Pořízka, P.; Klus, J.; Prochazková, P.; Novotný, J.; Novotný, K.; Kaiser, J.

2018-01-01

In this work, we investigate the impact of data provided by complementary laser-based spectroscopic methods on multivariate classification accuracy. Discrimination and classification of five Staphylococcus bacterial strains and one strain of Escherichia coli is presented. The technique that we used for measurements is a combination of Raman spectroscopy and Laser-Induced Breakdown Spectroscopy (LIBS). Obtained spectroscopic data were then processed using Multivariate Data Analysis algorithms. Principal Components Analysis (PCA) was selected as the most suitable technique for visualization of bacterial strains data. To classify the bacterial strains, we used Neural Networks, namely a supervised version of Kohonen's self-organizing maps (SOM). We were processing results in three different ways - separately from LIBS measurements, from Raman measurements, and we also merged data from both mentioned methods. The three types of results were then compared. By applying the PCA to Raman spectroscopy data, we observed that two bacterial strains were fully distinguished from the rest of the data set. In the case of LIBS data, three bacterial strains were fully discriminated. Using a combination of data from both methods, we achieved the complete discrimination of all bacterial strains. All the data were classified with a high success rate using SOM algorithm. The most accurate classification was obtained using a combination of data from both techniques. The classification accuracy varied, depending on specific samples and techniques. As for LIBS, the classification accuracy ranged from 45% to 100%, as for Raman Spectroscopy from 50% to 100% and in case of merged data, all samples were classified correctly. Based on the results of the experiments presented in this work, we can assume that the combination of Raman spectroscopy and LIBS significantly enhances discrimination and classification accuracy of bacterial species and strains. The reason is the complementarity in obtained chemical information while using these two methods.

Discrimination of transgenic soybean seeds by terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Wei; Liu, Changhong; Chen, Feng; Yang, Jianbo; Zheng, Lei

2016-10-01

Discrimination of genetically modified organisms is increasingly demanded by legislation and consumers worldwide. The feasibility of a non-destructive discrimination of glyphosate-resistant and conventional soybean seeds and their hybrid descendants was examined by terahertz time-domain spectroscopy system combined with chemometrics. Principal component analysis (PCA), least squares-support vector machines (LS-SVM) and PCA-back propagation neural network (PCA-BPNN) models with the first and second derivative and standard normal variate (SNV) transformation pre-treatments were applied to classify soybean seeds based on genotype. Results demonstrated clear differences among glyphosate-resistant, hybrid descendants and conventional non-transformed soybean seeds could easily be visualized with an excellent classification (accuracy was 88.33% in validation set) using the LS-SVM and the spectra with SNV pre-treatment. The results indicated that THz spectroscopy techniques together with chemometrics would be a promising technique to distinguish transgenic soybean seeds from non-transformed seeds with high efficiency and without any major sample preparation.

Discrimination of lymphoma using laser-induced breakdown spectroscopy conducted on whole blood samples

PubMed Central

Chen, Xue; Li, Xiaohui; Yang, Sibo; Yu, Xin; Liu, Aichun

2018-01-01

Lymphoma is a significant cancer that affects the human lymphatic and hematopoietic systems. In this work, discrimination of lymphoma using laser-induced breakdown spectroscopy (LIBS) conducted on whole blood samples is presented. The whole blood samples collected from lymphoma patients and healthy controls are deposited onto standard quantitative filter papers and ablated with a 1064 nm Q-switched Nd:YAG laser. 16 atomic and ionic emission lines of calcium (Ca), iron (Fe), magnesium (Mg), potassium (K) and sodium (Na) are selected to discriminate the cancer disease. Chemometric methods, including principal component analysis (PCA), linear discriminant analysis (LDA) classification, and k nearest neighbor (kNN) classification are used to build the discrimination models. Both LDA and kNN models have achieved very good discrimination performances for lymphoma, with an accuracy of over 99.7%, a sensitivity of over 0.996, and a specificity of over 0.997. These results demonstrate that the whole-blood-based LIBS technique in combination with chemometric methods can serve as a fast, less invasive, and accurate method for detection and discrimination of human malignancies. PMID:29541503

Study on discrimination of oral cancer from normal using blood plasma based on fluorescence steady and excited state at excitation wavelength 280 nm

NASA Astrophysics Data System (ADS)

Rekha, Pachaiappan; Aruna, Prakasa Rao; Ganesan, Singaravelu

2016-03-01

Many research works based on fluorescence spectroscopy have proven its potential in the diagnosis of various diseases using the spectral signatures of the native key fluorophores such as tryptophan, tyrosine, collagen, NADH, FAD and porphyrin. These fluorophores distribution, concentration and their conformation may be changed depending upon the pathological and metabolic conditions of cells and tissues. In this study, we have made an attempt to characterize the blood plasma of normal subject and oral cancer patients by native fluorescence spectroscopy at 280 nm excitation. Further, the fluorescence data were analyzed by employing the multivariate statistical method - linear discriminant analyses (LDA) using leaves one out cross validation method. The results illustrate the potential of fluorescence spectroscopy technique in the diagnosis of oral cancer using blood plasma.

Diagnosing basal cell carcinoma in vivo by near-infrared Raman spectroscopy: a Principal Components Analysis discrimination algorithm

NASA Astrophysics Data System (ADS)

Silveira, Landulfo, Jr.; Silveira, Fabrício L.; Bodanese, Benito; Pacheco, Marcos Tadeu T.; Zângaro, Renato A.

2012-02-01

This work demonstrated the discrimination among basal cell carcinoma (BCC) and normal human skin in vivo using near-infrared Raman spectroscopy. Spectra were obtained in the suspected lesion prior resectional surgery. After tissue withdrawn, biopsy fragments were submitted to histopathology. Spectra were also obtained in the adjacent, clinically normal skin. Raman spectra were measured using a Raman spectrometer (830 nm) with a fiber Raman probe. By comparing the mean spectra of BCC with the normal skin, it has been found important differences in the 800-1000 cm-1 and 1250-1350 cm-1 (vibrations of C-C and amide III, respectively, from lipids and proteins). A discrimination algorithm based on Principal Components Analysis and Mahalanobis distance (PCA/MD) could discriminate the spectra of both tissues with high sensitivity and specificity.

Rapid differentiation of Ghana cocoa beans by FT-NIR spectroscopy coupled with multivariate classification

NASA Astrophysics Data System (ADS)

Teye, Ernest; Huang, Xingyi; Dai, Huang; Chen, Quansheng

2013-10-01

Quick, accurate and reliable technique for discrimination of cocoa beans according to geographical origin is essential for quality control and traceability management. This current study presents the application of Near Infrared Spectroscopy technique and multivariate classification for the differentiation of Ghana cocoa beans. A total of 194 cocoa bean samples from seven cocoa growing regions were used. Principal component analysis (PCA) was used to extract relevant information from the spectral data and this gave visible cluster trends. The performance of four multivariate classification methods: Linear discriminant analysis (LDA), K-nearest neighbors (KNN), Back propagation artificial neural network (BPANN) and Support vector machine (SVM) were compared. The performances of the models were optimized by cross validation. The results revealed that; SVM model was superior to all the mathematical methods with a discrimination rate of 100% in both the training and prediction set after preprocessing with Mean centering (MC). BPANN had a discrimination rate of 99.23% for the training set and 96.88% for prediction set. While LDA model had 96.15% and 90.63% for the training and prediction sets respectively. KNN model had 75.01% for the training set and 72.31% for prediction set. The non-linear classification methods used were superior to the linear ones. Generally, the results revealed that NIR Spectroscopy coupled with SVM model could be used successfully to discriminate cocoa beans according to their geographical origins for effective quality assurance.

Assessment and forensic application of laser-induced breakdown spectroscopy (LIBS) for the discrimination of Australian window glass.

PubMed

El-Deftar, Moteaa M; Speers, Naomi; Eggins, Stephen; Foster, Simon; Robertson, James; Lennard, Chris

2014-08-01

A commercially available laser-induced breakdown spectroscopy (LIBS) instrument was evaluated for the determination of elemental composition of twenty Australian window glass samples, consisting of 14 laminated samples and 6 non-laminated samples (or not otherwise specified) collected from broken windows at crime scenes. In this study, the LIBS figures of merit were assessed in terms of accuracy, limits of detection and precision using three standard reference materials (NIST 610, 612, and 1831). The discrimination potential of LIBS was compared to that obtained using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), X-ray microfluorescence spectroscopy (μXRF) and scanning electron microscopy energy dispersive X-ray spectrometry (SEM-EDX) for the analysis of architectural window glass samples collected from crime scenes in the Canberra region, Australia. Pairwise comparisons were performed using a three-sigma rule, two-way ANOVA and Tukey's HSD test at 95% confidence limit in order to investigate the discrimination power for window glass analysis. The results show that the elemental analysis of glass by LIBS provides a discrimination power greater than 97% (>98% when combined with refractive index data), which was comparable to the discrimination powers obtained by LA-ICP-MS and μXRF. These results indicate that LIBS is a feasible alternative to the more expensive LA-ICP-MS and μXRF options for the routine forensic analysis of window glass samples. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Characterization of semiconductor materials using synchrotron radiation-based near-field infrared microscopy and nano-FTIR spectroscopy.

PubMed

Hermann, Peter; Hoehl, Arne; Ulrich, Georg; Fleischmann, Claudia; Hermelink, Antje; Kästner, Bernd; Patoka, Piotr; Hornemann, Andrea; Beckhoff, Burkhard; Rühl, Eckart; Ulm, Gerhard

2014-07-28

We describe the application of scattering-type near-field optical microscopy to characterize various semiconducting materials using the electron storage ring Metrology Light Source (MLS) as a broadband synchrotron radiation source. For verifying high-resolution imaging and nano-FTIR spectroscopy we performed scans across nanoscale Si-based surface structures. The obtained results demonstrate that a spatial resolution below 40 nm can be achieved, despite the use of a radiation source with an extremely broad emission spectrum. This approach allows not only for the collection of optical information but also enables the acquisition of near-field spectral data in the mid-infrared range. The high sensitivity for spectroscopic material discrimination using synchrotron radiation is presented by recording near-field spectra from thin films composed of different materials used in semiconductor technology, such as SiO2, SiC, SixNy, and TiO2.

In vivo study for the discrimination of cancerous and normal skin using fibre probe-based Raman spectroscopy.

PubMed

Schleusener, Johannes; Gluszczynska, Patrycja; Reble, Carina; Gersonde, Ingo; Helfmann, Jürgen; Fluhr, Joachim W; Lademann, Jürgen; Röwert-Huber, Joachim; Patzelt, Alexa; Meinke, Martina C

2015-10-01

Raman spectroscopy has proved its capability as an objective, non-invasive tool for the detection of various melanoma and non-melanoma skin cancers (NMSC) in a number of studies. Most publications are based on a Raman microspectroscopic ex vivo approach. In this in vivo clinical evaluation, we apply Raman spectroscopy using a fibre-coupled probe that allows access to a multitude of affected body sites. The probe design is optimized for epithelial sensitivity, whereby a large part of the detected signal originates from within the epidermal layer's depth down to the basal membrane where early stages of skin cancer develop. Data analysis was performed on measurements of 104 subjects scheduled for excision of lesions suspected of being malignant melanoma (MM) (n = 36), basal cell carcinoma (BCC) (n = 39) and squamous cell carcinoma (SCC) (n = 29). NMSC were discriminated from normal skin with a balanced accuracy of 73% (BCC) and 85% (SCC) using partial least squares discriminant analysis (PLS-DA). Discriminating MM and pigmented nevi (PN) resulted in a balanced accuracy of 91%. These results lie within the range of comparable in vivo studies and the accuracies achieved by trained dermatologists using dermoscopy. Discrimination proved to be unsuccessful between cancerous lesions and suspicious lesions that had been histopathologically verified as benign by dermoscopy. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Soft and Robust Identification of Body Fluid Using Fourier Transform Infrared Spectroscopy and Chemometric Strategies for Forensic Analysis.

PubMed

Takamura, Ayari; Watanabe, Ken; Akutsu, Tomoko; Ozawa, Takeaki

2018-05-31

Body fluid (BF) identification is a critical part of a criminal investigation because of its ability to suggest how the crime was committed and to provide reliable origins of DNA. In contrast to current methods using serological and biochemical techniques, vibrational spectroscopic approaches provide alternative advantages for forensic BF identification, such as non-destructivity and versatility for various BF types and analytical interests. However, unexplored issues remain for its practical application to forensics; for example, a specific BF needs to be discriminated from all other suspicious materials as well as other BFs, and the method should be applicable even to aged BF samples. Herein, we describe an innovative modeling method for discriminating the ATR FT-IR spectra of various BFs, including peripheral blood, saliva, semen, urine and sweat, to meet the practical demands described above. Spectra from unexpected non-BF samples were efficiently excluded as outliers by adopting the Q-statistics technique. The robustness of the models against aged BFs was significantly improved by using the discrimination scheme of a dichotomous classification tree with hierarchical clustering. The present study advances the use of vibrational spectroscopy and a chemometric strategy for forensic BF identification.

A pulse-shape discrimination method for improving Gamma-ray spectrometry based on a new digital shaping filter

NASA Astrophysics Data System (ADS)

Qin, Zhang-jian; Chen, Chuan; Luo, Jun-song; Xie, Xing-hong; Ge, Liang-quan; Wu, Qi-fan

2018-04-01

It is a usual practice for improving spectrum quality by the mean of designing a good shaping filter to improve signal-noise ratio in development of nuclear spectroscopy. Another method is proposed in the paper based on discriminating pulse-shape and discarding the bad pulse whose shape is distorted as a result of abnormal noise, unusual ballistic deficit or bad pulse pile-up. An Exponentially Decaying Pulse (EDP) generated in nuclear particle detectors can be transformed into a Mexican Hat Wavelet Pulse (MHWP) and the derivation process of the transform is given. After the transform is performed, the baseline drift is removed in the new MHWP. Moreover, the MHWP-shape can be discriminated with the three parameters: the time difference between the two minima of the MHWP, and the two ratios which are from the amplitude of the two minima respectively divided by the amplitude of the maximum in the MHWP. A new type of nuclear spectroscopy was implemented based on the new digital shaping filter and the Gamma-ray spectra were acquired with a variety of pulse-shape discrimination levels. It had manifested that the energy resolution and the peak-Compton ratio were both improved after the pulse-shape discrimination method was used.

Evaluation of portable Raman spectroscopy and handheld X-ray fluorescence analysis (hXRF) for the direct analysis of glyptics.

PubMed

Lauwers, D; Candeias, A; Coccato, A; Mirao, J; Moens, L; Vandenabeele, P

2016-03-15

In archaeometry, the advantages of a combined use of Raman spectroscopy and X-ray fluorescence spectroscopy are extensively discussed for applications such as the analysis of paintings, manuscripts, pottery, etc. Here, we demonstrate for the first time the advantage of using both techniques for analysing glyptics. These engraved gemstones or glass materials were originally used as stamps, to identify the owner, for instance on letters, but also on wine vessels. For this research, a set of 64 glyptics (42 Roman glass specimens and 22 modern ones), belonging to the collection of the museum 'Quinta das Cruzes' in Funchal (Madeira, Portugal), was analysed with portable Raman spectroscopy and handheld X-ray fluorescence (hXRF). These techniques were also used to confirm the gemological identification of these precious objects and can give extra information about the glass composition. Raman spectroscopy identifies the molecular composition as well as on the crystalline phases present. On the other hand, hXRF results show that the antique Roman glass samples are characterised with low Pb and Sn levels and that the modern specimens can be discriminated in two groups: lead-based and non-lead-based ones. Copyright © 2015 Elsevier B.V. All rights reserved.

Optical system for tablet variety discrimination using visible/near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Shao, Yongni; He, Yong; Hu, Xingyue

2007-12-01

An optical system based on visible/near-infrared spectroscopy (Vis/NIRS) for variety discrimination of ginkgo (Ginkgo biloba L.) tablets was developed. This system consisted of a light source, beam splitter system, sample chamber, optical detector (diffuse reflection detector), and data collection. The tablet varieties used in the research include Da na kang, Xin bang, Tian bao ning, Yi kang, Hua na xing, Dou le, Lv yuan, Hai wang, and Ji yao. All samples (n=270) were scanned in the Vis/NIR region between 325 and 1075 nm using a spectrograph. The chemometrics method of principal component artificial neural network (PC-ANN) was used to establish discrimination models of them. In PC-ANN models, the scores of the principal components were chosen as the input nodes for the input layer of ANN, and the best discrimination rate of 91.1% was reached. Principal component analysis was also executed to select several optimal wavelengths based on loading values. Wavelengths at 481, 458, 466, 570, 1000, 662, and 400 nm were then used as the input data of stepwise multiple linear regression, the regression equation of ginkgo tablets was obtained, and the discrimination rate was researched 84.4%. The results indicated that this optical system could be applied to discriminating ginkgo (Ginkgo biloba L.) tablets, and it supplied a new method for fast ginkgo tablet variety discrimination.

Discrimination of 1990s original automotive paint systems: a collaborative study of black nonmetallic base coat/clear coat finishes using infrared spectroscopy.

PubMed

Ryland, S; Bishea, G; Brun-Conti, L; Eyring, M; Flanagan, B; Jergovich, T; MacDougall, D; Suzuki, E

2001-01-01

The 1990s saw the introduction of significantly new types of paint binder chemistries into the automotive finish coat market. Considering the pronounced changes in the binders that can now be found in automotive paints and their potential use in a wide variety of finishes worldwide, the Paint Subgroup of the Scientific Working Group for Materials (SWGMAT) initiated a validation study to investigate the ability of commonly accepted methods of forensic paint examination to differentiate between these newer types of paints. Nine automotive paint systems typical of original equipment applications were acquired from General Motors Corporation in 1992. They consisted of steel panels coated with typical electrocoat primers and/or primer surfacers followed by a black nonmetallic base coat and clear coat. The primary purpose of this study was to evaluate the discrimination power of common forensic techniques when applied to the newer generation original automotive finishes. The second purpose was to evaluate interlaboratory reproducibility of automotive paint spectra collected on a variety of Fourier transform infrared (FT-IR) spectrometers and accessories normally used for forensic paint examinations. The results demonstrate that infrared spectroscopy is an effective tool for discriminating between the major automotive paint manufacturers' formulation types which are currently used in original finishes. Furthermore, and equally important, the results illustrate that the mid-infrared spectra of these finishes are generally quite reproducible even when comparing data from different laboratories, commercial FT-IR instruments, and accessories in a "real world," mostly uncontrolled, environment.

QCL-based standoff and proximal chemical detectors

NASA Astrophysics Data System (ADS)

Dupuis, Julia R.; Hensley, Joel; Cosofret, Bogdan R.; Konno, Daisei; Mulhall, Phillip; Schmit, Thomas; Chang, Shing; Allen, Mark; Marinelli, William J.

2016-05-01

The development of two longwave infrared quantum cascade laser (QCL) based surface contaminant detection platforms supporting government programs will be discussed. The detection platforms utilize reflectance spectroscopy with application to optically thick and thin materials including solid and liquid phase chemical warfare agents, toxic industrial chemicals and materials, and explosives. Operation at standoff (10s of m) and proximal (1 m) ranges will be reviewed with consideration given to the spectral signatures contained in the specular and diffusely reflected components of the signal. The platforms comprise two variants: Variant 1 employs a spectrally tunable QCL source with a broadband imaging detector, and Variant 2 employs an ensemble of broadband QCLs with a spectrally selective detector. Each variant employs a version of the Adaptive Cosine Estimator for detection and discrimination in high clutter environments. Detection limits of 5 μg/cm2 have been achieved through speckle reduction methods enabling detector noise limited performance. Design considerations for QCL-based standoff and proximal surface contaminant detectors are discussed with specific emphasis on speckle-mitigated and detector noise limited performance sufficient for accurate detection and discrimination regardless of the surface coverage morphology or underlying surface reflectivity. Prototype sensors and developmental test results will be reviewed for a range of application scenarios. Future development and transition plans for the QCL-based surface detector platforms are discussed.

Application of mid-infrared spectroscopy in analyzing different segmented production of Angelica by AB-8 macroporous resin

NASA Astrophysics Data System (ADS)

Guo, Yizhen; Wang, Jingjuan; Lu, Lina; Sun, Suqin; Liu, Yang; Xiao, Yao; Qin, Youwen; Xiao, Lijuan; Wen, Haoran; Qu, Lei

2016-01-01

As complicated mixture systems, chemical components of Angelica are very difficult to identify and discriminate, so as not to control its quality effectively. In recent years, Mid-infrared spectroscopy has been innovatively employed to identify and assess the quality of Traditional Chinese medicine (TCM) products. In this paper, the macroscopic IR fingerprint method including Fourier transform infrared spectroscopy (FT-IR), the second derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2D-IR), are applied to study and identify Angelica raw material, the decoction and different segmented production of AB-8 macroporous resin. FT-IR spectrum indicates that Angelica raw material is rich in sucrose and the correlation coefficient is 0.8465. The decoction of Angelica contains varieties of polysaccharides components and the content is gradually decreased with increasing concentration of ethanol. In addition, the decoction of Angelica contains a certain amount of protein components and 50% ethanol eluate has more protein than other eluates. Their second derivative spectra amplify the differences and reveal the potentially characteristic IR absorption bands, then we conclude that the decoction of Angelica contains a certain amount of ferulic acid and ligustilide. And 30% ethanol eluate, 50% ethanol eluate and 70% ethanol eluate are similar to ligustilide. Further, 2D-IR spectra enhance the spectral resolution and obtain much new information for discriminating the similar complicated samples. It is demonstrated that the above three-step infrared spectroscopy could be applicable for effective, visual and accurate analysis and identification of very complicated and similar mixture systems of traditional Chinese medicines.

Pattern recognition of visible and near-infrared spectroscopy from bayberry juice by use of partial least squares and a backpropagation neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cen Haiyan; Bao Yidan; He Yong

2006-10-10

Visible and near-infrared reflectance (visible-NIR) spectroscopy is applied to discriminate different varieties of bayberry juices. The discrimination of visible-NIR spectra from samples is a matter of pattern recognition. By partial least squares (PLS), the spectrum is reduced to certain factors, which are then taken as the input of the backpropagation neural network (BPNN). Through training and prediction, three different varieties of bayberry juice are classified based on the output of the BPNN. In addition, a mathematical model is built and the algorithm is optimized. With proper parameters in the training set,100% accuracy is obtained by the BPNN. Thus it ismore » concluded that the PLS analysis combined with the BPNN is an alternative for pattern recognition based on visible and NIR spectroscopy.« less

Detection and discrimination of microorganisms on various substrates with quantum cascade laser spectroscopy

NASA Astrophysics Data System (ADS)

Padilla-Jiménez, Amira C.; Ortiz-Rivera, William; Rios-Velazquez, Carlos; Vazquez-Ayala, Iris; Hernández-Rivera, Samuel P.

2014-06-01

Investigations focusing on devising rapid and accurate methods for developing signatures for microorganisms that could be used as biological warfare agents' detection, identification, and discrimination have recently increased significantly. Quantum cascade laser (QCL)-based spectroscopic systems have revolutionized many areas of defense and security including this area of research. In this contribution, infrared spectroscopy detection based on QCL was used to obtain the mid-infrared (MIR) spectral signatures of Bacillus thuringiensis, Escherichia coli, and Staphylococcus epidermidis. These bacteria were used as microorganisms that simulate biothreats (biosimulants) very truthfully. The experiments were conducted in reflection mode with biosimulants deposited on various substrates including cardboard, glass, travel bags, wood, and stainless steel. Chemometrics multivariate statistical routines, such as principal component analysis regression and partial least squares coupled to discriminant analysis, were used to analyze the MIR spectra. Overall, the investigated infrared vibrational techniques were useful for detecting target microorganisms on the studied substrates, and the multivariate data analysis techniques proved to be very efficient for classifying the bacteria and discriminating them in the presence of highly IR-interfering media.

Optical spectroscopy for food and beverages control

NASA Astrophysics Data System (ADS)

Mignani, Anna Grazia; Ciaccheri, Leonardo; Mencaglia, Andrea Azelio

2011-08-01

A selection of spectroscopy-based, fiber optic and micro-optic devices is presented. They have been designed and tested for monitoring the quality and safety of typical foodstuffs. The VIS-NIR spectra, considered as product fingerprints, allowed to discriminating the geographic region of production and to detecting nutritional and nutraceutic indicators.

Metabolic fingerprint of Brazilian maize landraces silk (stigma/styles) using NMR spectroscopy and chemometric methods.

PubMed

Kuhnen, Shirley; Bernardi Ogliari, Juliana; Dias, Paulo Fernando; da Silva Santos, Maiara; Ferreira, Antônio Gilberto; Bonham, Connie C; Wood, Karl Vernon; Maraschin, Marcelo

2010-02-24

Aqueous extract from maize silks is used by traditional medicine for the treatment of several ailments, mainly related to the urinary system. This work focuses on the application of NMR spectroscopy and chemometric analysis for the determination of metabolic fingerprint and pattern recognition of silk extracts from seven maize landraces cultivated in southern Brazil. Principal component analysis (PCA) of the (1)H NMR data set showed clear discrimination among the maize varieties by PC1 and PC2, pointing out three distinct metabolic profiles. Target compounds analysis showed significant differences (p < 0.05) in the contents of protocatechuic acid, gallic acid, t-cinnamic acid, and anthocyanins, corroborating the discrimination of the genotypes in this study as revealed by PCA analysis. Thus the combination of (1)H NMR and PCA is a useful tool for the discrimination of maize silks in respect to their chemical composition, including rapid authentication of the raw material of current pharmacological interest.

Fuji apple storage time rapid determination method using Vis/NIR spectroscopy.

PubMed

Liu, Fuqi; Tang, Xuxiang

2015-01-01

Fuji apple storage time rapid determination method using visible/near-infrared (Vis/NIR) spectroscopy was studied in this paper. Vis/NIR diffuse reflection spectroscopy responses to samples were measured for 6 days. Spectroscopy data were processed by stochastic resonance (SR). Principal component analysis (PCA) was utilized to analyze original spectroscopy data and SNR eigen value. Results demonstrated that PCA could not totally discriminate Fuji apples using original spectroscopy data. Signal-to-noise ratio (SNR) spectrum clearly classified all apple samples. PCA using SNR spectrum successfully discriminated apple samples. Therefore, Vis/NIR spectroscopy was effective for Fuji apple storage time rapid discrimination. The proposed method is also promising in condition safety control and management for food and environmental laboratories.

Fuji apple storage time rapid determination method using Vis/NIR spectroscopy

PubMed Central

Liu, Fuqi; Tang, Xuxiang

2015-01-01

Fuji apple storage time rapid determination method using visible/near-infrared (Vis/NIR) spectroscopy was studied in this paper. Vis/NIR diffuse reflection spectroscopy responses to samples were measured for 6 days. Spectroscopy data were processed by stochastic resonance (SR). Principal component analysis (PCA) was utilized to analyze original spectroscopy data and SNR eigen value. Results demonstrated that PCA could not totally discriminate Fuji apples using original spectroscopy data. Signal-to-noise ratio (SNR) spectrum clearly classified all apple samples. PCA using SNR spectrum successfully discriminated apple samples. Therefore, Vis/NIR spectroscopy was effective for Fuji apple storage time rapid discrimination. The proposed method is also promising in condition safety control and management for food and environmental laboratories. PMID:25874818

Authentication of animal origin of heparin and low molecular weight heparin including ovine, porcine and bovine species using 1D NMR spectroscopy and chemometric tools.

PubMed

Monakhova, Yulia B; Diehl, Bernd W K; Fareed, Jawed

2018-02-05

High resolution (600MHz) nuclear magnetic resonance (NMR) spectroscopy is used to distinguish heparin and low-molecular weight heparins (LMWHs) produced from porcine, bovine and ovine mucosal tissues as well as their blends. For multivariate analysis several statistical methods such as principal component analysis (PCA), factor discriminant analysis (FDA), partial least squares - discriminant analysis (PLS-DA), linear discriminant analysis (LDA) were utilized for the modeling of NMR data of more than 100 authentic samples. Heparin and LMWH samples from the independent test set (n=15) were 100% correctly classified according to its animal origin. Moreover, by using 1 H NMR coupled with chemometrics and several batches of bovine heparins from two producers were differentiated. Thus, NMR spectroscopy combined with chemometrics is an efficient tool for simultaneous identification of animal origin and process based manufacturing difference in heparin products. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative determination and evaluation of Paris polyphylla var. yunnanensis with different harvesting times using UPLC-UV-MS and FT-IR spectroscopy in combination with partial least squares discriminant analysis.

PubMed

Yang, Yuan-Gui; Zhang, Ji; Zhao, Yan-Li; Zhang, Jin-Yu; Wang, Yuan-Zhong

2017-07-01

A rapid method was developed and validated by ultra-performance liquid chromatography-triple quadrupole mass spectroscopy with ultraviolet detection (UPLC-UV-MS) for simultaneous determination of paris saponin I, paris saponin II, paris saponin VI and paris saponin VII. Partial least squares discriminant analysis (PLS-DA) based on UPLC and Fourier transform infrared (FT-IR) spectroscopy was employed to evaluate Paris polyphylla var. yunnanensis (PPY) at different harvesting times. Quantitative determination implied that the various contents of bioactive compounds with different harvesting times may lead to different pharmacological effects; the average content of total saponins for PPY harvested at 8 years was higher than that from other samples. The PLS-DA of FT-IR spectra had a better performance than that of UPLC for discrimination of PPY from different harvesting times. Copyright © 2016 John Wiley & Sons, Ltd.

Discrimination of Aurantii Fructus Immaturus and Fructus Poniciri Trifoliatae Immaturus by Flow Injection UV Spectroscopy (FIUV) and 1H NMR using Partial Least-squares Discriminant Analysis (PLS-DA)

USDA-ARS?s Scientific Manuscript database

Two simple fingerprinting methods, flow-injection UV spectroscopy (FIUV) and 1H nuclear magnetic resonance (NMR), for discrimination of Aurantii FructusImmaturus and Fructus Poniciri TrifoliataeImmaturususing were described. Both methods were combined with partial least-squares discriminant analysis...

Micro-Raman spectroscopy for meat type detection

NASA Astrophysics Data System (ADS)

De Biasio, M.; Stampfer, P.; Leitner, R.; Huck, C. W.; Wiedemair, V.; Balthasar, D.

2015-06-01

The recent horse meat scandal in Europe increased the demand for optical sensors that can identify meat type. Micro-Raman spectroscopy is a promising technique for the discrimination of meat types. Here, we present micro-Raman measurements of chicken, pork, turkey, mutton, beef and horse meat test samples. The data was analyzed with different combinations of data normalization and classification approaches. Our results show that Raman spectroscopy can discriminate between different meat types. Red and white meat are easily discriminated, however a sophisticated chemometric model is required to discriminate species within these groups.

[Application of support vector machine-recursive feature elimination algorithm in Raman spectroscopy for differential diagnosis of benign and malignant breast diseases].

PubMed

Zhang, Haipeng; Fu, Tong; Zhang, Zhiru; Fan, Zhimin; Zheng, Chao; Han, Bing

2014-08-01

To explore the value of application of support vector machine-recursive feature elimination (SVM-RFE) method in Raman spectroscopy for differential diagnosis of benign and malignant breast diseases. Fresh breast tissue samples of 168 patients (all female; ages 22-75) were obtained by routine surgical resection from May 2011 to May 2012 at the Department of Breast Surgery, the First Hospital of Jilin University. Among them, there were 51 normal tissues, 66 benign and 51 malignant breast lesions. All the specimens were assessed by Raman spectroscopy, and the SVM-RFE algorithm was used to process the data and build the mathematical model. Mahalanobis distance and spectral residuals were used as discriminating criteria to evaluate this data-processing method. 1 800 Raman spectra were acquired from the fresh samples of human breast tissues. Based on spectral profiles, the presence of 1 078, 1 267, 1 301, 1 437, 1 653, and 1 743 cm(-1) peaks were identified in the normal tissues; and 1 281, 1 341, 1 381, 1 417, 1 465, 1 530, and 1 637 cm(-1) peaks were found in the benign and malignant tissues. The main characteristic peaks differentiating benign and malignant lesions were 1 340 and 1 480 cm(-1). The accuracy of SVM-RFE in discriminating normal and malignant lesions was 100.0%, while that in the assessment of benign lesions was 93.0%. There are distinct differences among the Raman spectra of normal, benign and malignant breast tissues, and SVM-RFE method can be used to build differentiation model of breast lesions.

Discrimination of Cynanchum wilfordii and Cynanchum auriculatum by terahertz spectroscopic analysis.

PubMed

Ham, Woo Sik; Kim, Jinju; Park, Dae Joon; Ryu, Han-Cheol; Jang, Young Pyo

2018-02-12

Precise identification of botanical origin of plant species is crucial for the quality control of herbal medicine. In Korea, the root part of Cynanchum auriculatum has been misused for C. wilfordii in the herbal drug market due to their morphological similarities. Currently, DNA analysis using the polymerase chain reaction (PCR) method is employed to discriminate between these species. In order to develop a new analytical tool for the rapid discrimination of C. wilfordii and C. auriculatum, terahertz (THz) spectroscopy was employed. Authentic samples of C. wilfordii and C. auriculatum were provided from the National Institute and standardized pellets for each species were prepared to get optimum results with terahertz time-domain spectroscopy (THz-TDS) in frequency range 0.2-1.20 THz. The C. wilfordii pellet showed longer time delay compare to the sample of C. auriculatum and this was due to the difference in permittivity. The pellet samples of C. wilfordii and C. auriculatum showed a permittivity difference of about 0.08 at 0.2-1.20 THz. The experimental results indicated that THz-TDS analysis can be an effective and rapid method for the discrimination of C. wilfordii and C. auriculatum, and this application can be expanded for the discrimination of other similar herbal medicines. Copyright © 2018 John Wiley & Sons, Ltd.

A triple-crystal phoswich detector with digital pulse shape discrimination for alpha/beta/gamma spectroscopy

NASA Astrophysics Data System (ADS)

White, Travis L.; Miller, William H.

1999-02-01

Researchers at the University of Missouri - Columbia have developed a three-crystal phoswich detector coupled to a digital pulse shape discrimination system for use in alpha/beta/gamma spectroscopy. Phoswich detectors use a sandwich of scintillators viewed by a single photomultiplier tube to simultaneously detect multiple types of radiation. Separation of radiation types is based upon pulse shape difference among the phosphors, which has historically been performed with analog circuitry. The system uses a GaGe CompuScope 1012, 12 bit, 10 MHz computer-based oscilloscope that digitally captures the pulses from a phoswich detector and subsequently performs pulse shape discrimination with cross-correlation analysis. The detector, based partially on previous phoswich designs by Usuda et al., uses a 10 mg/cm 2 thick layer of ZnS(Ag) for alpha detection, followed by a 0.254 cm CaF 2(Eu) crystal for beta detection, all backed by a 2.54 cm NaI(Tl) crystal for gamma detection. Individual energy spectra and count rate information for all three radiation types are displayed and updated periodically. The system shows excellent charged particle discrimination with an accuracy of greater than 99%. Future development will include a large area beta probe with gamma-ray discrimination, systems for low-energy photon detection (e.g. Bremsstrahlung or keV-range photon emissions), and other health physics instrumentation.

A phoswich detector for simultaneous alpha-gamma spectroscopy

NASA Astrophysics Data System (ADS)

Moghadam, S. Rajabi; Feghhi, S. A. H.; Safari, M. J.

2015-11-01

Phoswich detectors are of value for radiation spectroscopy, especially in cases where a low-cost solution for a mixed radiation field is desired. Meanwhile, simultaneous spectroscopy of alpha particles and gamma-rays has many applications in quantification and distinguishing the alpha-emitting radionuclides which usually occur in the analysis of environmental solid samples. Here, we have developed a system for detection of radioactive actinides (e.g., 241Am) based on the alpha-gamma coincidence technique. The underlying concept, is to assemble two appropriately selected scintillators (i.e., a fast and a slow one) together with a discriminating unit for analysis of their data. Detailed Monte Carlo simulation procedure has been developed using the GEANT4 toolkit to design and find enough knowledge about the response of the system in the studied radiation field. Various comparisons were made between experimental and simulation data which showed appropriate agreement between them. The calibration was performed and the MDA was estimated as 60 mBq for the phoswich system.

Analytical Raman spectroscopic study for discriminant analysis of different animal-derived feedstuff: Understanding the high correlation between Raman spectroscopy and lipid characteristics.

PubMed

Gao, Fei; Xu, Lingzhi; Zhang, Yuejing; Yang, Zengling; Han, Lujia; Liu, Xian

2018-02-01

The objectives of the current study were to explore the correlation between Raman spectroscopy and lipid characteristics and to assess the potential of Raman spectroscopic methods for distinguishing the different sources of animal-originated feed based on lipid characteristics. A total of 105 lipid samples derived from five animal species have been analyzed by gas chromatography (GC) and FT-Raman spectroscopy. High correlations (r 2 >0.94) were found between the characteristic peak ratio of the Raman spectra (1654/1748 and 1654/1445) and the degree of unsaturation of the animal lipids. The results of FT-Raman data combined with chemometrics showed that the fishmeal, poultry, porcine and ruminant (bovine and ovine) MBMs could be well separated based on their lipid spectral characteristics. This study demonstrated that FT-Raman spectroscopy can mostly exhibit the lipid structure specificity of different species of animal-originated feed and can be used to discriminate different animal-originated feed samples. Copyright © 2017. Published by Elsevier Ltd.

[Study on the genuineness and producing area of Panax notoginseng based on infrared spectroscopy combined with discriminant analysis].

PubMed

Liu, Fei; Wang, Yuan-zhong; Yang, Chun-yan; Jin, Hang

2015-01-01

The genuineness and producing area of Panax notoginseng were studied based on infrared spectroscopy combined with discriminant analysis. The infrared spectra of 136 taproots of P. notoginseng from 13 planting point in 11 counties were collected and the second derivate spectra were calculated by Omnic 8. 0 software. The infrared spectra and their second derivate spectra in the range 1 800 - 700 cm-1 were used to build model by stepwise discriminant analysis, which was in order to distinguish study on the genuineness of P. notoginseng. The model built based on the second derivate spectra showed the better recognition effect for the genuineness of P. notoginseng. The correct rate of returned classification reached to 100%, and the prediction accuracy was 93. 4%. The stability of model was tested by cross validation and the method was performed extrapolation validation. The second derivate spectra combined with the same discriminant analysis method were used to distinguish the producing area of P. notoginseng. The recognition effect of models built based on different range of spectrum and different numbers of samples were compared and found that when the model was built by collecting 8 samples from each planting point as training sample and the spectrum in the range 1 500 - 1 200 cm-1 , the recognition effect was better, with the correct rate of returned classification reached to 99. 0%, and the prediction accuracy was 76. 5%. The results indicated that infrared spectroscopy combined with discriminant analysis showed good recognition effect for the genuineness of P. notoginseng. The method might be a hopeful new method for identification of genuineness of P. notoginseng in practice. The method could recognize the producing area of P. notoginseng to some extent and could be a new thought for identification of the producing area of P. natoginseng.

Optical biopsy of pre-malignant or degenerative lesions: the role of the inflammatory process

NASA Astrophysics Data System (ADS)

da Silva Martinho, Herculano

2011-03-01

Recent technological advances in fiber optics, light sources, detectors, and molecular biology have stimulated unprecedented development of optical methods to detect pathological changes in tissues. These methods, collectively termed "optical biopsy," are nondestructive in situ and real-time assays. Optical biopsy techniques as fluorescence spectroscopy, polarized light scattering spectroscopy, optical coherence tomography, confocal reflectance microscopy, and Raman spectroscopy had been extensively used to characterize several pathological tissues. In special, Raman spectroscopy technique had been able to probe several biochemical alterations due to pathology development as change in the DNA, glycogen, phospholipid, non-collagenous proteins. All studies claimed that the optical biopsy methods were able to discriminate normal and malignant tissues. However, few studies had been devoted to the discrimination of very common subtle or early pathological states as inflammatory process, which are always present on, e.g., cancer lesion border. In this work we present a systematic comparison of optical biopsy data on several kinds of lesions were inflammatory infiltrates play the role (breast, cervical, and oral lesion). It will be discussed the essential conditions for the optimization of discrimination among normal and alterated states based on statistical analysis.

Qualitative analysis of pure and adulterated canola oil via SIMCA

NASA Astrophysics Data System (ADS)

Basri, Katrul Nadia; Khir, Mohd Fared Abdul; Rani, Rozina Abdul; Sharif, Zaiton; Rusop, M.; Zoolfakar, Ahmad Sabirin

2018-05-01

This paper demonstrates the utilization of near infrared (NIR) spectroscopy to classify pure and adulterated sample of canola oil. Soft Independent Modeling Class Analogies (SIMCA) algorithm was implemented to discriminate the samples to its classes. Spectral data obtained was divided using Kennard Stone algorithm into training and validation dataset by a fixed ratio of 7:3. The model accuracy obtained based on the model built is 0.99 whereas the sensitivity and precision are 0.92 and 1.00. The result showed the classification model is robust to perform qualitative analysis of canola oil for future application.

Citrus species and hybrids depicted by near- and mid-infrared spectroscopy.

PubMed

Páscoa, Ricardo Nmj; Moreira, Silvana; Lopes, João A; Sousa, Clara

2018-01-31

Citrus trees are among the most cultivated plants in the world, with a high economic impact. The wide sexual compatibility among relatives gave rise to a large number of hybrids that are difficult to discriminate. This work sought to explore the ability of infrared spectroscopy to discriminate among Citrus species and/or hybrids and to contribute to the elucidation of its relatedness. Adult leaves of 18 distinct Citrus plants were included in this work. Near- and mid-infrared (NIR and FTIR) spectra were acquired from leaves after harvesting and a drying period of 1 month. Spectra were modelled by principal component analysis and partial least squares discriminant analysis. Both techniques revealed a high discrimination potential (78.5-95.9%), being the best results achieved with NIR spectroscopy and air-dried leaves (95.9%). Infrared spectroscopy was able to successfully discriminate several Citrus species and/or hybrids. Our results contributed also to enhance insights regarding the studied Citrus species and/or hybrids. Despite the benefit of including additional samples, the results herein obtained clearly pointed infrared spectroscopy as a reliable technique for Citrus species and/or hybrid discrimination. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Deuterated scintillators and their application to neutron spectroscopy

NASA Astrophysics Data System (ADS)

Febbraro, M.; Lawrence, C. C.; Zhu, H.; Pierson, B.; Torres-Isea, R. O.; Becchetti, F. D.; Kolata, J. J.; Riggins, J.

2015-06-01

Deuterated scintillators have been used as a tool for neutron spectroscopy without Neutron Time-of-Flight (n-ToF) for more than 30 years. This article will provide a brief historical overview of the technique and current uses of deuterated scintillators in the UM-DSA and DESCANT arrays. Pulse-shape discrimination and spectrum unfolding with the maximum-likelihood expectation maximization algorithm will be discussed. Experimental unfolding and cross section results from measurements of (d,n), (3He,n) and (α,n) reactions are shown.

Escherichia coli identification and strain discrimination using nanosecond laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Diedrich, Jonathan; Rehse, Steven J.; Palchaudhuri, Sunil

2007-04-01

Three strains of Escherichia coli, one strain of environmental mold, and one strain of Candida albicans yeast have been analyzed by laser-induced breakdown spectroscopy using nanosecond laser pulses. All microorganisms were analyzed while still alive and with no sample preparation. Nineteen atomic and ionic emission lines have been identified in the spectrum, which is dominated by calcium, magnesium, and sodium. A discriminant function analysis has been used to discriminate between the biotypes and E. coli strains. This analysis showed efficient discrimination between laser-induced breakdown spectroscopy spectra from different strains of a single bacteria species.

[Fast discrimination of edible vegetable oil based on Raman spectroscopy].

PubMed

Zhou, Xiu-Jun; Dai, Lian-Kui; Li, Sheng

2012-07-01

A novel method to fast discriminate edible vegetable oils by Raman spectroscopy is presented. The training set is composed of different edible vegetable oils with known classes. Based on their original Raman spectra, baseline correction and normalization were applied to obtain standard spectra. Two characteristic peaks describing the unsaturated degree of vegetable oil were selected as feature vectors; then the centers of all classes were calculated. For an edible vegetable oil with unknown class, the same pretreatment and feature extraction methods were used. The Euclidian distances between the feature vector of the unknown sample and the center of each class were calculated, and the class of the unknown sample was finally determined by the minimum distance. For 43 edible vegetable oil samples from seven different classes, experimental results show that the clustering effect of each class was more obvious and the class distance was much larger with the new feature extraction method compared with PCA. The above classification model can be applied to discriminate unknown edible vegetable oils rapidly and accurately.

In vivo characterization of colorectal metastases in human liver using diffuse reflectance spectroscopy: toward guidance in oncological procedures

NASA Astrophysics Data System (ADS)

Spliethoff, Jarich W.; de Boer, Lisanne L.; Meier, Mark A. J.; Prevoo, Warner; de Jong, Jeroen; Kuhlmann, Koert; Bydlon, Torre M.; Sterenborg, Henricus J. C. M.; Hendriks, Benno H. W.; Ruers, Theo J. M.

2016-09-01

There is a strong need to develop clinical instruments that can perform rapid tissue assessment at the tip of smart clinical instruments for a variety of oncological applications. This study presents the first in vivo real-time tissue characterization during 24 liver biopsy procedures using diffuse reflectance (DR) spectroscopy at the tip of a core biopsy needle with integrated optical fibers. DR measurements were performed along each needle path, followed by biopsy of the target lesion using the same needle. Interventional imaging was coregistered with the DR spectra. Pathology results were compared with the DR spectroscopy data at the final measurement position. Bile was the primary discriminator between normal liver tissue and tumor tissue. Relative differences in bile content matched with the tissue diagnosis based on histopathological analysis in all 24 clinical cases. Continuous DR measurements during needle insertion in three patients showed that the method can also be applied for biopsy guidance or tumor recognition during surgery. This study provides an important validation step for DR spectroscopy-based tissue characterization in the liver. Given the feasibility of the outlined approach, it is also conceivable to make integrated fiber-optic tools for other clinical procedures that rely on accurate instrument positioning.

The use of wavelength dispersive X-ray fluorescence in the identification of the elemental composition of vanilla samples and the determination of the geographic origin by discriminant function analysis.

PubMed

Hondrogiannis, Ellen; Rotta, Kathryn; Zapf, Charles M

2013-03-01

Sixteen elements found in 37 vanilla samples from Madagascar, Uganda, India, Indonesia (all Vanilla planifolia species), and Papa New Guinea (Vanilla tahitensis species) were measured by wavelength dispersive X-ray fluorescence (WDXRF) spectroscopy for the purpose of determining the elemental concentrations to discriminate among the origins. Pellets were prepared of the samples and elemental concentrations were calculated based on calibration curves created using 4 Natl. Inst. of Standards and Technology (NIST) standards. Discriminant analysis was used to successfully classify the vanilla samples by their species and their geographical region. Our method allows for higher throughput in the rapid screening of vanilla samples in less time than analytical methods currently available. Wavelength dispersive X-ray fluorescence spectroscopy and discriminant function analysis were used to classify vanilla from different origins resulting in a model that could potentially serve to rapidly validate these samples before purchasing from a producer. © 2013 Institute of Food Technologists®

Application of chemometrics in quality control of Turmeric (Curcuma longa) based on Ultra-violet, Fourier transform-infrared and 1H NMR spectroscopy.

PubMed

Gad, Haidy A; Bouzabata, Amel

2017-12-15

Turmeric (Curcuma longa L.) belongs to the family Zingiberaceae that is widely used as a spice in food preparations in addition to its biological activities. UV, FT-IR, 1 H NMR in addition to HPLC were applied to construct a metabolic fingerprint for Turmeric in an attempt to assess its quality. 30 samples were analyzed, and then principal component analysis (PCA) and hierarchical clustering analysis (HCA) were utilized to assess the differences and similarities between collected samples. PCA score plot based on both HPLC and UV spectroscopy showed the same discriminatory pattern, where the samples were segregated into four main groups depending on their total curcuminoids content. The results revealed that UV could be utilized as a simple and rapid alternative for HPLC. However, FT-IR failed to discriminate between the same species. By applying 1 H NMR, the metabolic variability between samples was more evident in the essential oils/fatty acid region. Copyright © 2017 Elsevier Ltd. All rights reserved.

Discrimination of wild-growing and cultivated Lentinus edodes by tri-step infrared spectroscopy

NASA Astrophysics Data System (ADS)

Lin, Haojian; Liu, Gang; Yang, Weimei; An, Ran; Ou, Quanhong

2018-01-01

It's not easy to discriminate dried wild-growing Lentinus edodes (WL) and cultivated Lentinus edodes (CL) by conventional method based on the morphological inspection of fruiting bodies. In this paper, fruiting body samples of WL and CL are discriminated by a tri-step IR spectroscopy method, including Fourier transform infrared (FT-IR) spectroscopy, second derivatives infrared (SD-IR) spectroscopy and two-dimensional correlation infrared (2D-IR) spectroscopy under thermal perturbation. The results show that the FT-IR spectra of WL and CL are similar in holistic spectral profile. More significant differences are exhibited in their SD-IR spectra in the range of 1700 - 900 cm-1. Furthermore, more evident differences have been observed in their synchronous 2D-IR spectra in the range of 2970 - 2900, 1678 - 1390, 1250 -1104 and 1090 - 1030 cm-1. The CL has thirteen auto-peaks at 2958, 2921, 1649, 1563, 1450, 1218, 1192, 1161, 1140, 1110, 1082, 1065 and 1047 cm-1, in which the four strongest auto-peaks are at 2921, 1563, 1192 and 1082 cm-1. The WL shows fifteen auto-peaks at 2960, 2937, 2921, 1650, 1615, 1555, 1458, 1219, 1190, 1138, 1111, 1084, 1068, 1048 and 1033 cm-1, in which the four strongest auto-peaks are at 2921, 1650, 1190 and 1068 cm-1. This study shows the potential of FT-IR spectroscopy and 2D correlation analysis in a simple and quick distinction of wild-growing and cultivated mushrooms.

29 CFR 1604.4 - Discrimination against married women.

Code of Federal Regulations, 2014 CFR

2014-07-01

... DISCRIMINATION BECAUSE OF SEX § 1604.4 Discrimination against married women. (a) The Commission has determined... applicable to married men is a discrimination based on sex prohibited by title VII of the Civil Rights Act... married females, for so long as sex is a factor in the application of the rule, such application involves...

[Application of Fourier transform infrared spectroscopy in identification of wine spoilage].

PubMed

Zhao, Xian-De; Dong, Da-Ming; Zheng, Wen-Gang; Jiao, Lei-Zi; Lang, Yun

2014-10-01

In the present work, fresh and spoiled wine samples from three wines produced by different companies were studied u- sing Fourier transform infrared (FTIR) spectroscopy. We analyzed the physicochemical property change in the process of spoil- age, and then, gave out the attribution of some main FTIR absorption peaks. A novel determination method was explored based on the comparisons of some absorbance ratios at different wavebands although the absorbance ratios in this method were relative. Through the compare of the wine spectra before and after spoiled, the authors found that they were informative at the bands of 3,020~2,790, 1,760~1,620 and 1,550~800 cm(-1). In order to find the relation between these informative spectral bands and the wine deterioration and achieve the discriminant analysis, chemometrics methods were introduced. Principal compounds analysis (PCA) and soft independent modeling of class analogy (SIMCA) were used for classifying different-quality wines. And partial least squares discriminant analysis (PLS-DA) was applied to identify spoiled wines and good wines. Results showed that FTIR technique combined with chemometrics methods could effectively distinguish spoiled wines from fresh samples. The effect of classification at the wave band of 1 550-800 cm(-1) was the best. The recognition rate of SIMCA and PLSDA were respectively 94% and 100%. This study demonstrates that Fourier transform infrared spectroscopy is an effective tool for monitoring red wine's spoilage and provides theoretical support for developing early-warning equipments.

Photoacoustic spectroscopy based investigatory approach to discriminate breast cancer from normal: a pilot study

NASA Astrophysics Data System (ADS)

Priya, Mallika; Rao, Bola Sadashiva Satish; Chandra, Subhash; Ray, Satadru; Mathew, Stanley; Datta, Anirbit; Nayak, Subramanya G.; Mahato, Krishna Kishore

2016-02-01

In spite of many efforts for early detection of breast cancer, there is still lack of technology for immediate implementation. In the present study, the potential photoacoustic spectroscopy was evaluated in discriminating breast cancer from normal, involving blood serum samples seeking early detection. Three photoacoustic spectra in time domain were recorded from each of 20 normal and 20 malignant samples at 281nm pulsed laser excitations and a total of 120 spectra were generated. The time domain spectra were then Fast Fourier Transformed into frequency domain and 116.5625 - 206.875 kHz region was selected for further analysis using a combinational approach of wavelet, PCA and logistic regression. Initially, wavelet analysis was performed on the FFT data and seven features (mean, median, area under the curve, variance, standard deviation, skewness and kurtosis) from each were extracted. PCA was then performed on the feature matrix (7x120) for discriminating malignant samples from the normal by plotting a decision boundary using logistic regression analysis. The unsupervised mode of classification used in the present study yielded specificity and sensitivity values of 100% in each respectively with a ROC - AUC value of 1. The results obtained have clearly demonstrated the capability of photoacoustic spectroscopy in discriminating cancer from the normal, suggesting its possible clinical implications.

A Novel Spectroscopically Determined Pharmacodynamic Biomarker for Skin Toxicity in Cancer Patients Treated with Targeted Agents.

PubMed

Azan, Antoine; Caspers, Peter J; Bakker Schut, Tom C; Roy, Séverine; Boutros, Céline; Mateus, Christine; Routier, Emilie; Besse, Benjamin; Planchard, David; Seck, Atmane; Kamsu Kom, Nyam; Tomasic, Gorana; Koljenović, Senada; Noordhoek Hegt, Vincent; Texier, Matthieu; Lanoy, Emilie; Eggermont, Alexander M M; Paci, Angelo; Robert, Caroline; Puppels, Gerwin J; Mir, Lluis M

2017-01-15

Raman spectroscopy is a noninvasive and label-free optical technique that provides detailed information about the molecular composition of a sample. In this study, we evaluated the potential of Raman spectroscopy to predict skin toxicity due to tyrosine kinase inhibitors treatment. We acquired Raman spectra of skin of patients undergoing treatment with MEK, EGFR, or BRAF inhibitors, which are known to induce severe skin toxicity; for this pilot study, three patients were included for each inhibitor. Our algorithm, based on partial least squares-discriminant analysis (PLS-DA) and cross-validation by bootstrapping, discriminated to variable degrees spectra from patient suffering and not suffering cutaneous adverse events. For MEK and EGFR inhibitors, discriminative power was more than 90% in the viable epidermis skin layer; whereas for BRAF inhibitors, discriminative power was 71%. There was a 81.5% correlation between blood drug concentration and Raman signature of skin in the case of EGFR inhibitors and viable epidermis skin layer. Our results demonstrate the power of Raman spectroscopy to detect apparition of skin toxicity in patients treated with tyrosine kinase inhibitors at levels not detectable via dermatological inspection and histological evaluation. Cancer Res; 77(2); 557-65. ©2016 AACR. ©2016 American Association for Cancer Research.

Application of the laguerre deconvolution method for time-resolved fluorescence spectroscopy to the characterization of atherosclerotic plaques.

PubMed

Jo, J A; Fang, Q; Papaioannou, T; Qiao, J H; Fishbein, M C; Beseth, B; Dorafshar, A H; Reil, T; Baker, D; Freischlag, J; Marcu, L

2005-01-01

This study investigates the ability of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) to detect inflammation in atherosclerotic lesion, a key feature of plaque vulnerability. A total of 348 TR-LIFS measurements were taken from carotid plaques of 30 patients, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified as Early, Fibrotic/Calcified or Inflamed lesions. A stepwise linear discriminant analysis algorithm was developed using spectral and TR features (normalized intensity values and Laguerre expansion coefficients at discrete emission wavelengths, respectively). Features from only three emission wavelengths (390, 450 and 500 nm) were used in the classifier. The Inflamed lesions were discriminated with sensitivity > 80% and specificity > 90 %, when the Laguerre expansion coefficients were included in the feature space. These results indicate that TR-LIFS information derived from the Laguerre expansion coefficients at few selected emission wavelengths can discriminate inflammation in atherosclerotic plaques. We believe that TR-LIFS derived Laguerre expansion coefficients can provide a valuable additional dimension for the detection of vulnerable plaques.

Non-invasive characterization of colorants by portable diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Manfredi, Marcello; Barberis, Elettra; Aceto, Maurizio; Marengo, Emilio

2017-06-01

During the last years the need for non-invasive and non-destructive analytical methods brought to the development and application of new instrumentation and analytical methods for the in-situ analysis of cultural heritage objects. In this work we present the application of a portable diffuse reflectance infrared Fourier transform (DRIFT) method for the non-invasive characterization of colorants prepared according to ancient recipes and using egg white and Gum Arabic as binders. Approximately 50 colorants were analyzed with the DRIFT spectroscopy: we were able to identify and discriminate the most used yellow (i.e. yellow ochres, Lead-tin Yellow, Orpiment, etc.), red (i.e. red ochres, Hematite) and blue (i.e. Lapis Lazuli, Azurite, indigo) colorants, creating a complete DRIFT spectral library. The Principal Component Analysis-Discriminant Analysis (PCA-DA) was then employed for the colorants classification according to the chemical/mineralogical composition. The DRIFT analysis was also performed on a gouache painting of the artist Sutherland; and the colorants used by the painter were identified directly in-situ and in a non-invasive manner.

The multifunctional application of microfluidic lab-on-a-chip surface enhanced Raman spectroscopy (LOC-SERS) within the field of bioanalytics

NASA Astrophysics Data System (ADS)

März, Anne; Mönch, Bettina; Walter, Angela; Bocklitz, Thomas; Schumacher, Wilm; Rösch, Petra; Kiehntopf, Michael; Popp, Jürgen

2011-07-01

This contribution will present a variety of applications of lab-on-a-chip surface enhanced Raman spectroscopy in the field of bioanalytic. Beside the quantification and online monitoring of drugs and pharmaceuticals, determination of enzyme activity and discrimination of bacteria are successfully carried out utilizing LOC-SERS. The online-monitoring of drugs using SERS in a microfluidic device is demonstrated for nicotine. The enzyme activity of thiopurine methyltransferase (TPMT) in lysed red blood cells is determined by SERS in a lab-on-a-chip device. To analyse the activity of TPMT the metabolism of 6-mercaptopurine to 6-methylmercaptopurine is investigated. The discrimination of bacteria on strain level is carried out with different E. coli strains. For the investigations, the bacteria are busted by ultra sonic to achieve a high information output. This sample preparation provides the possibility to detect SERS spectra containing information of the bacterial cell walls as well as of the cytoplasm. This contribution demonstrates the great potential of LOC-SERS in the field of bioanalytics.

Biophotonics in diagnosis and modeling of tissue pathologies

NASA Astrophysics Data System (ADS)

Serafetinides, A. A.; Makropoulou, M.; Drakaki, E.

2008-12-01

Biophotonics techniques are applied to several fields in medicine and biology. The laser based techniques, such as the laser induced fluorescence (LIF) spectroscopy and the optical coherence tomography (OCT), are of particular importance in dermatology, where the laser radiation could be directly applied to the tissue target (e.g. skin). In addition, OCT resolves architectural tissue properties that might be useful as tumour discrimination parameters for skin as well as for ocular non-invasive visualization. Skin and ocular tissues are complex multilayered and inhomogeneous organs with spatially varying optical properties. This fact complicates the quantitative analysis of the fluorescence and/or light scattering spectra, even from the same tissue sample. To overcome this problem, mathematical simulation is applied for the investigation of the human tissue optical properties, in the visible/infrared range of the spectrum, resulting in a better discrimination of several tissue pathologies. In this work, we present i) a general view on biophotonics applications in diagnosis of human diseases, ii) some specific results on laser spectroscopy techniques, as LIF measurements, applied in arterial and skin pathologies and iii) some experimental and theoretical results on ocular OCT measurements. Regarding the LIF spectroscopy, we examined the autofluorescence properties of several human skin samples, excised from humans undergoing biopsy examination. A nitrogen laser was used as an excitation source, emitting at 337 nm (ultraviolet excitation). Histopathology examination of the samples was also performed, after the laser spectroscopy measurements and the results from the spectroscopic and medical analysis were compared, to differentiate malignancies, e.g. basal cell carcinoma tissue (BCC), from normal skin tissue. Regarding the OCT technique, we correlated human data, obtained from patients undergoing OCT examination, with Monte Carlo simulated cornea and retina tissues for diagnosis of ocular diseases.

Photoacoustic spectroscopy for chemical detection

NASA Astrophysics Data System (ADS)

Holthoff, Ellen L.; Pellegrino, Paul M.

2012-06-01

The Global War on Terror has made rapid detection and identification of chemical and biological agents a priority for Military and Homeland Defense applications. Reliable real-time detection of these threats is complicated by our enemy's use of a diverse range of materials. Therefore, an adaptable platform is necessary. Photoacoustic spectroscopy (PAS) is a useful monitoring technique that is well suited for trace detection of gaseous media. This method routinely exhibits detection limits at the parts-per-billion (ppb) or sub-ppb range. The versatility of PAS also allows for the investigation of solid and liquid analytes. Current research utilizes quantum cascade lasers (QCLs) in combination with an air-coupled solid-phase photoacoustic cell design for the detection of condensed phase material films deposited on a surface. Furthermore, variation of the QCL pulse repetition rate allows for identification and molecular discrimination of analytes based solely on photoacoustic spectra collected at different film depths.

Microorganisms detection on substrates using QCL spectroscopy

NASA Astrophysics Data System (ADS)

Padilla-Jiménez, Amira C.; Ortiz-Rivera, William; Castro-Suarez, John R.; Ríos-Velázquez, Carlos; Vázquez-Ayala, Iris; Hernández-Rivera, Samuel P.

2013-05-01

Recent investigations have focused on the improvement of rapid and accurate methods to develop spectroscopic markers of compounds constituting microorganisms that are considered biological threats. Quantum cascade lasers (QCL) systems have revolutionized many areas of research and development in defense and security applications, including his area of research. Infrared spectroscopy detection based on QCL was employed to acquire mid infrared (MIR) spectral signatures of Bacillus thuringiensis (Bt), Escherichia coli (Ec) and Staphylococcus epidermidis (Se), which were used as biological agent simulants of biothreats. The experiments were carried out in reflection mode on various substrates such as cardboard, glass, travel baggage, wood and stainless steel. Chemometrics statistical routines such as principal component analysis (PCA) regression and partial least squares-discriminant analysis (PLS-DA) were applied to the recorded MIR spectra. The results show that the infrared vibrational techniques investigated are useful for classification/detection of the target microorganisms on the types of substrates studied.

Optical diagnosis of cervical cancer by intrinsic mode functions

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sabyasachi; Pratiher, Sawon; Pratiher, Souvik; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2017-03-01

In this paper, we make use of the empirical mode decomposition (EMD) to discriminate the cervical cancer tissues from normal ones based on elastic scattering spectroscopy. The phase space has been reconstructed through decomposing the optical signal into a finite set of bandlimited signals known as intrinsic mode functions (IMFs). It has been shown that the area measure of the analytic IMFs provides a good discrimination performance. Simulation results validate the efficacy of the IMFs followed by SVM based classification.

Detection of sunn pest-damaged wheat samples using visible/near-infrared spectroscopy based on pattern recognition.

PubMed

Basati, Zahra; Jamshidi, Bahareh; Rasekh, Mansour; Abbaspour-Gilandeh, Yousef

2018-05-30

The presence of sunn pest-damaged grains in wheat mass reduces the quality of flour and bread produced from it. Therefore, it is essential to assess the quality of the samples in collecting and storage centers of wheat and flour mills. In this research, the capability of visible/near-infrared (Vis/NIR) spectroscopy combined with pattern recognition methods was investigated for discrimination of wheat samples with different percentages of sunn pest-damaged. To this end, various samples belonging to five classes (healthy and 5%, 10%, 15% and 20% unhealthy) were analyzed using Vis/NIR spectroscopy (wavelength range of 350-1000 nm) based on both supervised and unsupervised pattern recognition methods. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) as the unsupervised techniques and soft independent modeling of class analogies (SIMCA) and partial least squares-discriminant analysis (PLS-DA) as supervised methods were used. The results showed that Vis/NIR spectra of healthy samples were correctly clustered using both PCA and HCA. Due to the high overlapping between the four unhealthy classes (5%, 10%, 15% and 20%), it was not possible to discriminate all the unhealthy samples in individual classes. However, when considering only the two main categories of healthy and unhealthy, an acceptable degree of separation between the classes can be obtained after classification with supervised pattern recognition methods of SIMCA and PLS-DA. SIMCA based on PCA modeling correctly classified samples in two classes of healthy and unhealthy with classification accuracy of 100%. Moreover, the power of the wavelengths of 839 nm, 918 nm and 995 nm were more than other wavelengths to discriminate two classes of healthy and unhealthy. It was also concluded that PLS-DA provides excellent classification results of healthy and unhealthy samples (R 2  = 0.973 and RMSECV = 0.057). Therefore, Vis/NIR spectroscopy based on pattern recognition techniques can be useful for rapid distinguishing the healthy wheat samples from those damaged by sunn pest in the maintenance and processing centers. Copyright © 2018 Elsevier B.V. All rights reserved.

Application of metabonomic strategy to discover an unreported active ingredient in LiuWeiDiHuang pills suppressing beta-glucuronidase.

PubMed

Xie, Baogang; Zhang, Zhirong; Gong, Tao; Zhang, Ningning; Wang, Huiyun; Zou, Huiqing

2015-01-01

Identification of the bioactive ingredient from traditional Chinese medicine (TCM) remains a challenging task by traditional approach that focuses on chemical isolation coupled with biological activity screening. Here, we present a metabonomics-based approach for bioactive ingredient discovery in LiuWeiDiHuang pills (LWPs). First, a non-targeted high-performance liquid chromatography ultraviolet (HPLC-UV) profiling of rat urine was used to discriminate urinary profiling intervened by LWPs. Orthogonal partial least-squares discriminant analysis (OPLS-DA) revealed that eight chromatographic peaks made a significant contribution to the classification of the LWPs group and the control group. Five of these chromatographic peaks were successfully isolated and identified as hippurate, genistein (GT), daidzein (DZ), and glucuronide conjugate of GT and that of DZ by mass spectroscopy (MS). Subsequently, we found that LWPs significantly decreased the activity of intestinal β-glucuronidase by 18 % and exerted a dose-dependent inhibitory effect on rat liver lysosomal fraction, suggesting that LWPs were a β-glucuronidase inhibitor. In the end, by inhibiting β-glucuronidase-guided isolation, D-glucaro-1,4-lactone, a previously unreported ingredient of LWPs, was identified by MS, MS/MS, and nuclear magnetic resonance spectroscopy. Our findings indicated that metabonomics might increase research productivity toward the drug targets and/or bioactive compounds from TCM.

Evaluation of elemental profiling methods, including laser-induced breakdown spectroscopy (LIBS), for the differentiation of Cannabis plant material grown in different nutrient solutions.

PubMed

El-Deftar, Moteaa M; Robertson, James; Foster, Simon; Lennard, Chris

2015-06-01

Laser-induced breakdown spectroscopy (LIBS) is an emerging atomic emission based solid sampling technique that has many potential forensic applications. In this study, the analytical performance of LIBS, as well as that of inductively coupled plasma mass spectrometry (ICP-MS), laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and X-ray microfluorescence (μXRF), was evaluated for the ability to conduct elemental analyses on Cannabis plant material, with a specific investigation of the possible links between hydroponic nutrients and elemental profiles from associated plant material. No such study has been previously published in the literature. Good correlation among the four techniques was observed when the concentrations or peak areas of the elements of interest were monitored. For Cannabis samples collected at the same growth time, the elemental profiles could be related to the use of particular commercial nutrients. In addition, the study demonstrated that ICP-MS, LA-ICP-MS and LIBS are suitable techniques for the comparison of Cannabis samples from different sources, with high discriminating powers being achieved. On the other hand, μXRF method was not suitable for the discrimination of Cannabis samples originating from different growth nutrients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Resonant Absorption in GaAs-Based Nanowires by Means of Photo-Acoustic Spectroscopy

NASA Astrophysics Data System (ADS)

Petronijevic, E.; Leahu, G.; Belardini, A.; Centini, M.; Li Voti, R.; Hakkarainen, T.; Koivusalo, E.; Guina, M.; Sibilia, C.

2018-03-01

Semiconductor nanowires made of high refractive index materials can couple the incoming light to specific waveguide modes that offer resonant absorption enhancement under the bandgap wavelength, essential for light harvesting, lasing and detection applications. Moreover, the non-trivial ellipticity of such modes can offer near field interactions with chiral molecules, governed by near chiral field. These modes are therefore very important to detect. Here, we present the photo-acoustic spectroscopy as a low-cost, reliable, sensitive and scattering-free tool to measure the spectral position and absorption efficiency of these modes. The investigated samples are hexagonal nanowires with GaAs core; the fabrication by means of lithography-free molecular beam epitaxy provides controllable and uniform dimensions that allow for the excitation of the fundamental resonant mode around 800 nm. We show that the modulation frequency increase leads to the discrimination of the resonant mode absorption from the overall absorption of the substrate. As the experimental data are in great agreement with numerical simulations, the design can be optimized and followed by photo-acoustic characterization for a specific application.

Discrimination of selected species of pathogenic bacteria using near-infrared Raman spectroscopy and principal components analysis

NASA Astrophysics Data System (ADS)

de Siqueira e Oliveira, Fernanda S.; Giana, Hector E.; Silveira, Landulfo, Jr.

2012-03-01

It has been proposed a method based on Raman spectroscopy for identification of different microorganisms involved in bacterial urinary tract infections. Spectra were collected from different bacterial colonies (Gram negative: E. coli, K. pneumoniae, P. mirabilis, P. aeruginosa, E. cloacae and Gram positive: S. aureus and Enterococcus sp.), grown in culture medium (Agar), using a Raman spectrometer with a fiber Raman probe (830 nm). Colonies were scraped from Agar surface placed in an aluminum foil for Raman measurements. After pre-processing, spectra were submitted to a Principal Component Analysis and Mahalanobis distance (PCA/MD) discrimination algorithm. It has been found that the mean Raman spectra of different bacterial species show similar bands, being the S. aureus well characterized by strong bands related to carotenoids. PCA/MD could discriminate Gram positive bacteria with sensitivity and specificity of 100% and Gram negative bacteria with good sensitivity and high specificity.

Toward improving fine needle aspiration cytology by applying Raman microspectroscopy

NASA Astrophysics Data System (ADS)

Becker-Putsche, Melanie; Bocklitz, Thomas; Clement, Joachim; Rösch, Petra; Popp, Jürgen

2013-04-01

Medical diagnosis of biopsies performed by fine needle aspiration has to be very reliable. Therefore, pathologists/cytologists need additional biochemical information on single cancer cells for an accurate diagnosis. Accordingly, we applied three different classification models for discriminating various features of six breast cancer cell lines by analyzing Raman microspectroscopic data. The statistical evaluations are implemented by linear discriminant analysis (LDA) and support vector machines (SVM). For the first model, a total of 61,580 Raman spectra from 110 single cells are discriminated at the cell-line level with an accuracy of 99.52% using an SVM. The LDA classification based on Raman data achieved an accuracy of 94.04% by discriminating cell lines by their origin (solid tumor versus pleural effusion). In the third model, Raman cell spectra are classified by their cancer subtypes. LDA results show an accuracy of 97.45% and specificities of 97.78%, 99.11%, and 98.97% for the subtypes basal-like, HER2+/ER-, and luminal, respectively. These subtypes are confirmed by gene expression patterns, which are important prognostic features in diagnosis. This work shows the applicability of Raman spectroscopy and statistical data handling in analyzing cancer-relevant biochemical information for advanced medical diagnosis on the single-cell level.

Novel methods of time-resolved fluorescence data analysis for in-vivo tissue characterization: application to atherosclerosis.

PubMed

Jo, J A; Fang, Q; Papaioannou, T; Qiao, J H; Fishbein, M C; Dorafshar, A; Reil, T; Baker, D; Freischlag, J; Marcu, L

2004-01-01

This study investigates the ability of new analytical methods of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data to characterize tissue in-vivo, such as the composition of atherosclerotic vulnerable plaques. A total of 73 TR-LIFS measurements were taken in-vivo from the aorta of 8 rabbits, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified as normal aorta, thin or thick lesions, and lesions rich in either collagen or macrophages/foam-cells. Different linear and nonlinear classification algorithms (linear discriminant analysis, stepwise linear discriminant analysis, principal component analysis, and feedforward neural networks) were developed using spectral and TR features (ratios of intensity values and Laguerre expansion coefficients, respectively). Normal intima and thin lesions were discriminated from thick lesions (sensitivity >90%, specificity 100%) using only spectral features. However, both spectral and time-resolved features were necessary to discriminate thick lesions rich in collagen from thick lesions rich in foam cells (sensitivity >85%, specificity >93%), and thin lesions rich in foam cells from normal aorta and thin lesions rich in collagen (sensitivity >85%, specificity >94%). Based on these findings, we believe that TR-LIFS information derived from the Laguerre expansion coefficients can provide a valuable additional dimension for in-vivo tissue characterization.

Accurate classification of brain gliomas by discriminate dictionary learning based on projective dictionary pair learning of proton magnetic resonance spectra.

PubMed

Adebileje, Sikiru Afolabi; Ghasemi, Keyvan; Aiyelabegan, Hammed Tanimowo; Saligheh Rad, Hamidreza

2017-04-01

Proton magnetic resonance spectroscopy is a powerful noninvasive technique that complements the structural images of cMRI, which aids biomedical and clinical researches, by identifying and visualizing the compositions of various metabolites within the tissues of interest. However, accurate classification of proton magnetic resonance spectroscopy is still a challenging issue in clinics due to low signal-to-noise ratio, overlapping peaks of metabolites, and the presence of background macromolecules. This paper evaluates the performance of a discriminate dictionary learning classifiers based on projective dictionary pair learning method for brain gliomas proton magnetic resonance spectroscopy spectra classification task, and the result were compared with the sub-dictionary learning methods. The proton magnetic resonance spectroscopy data contain a total of 150 spectra (74 healthy, 23 grade II, 23 grade III, and 30 grade IV) from two databases. The datasets from both databases were first coupled together, followed by column normalization. The Kennard-Stone algorithm was used to split the datasets into its training and test sets. Performance comparison based on the overall accuracy, sensitivity, specificity, and precision was conducted. Based on the overall accuracy of our classification scheme, the dictionary pair learning method was found to outperform the sub-dictionary learning methods 97.78% compared with 68.89%, respectively. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Application of FTIR Spectroscopy for Assessment of Green Coffee Beans According to Their Origin

NASA Astrophysics Data System (ADS)

Obeidat, S. M.; Hammoudeh, A. Y.; Alomary, A. A.

2018-01-01

Samples of green coffee beans originating from five different countries were ground and analyzed using FTIR spectra in the region of 600-4000 cm-1. Successful discrimination of each coffee type based on their origin was achieved applying a PCA algorithm on the obtained IR spectra for all samples. PCA loading plots show that the IR bands at 2850, 2920, and 1745 cm-1 corresponding to the symmetric, and antisymmetric vibrations of CH2 and the stretching vibration of C=O bond in ester, respectively, are the most significant peaks in distinguishing the origin of the above coffee samples.

A novel combined approach of diffuse reflectance UV-Vis-NIR spectroscopy and multivariate analysis for non-destructive examination of blue ballpoint pen inks in forensic application

NASA Astrophysics Data System (ADS)

Kumar, Raj; Sharma, Vishal

2017-03-01

The present research is focused on the analysis of writing inks using destructive UV-Vis spectroscopy (dissolution of ink by the solvent) and non-destructive diffuse reflectance UV-Vis-NIR spectroscopy along with Chemometrics. Fifty seven samples of blue ballpoint pen inks were analyzed under optimum conditions to determine the differences in spectral features of inks among same and different manufacturers. Normalization was performed on the spectroscopic data before chemometric analysis. Principal Component Analysis (PCA) and K-mean cluster analysis were used on the data to ascertain whether the blue ballpoint pen inks could be differentiated by their UV-Vis/UV-Vis NIR spectra. The discriminating power is calculated by qualitative analysis by the visual comparison of the spectra (absorbance peaks), produced by the destructive and non-destructive methods. In the latter two methods, the pairwise comparison is made by incorporating the clustering method. It is found that chemometric method provides better discriminating power (98.72% and 99.46%, in destructive and non-destructive, respectively) in comparison to the qualitative analysis (69.67%).

Detection of Lipitor counterfeits: a comparison of NIR and Raman spectroscopy in combination with chemometrics.

PubMed

de Peinder, P; Vredenbregt, M J; Visser, T; de Kaste, D

2008-08-05

Research has been carried on the feasibility of near infrared (NIR) and Raman spectroscopy as rapid screening methods to discriminate between genuine and counterfeits of the cholesterol-lowering medicine Lipitor. Classification, based on partial least squares discriminant analysis (PLS-DA) models, appears to be successful for both spectroscopic techniques, irrespective of whether atorvastatine or lovastatine has been used as the active pharmaceutical ingredient (API). The discriminative power of the NIR model, in particular, largely relies on the spectral differences of the tablet matrix. This is due to the relative large sample volume that is probed with NIR and the strong spectroscopic activity of the excipients. PLS-DA models based on NIR or Raman spectra can also be applied to distinguish between atorvastatine and lovastatine as the API used in the counterfeits tested in this study. A disadvantage of Raman microscopy for this type of analysis is that it is primarily a surface technique. As a consequence spectra of the coating and the tablet core might differ. Besides, spectra may change with the position of the laser in case the sample is inhomogeneous. However, the robustness of the PLS-DA models turned out to be sufficiently large to allow a reliable discrimination. Principal component analysis (PCA) of the spectra revealed that the conditions, at which tablets have been stored, affect the NIR data. This effect is attributed to the adsorption of water from the atmosphere after unpacking from the blister. It implies that storage conditions should be taken into account when the NIR technique is used for discriminating purposes. However, in this study both models based on NIR spectra and Raman data enabled reliable discrimination between genuine and counterfeited Lipitor tablets, regardless of their storage conditions.

Proof of Principle for a Real-Time Pathogen Isolation Media Diagnostic: The Use of Laser-Induced Breakdown Spectroscopy to Discriminate Bacterial Pathogens and Antimicrobial-Resistant Staphylococcus aureus Strains Grown on Blood Agar

PubMed Central

Multari, Rosalie A.; Cremers, David A.; Bostian, Melissa L.; Dupre, Joanne M.

2013-01-01

Laser-Induced Breakdown Spectroscopy (LIBS) is a rapid, in situ, diagnostic technique in which light emissions from a laser plasma formed on the sample are used for analysis allowing automated analysis results to be available in seconds to minutes. This speed of analysis coupled with little or no sample preparation makes LIBS an attractive detection tool. In this study, it is demonstrated that LIBS can be utilized to discriminate both the bacterial species and strains of bacterial colonies grown on blood agar. A discrimination algorithm was created based on multivariate regression analysis of spectral data. The algorithm was deployed on a simulated LIBS instrument system to demonstrate discrimination capability using 6 species. Genetically altered Staphylococcus aureus strains grown on BA, including isogenic sets that differed only by the acquisition of mutations that increase fusidic acid or vancomycin resistance, were also discriminated. The algorithm successfully identified all thirteen cultures used in this study in a time period of 2 minutes. This work provides proof of principle for a LIBS instrumentation system that could be developed for the rapid discrimination of bacterial species and strains demonstrating relatively minor genomic alterations using data collected directly from pathogen isolation media. PMID:24109513

Assay based on electrical impedance spectroscopy to discriminate between normal and cancerous mammalian cells

NASA Astrophysics Data System (ADS)

Giana, Fabián Eduardo; Bonetto, Fabián José; Bellotti, Mariela Inés

2018-03-01

In this work we present an assay to discriminate between normal and cancerous cells. The method is based on the measurement of electrical impedance spectra of in vitro cell cultures. We developed a protocol consisting on four consecutive measurement phases, each of them designed to obtain different information about the cell cultures. Through the analysis of the measured data, 26 characteristic features were obtained for both cell types. From the complete set of features, we selected the most relevant in terms of their discriminant capacity by means of conventional statistical tests. A linear discriminant analysis was then carried out on the selected features, allowing the classification of the samples in normal or cancerous with 4.5% of false positives and no false negatives.

Assay based on electrical impedance spectroscopy to discriminate between normal and cancerous mammalian cells.

PubMed

Giana, Fabián Eduardo; Bonetto, Fabián José; Bellotti, Mariela Inés

2018-03-01

In this work we present an assay to discriminate between normal and cancerous cells. The method is based on the measurement of electrical impedance spectra of in vitro cell cultures. We developed a protocol consisting on four consecutive measurement phases, each of them designed to obtain different information about the cell cultures. Through the analysis of the measured data, 26 characteristic features were obtained for both cell types. From the complete set of features, we selected the most relevant in terms of their discriminant capacity by means of conventional statistical tests. A linear discriminant analysis was then carried out on the selected features, allowing the classification of the samples in normal or cancerous with 4.5% of false positives and no false negatives.

Application of multispectral reflectance for early detection of tomato disease

NASA Astrophysics Data System (ADS)

Xu, Huirong; Zhu, Shengpan; Ying, Yibin; Jiang, Huanyu

2006-10-01

Automatic diagnosis of plant disease is important for plant management and environmental preservation in the future. The objective of this study is to use multispectral reflectance measurements to make an early discrimination between the healthy and infected plants by the strain of tobacco mosaic virus (TMV-U1) infection. There were reflectance changes in the visible (VIS) and near infrared spectroscopy (NIR) between the healthy and infected plants. Discriminant models were developed using discriminant partial least squares (DPLS) and Mahalanobis distance (MD). The DPLS models had a root mean square error of calibration (RMSEC) of 0.397 and correlation coefficient (r) of 0.59 and the MD model correctly classified 86.7% healthy plants and up to 91.7% infected plants.

Discrimination of Fritillary according to geographical origin with Fourier transform infrared spectroscopy and two-dimensional correlation IR spectroscopy.

PubMed

Hua, Rui; Sun, Su-Qin; Zhou, Qun; Noda, Isao; Wang, Bao-Qin

2003-09-19

Fritillaria is a traditional Chinese herbal medicine for eliminating phlegm and relieving a cough with a long history in China and some other Asian countries. The objective of this study is to develop a nondestructive and accurate method to discriminate Fritillaria of different geographical origins, which is a troublesome work by existing analytical methods. We conducted a systematic study on five kinds of Fritillaria by Fourier transform infrared spectroscopy, second derivative infrared spectroscopy, and two-dimensional (2D) correlation infrared spectroscopy under thermal perturbation. Because Fritillaria consist of a large amount of starch, the conventional IR spectra of different Fritillaria only have very limited spectral feature differences. Based on these differences, we can separate different Fritillaria to a limited extent, but this method was deemed not very practical. The second derivative IR spectra of Fritillaria could enhance spectrum resolution, amplify the differences between the IR spectra of different Fritillaria, and provide some dissimilarity in their starch content, when compared with the spectrum of pure starch. Finally, we applied thermal perturbation to Fritillaria and analyzed the resulting spectra by the 2D correlation method to distinguish different Fritillaria easily and clearly. The distinction of very similar Fritillaria was possible because the spectral resolution was greatly enhanced by the 2D correlation spectroscopy. In addition, with the dynamic information of molecular structure provided by 2D correlation IR spectra, we studied the differences in the stability of active components of Fritillaria. The differences embodied mainly on the intensity ratio of the auto-peak at 985 cm(-1) and other auto-peaks. The 2D correlation IR spectroscopy (2D IR) of Fritillaria can be a new and powerful method to discriminate Fritillaria.

Visible spectroscopy as a tool for the assessment of storage conditions of fresh pork packaged in modified atmosphere.

PubMed

Spanos, Dimitrios; Christensen, Mette; Tørngren, Mari Ann; Baron, Caroline P

2016-03-01

The storage conditions of fresh meat are known to impact its colour and microbial shelf life. In the present study, visible spectroscopy was evaluated as a method to assess meat storage conditions and its optimisation. Fresh pork steaks (longissimus thoracis et lumborum and semimembranosus) were placed in modified atmosphere packaging using gas mixtures containing 0, 40, 50, and 80% oxygen, and stored with or without light for up to 9days. Principal component analysis of visible reflectance spectra (400-700nm) showed that the colour of the different meat cuts was affected by presence of oxygen, illumination, and storage time. Differences in the oxygen levels did not contribute to the observed variance. Predictive models based on partial least squares regression-discriminant analysis exhibited high potency in the classification of the storage parameters of meat cuts packaged in modified atmosphere. The study demonstrates the applicability of visible spectroscopy as a tool to assess the storage conditions of meat cuts packaged in modified atmosphere. Copyright © 2015 Elsevier Ltd. All rights reserved.

Detection of Anomalies in Citrus Leaves Using Laser-Induced Breakdown Spectroscopy (LIBS).

PubMed

Sankaran, Sindhuja; Ehsani, Reza; Morgan, Kelly T

2015-08-01

Nutrient assessment and management are important to maintain productivity in citrus orchards. In this study, laser-induced breakdown spectroscopy (LIBS) was applied for rapid and real-time detection of citrus anomalies. Laser-induced breakdown spectroscopy spectra were collected from citrus leaves with anomalies such as diseases (Huanglongbing, citrus canker) and nutrient deficiencies (iron, manganese, magnesium, zinc), and compared with those of healthy leaves. Baseline correction, wavelet multivariate denoising, and normalization techniques were applied to the LIBS spectra before analysis. After spectral pre-processing, features were extracted using principal component analysis and classified using two models, quadratic discriminant analysis and support vector machine (SVM). The SVM resulted in a high average classification accuracy of 97.5%, with high average canker classification accuracy (96.5%). LIBS peak analysis indicated that high intensities at 229.7, 247.9, 280.3, 393.5, 397.0, and 769.8 nm were observed of 11 peaks found in all the samples. Future studies using controlled experiments with variable nutrient applications are required for quantification of foliar nutrients by using LIBS-based sensing.

Dual modal endoscopic cancer detection based on optical pH sensing and Raman spectroscopy

NASA Astrophysics Data System (ADS)

Kim, Soogeun; Kim, ByungHyun; Sohn, Won Bum; Byun, Kyung Min; Lee, Soo Yeol

2017-02-01

To discriminate between normal and cancerous tissue, a dual modal approach using Raman spectroscopy and pH sensor was designed and applied. Raman spectroscopy has demonstrated the possibility of using as diagnostic method for the early detection of precancerous and cancerous lesions in vivo. It also can be used in identifying markers associated with malignant change. However, Raman spectroscopy lacks sufficient sensitivity due to very weak Raman scattering signal or less distinctive spectral pattern. A dual modal approach could be one of the solutions to solve this issue. The level of extracellular pH in cancer tissue is lower than that in normal tissue due to increased lactic acid production, decreased interstitial fluid buffering and decreased perfusion. High sensitivity and specificity required for accurate cancer diagnosis could be achieved by combining the chemical information from Raman spectrum with metabolic information from pH level. Raman spectra were acquired by using a fiber optic Raman probe, a cooled CCD camera connected to a spectrograph and 785 nm laser source. Different transmission spectra depending on tissue pH were measured by a lossy-mode resonance sensor based on fiber optic. The discriminative capability of pH-Raman dual modal method was evaluated using principal component analysis (PCA). The obtained results showed that the pH-Raman dual modal approach can improve discriminative capability between normal and cancerous tissue, which can lead to very high sensitivity and specificity. The proposed method for cancer detection is expected to be used in endoscopic diagnosis later.

Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study.

PubMed

Prabitha, Vasumathi Gopala; Suchetha, Sambasivan; Jayanthi, Jayaraj Lalitha; Baiju, Kamalasanan Vijayakumary; Rema, Prabhakaran; Anuraj, Koyippurath; Mathews, Anita; Sebastian, Paul; Subhash, Narayanan

2016-01-01

Diffuse reflectance (DR) spectroscopy is a non-invasive, real-time, and cost-effective tool for early detection of malignant changes in squamous epithelial tissues. The present study aims to evaluate the diagnostic power of diffuse reflectance spectroscopy for non-invasive discrimination of cervical lesions in vivo. A clinical trial was carried out on 48 sites in 34 patients by recording DR spectra using a point-monitoring device with white light illumination. The acquired data were analyzed and classified using multivariate statistical analysis based on principal component analysis (PCA) and linear discriminant analysis (LDA). Diagnostic accuracies were validated using random number generators. The receiver operating characteristic (ROC) curves were plotted for evaluating the discriminating power of the proposed statistical technique. An algorithm was developed and used to classify non-diseased (normal) from diseased sites (abnormal) with a sensitivity of 72 % and specificity of 87 %. While low-grade squamous intraepithelial lesion (LSIL) could be discriminated from normal with a sensitivity of 56 % and specificity of 80 %, and high-grade squamous intraepithelial lesion (HSIL) from normal with a sensitivity of 89 % and specificity of 97 %, LSIL could be discriminated from HSIL with 100 % sensitivity and specificity. The areas under the ROC curves were 0.993 (95 % confidence interval (CI) 0.0 to 1) and 1 (95 % CI 1) for the discrimination of HSIL from normal and HSIL from LSIL, respectively. The results of the study show that DR spectroscopy could be used along with multivariate analytical techniques as a non-invasive technique to monitor cervical disease status in real time.

Using surface-enhanced Raman spectroscopy and electrochemically driven melting to discriminate Yersinia pestis from Y. pseudotuberculosis based on single nucleotide polymorphisms within unpurified polymerase chain reaction amplicons.

PubMed

Papadopoulou, Evanthia; Goodchild, Sarah A; Cleary, David W; Weller, Simon A; Gale, Nittaya; Stubberfield, Michael R; Brown, Tom; Bartlett, Philip N

2015-02-03

The development of sensors for the detection of pathogen-specific DNA, including relevant species/strain level discrimination, is critical in molecular diagnostics with major impacts in areas such as bioterrorism and food safety. Herein, we use electrochemically driven denaturation assays monitored by surface-enhanced Raman spectroscopy (SERS) to target single nucleotide polymorphisms (SNPs) that distinguish DNA amplicons generated from Yersinia pestis, the causative agent of plague, from the closely related species Y. pseudotuberculosis. Two assays targeting SNPs within the groEL and metH genes of these two species have been successfully designed. Polymerase chain reaction (PCR) was used to produce Texas Red labeled single-stranded DNA (ssDNA) amplicons of 262 and 251 bases for the groEL and metH targets, respectively. These amplicons were used in an unpurified form to hybridize to immobilized probes then subjected to electrochemically driven melting. In all cases electrochemically driven melting was able to discriminate between fully homologous DNA and that containing SNPs. The metH assay was particularly challenging due to the presence of only a single base mismatch in the middle of the 251 base long PCR amplicon. However, manipulation of assay conditions (conducting the electrochemical experiments at 10 °C) resulted in greater discrimination between the complementary and mismatched DNA. Replicate data were collected and analyzed for each duplex on different days, using different batches of PCR product and different sphere segment void (SSV) substrates. Despite the variability introduced by these differences, the assays are shown to be reliable and robust providing a new platform for strain discrimination using unpurified PCR samples.

Spatially resolved bimodal spectroscopy for classification/evaluation of mouse skin inflammatory and pre-cancerous stages

NASA Astrophysics Data System (ADS)

Díaz-Ayil, Gilberto; Amouroux, Marine; Clanché, Fabien; Granjon, Yves; Blondel, Walter C. P. M.

2009-07-01

Spatially-resolved bimodal spectroscopy (multiple AutoFluorescence AF excitation and Diffuse Reflectance DR), was used in vivo to discriminate various healthy and precancerous skin stages in a pre-clinical model (UV-irradiated mouse): Compensatory Hyperplasia CH, Atypical Hyperplasia AH and Dysplasia D. A specific data preprocessing scheme was applied to intensity spectra (filtering, spectral correction and intensity normalization), and several sets of spectral characteristics were automatically extracted and selected based on their discrimination power, statistically tested for every pair-wise comparison of histological classes. Data reduction with Principal Components Analysis (PCA) was performed and 3 classification methods were implemented (k-NN, LDA and SVM), in order to compare diagnostic performance of each method. Diagnostic performance was studied and assessed in terms of Sensibility (Se) and Specificity (Sp) as a function of the selected features, of the combinations of 3 different inter-fibres distances and of the numbers of principal components, such that: Se and Sp ~ 100% when discriminating CH vs. others; Sp ~ 100% and Se > 95% when discriminating Healthy vs. AH or D; Sp ~ 74% and Se ~ 63% for AH vs. D.

The discrimination of colored acrylic, cotton, and wool textile fibers using micro-Raman spectroscopy. Part 1: in situ detection and characterization of dyes.

PubMed

Buzzini, Patrick; Massonnet, Genevieve

2013-11-01

Raman spectroscopy has been applied to characterize fiber dyes and determine the discriminating ability of the method. Black, blue, and red acrylic, cotton, and wool samples were analyzed. Four excitation sources were used to obtain complementary responses in the case of fluorescent samples. Fibers that did not provide informative spectra using a given laser were usually detected using another wavelength. For any colored acrylic, the 633-nm laser did not provide Raman information. The 514-nm laser provided the highest discrimination for blue and black cotton, but half of the blue cottons produced noninformative spectra. The 830-nm laser exhibited the highest discrimination for red cotton. Both visible lasers provided the highest discrimination for black and blue wool, and NIR lasers produced remarkable separation for red and black wool. This study shows that the discriminating ability of Raman spectroscopy depends on the fiber type, color, and the laser wavelength. © 2013 American Academy of Forensic Sciences.

Differentiation of different mixed Listeria strains and also acid-injured, heat-injured, and repaired cells of Listeria monocytogenes using fourier transform infrared spectroscopy.

PubMed

Nyarko, Esmond; Donnelly, Catherine

2015-03-01

Fourier transform infrared (FT-IR) spectroscopy was used to differentiate mixed strains of Listeria monocytogenes and mixed strains of L. monocytogenes and Listeria innocua. FT-IR spectroscopy was also applied to investigate the hypothesis that heat-injured and acid-injured cells would return to their original physiological integrity following repair. Thin smears of cells on infrared slides were prepared from cultures for mixed strains of L. monocytogenes, mixed strains of L. monocytogenes and L. innocua, and each individual strain. Heat-injured and acid-injured cells were prepared by exposing harvested cells of L. monocytogenes strain R2-764 to a temperature of 56 ± 0.2°C for 10 min or lactic acid at pH 3 for 60 min, respectively. Cellular repair involved incubating aliquots of acid-injured and heat-injured cells separately in Trypticase soy broth supplemented with 0.6% yeast extract for 22 to 24 h; bacterial thin smears on infrared slides were prepared for each treatment. Spectral collection was done using 250 scans at a resolution of 4 cm(-1) in the mid-infrared wavelength region. Application of multivariate discriminant analysis to the wavelength region from 1,800 to 900 cm(-1) separated the individual L. monocytogenes strains. Mixed strains of L. monocytogenes and L. monocytogenes cocultured with L. innocua were successfully differentiated from the individual strains when the discriminant analysis was applied. Different mixed strains of L. monocytogenes were also successfully separated when the discriminant analysis was applied. A data set for injury and repair analysis resulted in the separation of acid-injured, heat-injured, and intact cells; repaired cells clustered closer to intact cells when the discriminant analysis (1,800 to 600 cm(-1)) was applied. FT-IR spectroscopy can be used for the rapid source tracking of L. monocytogenes strains because it can differentiate between different mixed strains and individual strains of the pathogen.

Rapid and automatic chemical identification of the medicinal flower buds of Lonicera plants by the benchtop and hand-held Fourier transform infrared spectroscopy

NASA Astrophysics Data System (ADS)

Chen, Jianbo; Guo, Baolin; Yan, Rui; Sun, Suqin; Zhou, Qun

2017-07-01

With the utilization of the hand-held equipment, Fourier transform infrared (FT-IR) spectroscopy is a promising analytical technique to minimize the time cost for the chemical identification of herbal materials. This research examines the feasibility of the hand-held FT-IR spectrometer for the on-site testing of herbal materials, using Lonicerae Japonicae Flos (LJF) and Lonicerae Flos (LF) as examples. Correlation-based linear discriminant models for LJF and LF are established based on the benchtop and hand-held FT-IR instruments. The benchtop FT-IR models can exactly recognize all articles of LJF and LF. Although a few LF articles are misjudged at the sub-class level, the hand-held FT-IR models are able to exactly discriminate LJF and LF. As a direct and label-free analytical technique, FT-IR spectroscopy has great potential in the rapid and automatic chemical identification of herbal materials either in laboratories or in fields. This is helpful to prevent the spread and use of adulterated herbal materials in time.

Corona discharge radical emission spectroscopy: a multi-channel detector with nose-type function for discrimination analysis.

PubMed

Tian, Yunfei; Wu, Peng; Wu, Xi; Jiang, Xiaoming; Xu, Kailai; Hou, Xiandeng

2013-04-21

A simple and economical multi-channel optical sensor using corona discharge radical emission spectroscopy is developed and explored as an optical nose for discrimination analysis of volatile organic compounds, wines, and even isomers.

Detection of Genetically Modified Sugarcane by Using Terahertz Spectroscopy and Chemometrics

NASA Astrophysics Data System (ADS)

Liu, J.; Xie, H.; Zha, B.; Ding, W.; Luo, J.; Hu, C.

2018-03-01

A methodology is proposed to identify genetically modified sugarcane from non-genetically modified sugarcane by using terahertz spectroscopy and chemometrics techniques, including linear discriminant analysis (LDA), support vector machine-discriminant analysis (SVM-DA), and partial least squares-discriminant analysis (PLS-DA). The classification rate of the above mentioned methods is compared, and different types of preprocessing are considered. According to the experimental results, the best option is PLS-DA, with an identification rate of 98%. The results indicated that THz spectroscopy and chemometrics techniques are a powerful tool to identify genetically modified and non-genetically modified sugarcane.

Investigation of the composition of anabolic tablets using near infrared spectroscopy and Raman chemical imaging.

PubMed

Rebiere, Hervé; Ghyselinck, Céline; Lempereur, Laurent; Brenier, Charlotte

2016-01-01

The use of performance enhancing drugs is a widespread phenomenon in professional and leisure sports. A spectroscopic study was carried out on anabolic tablets labelled as 5 mg methandienone tablets provided by police departments. The analytical approach was based on a two-step methodology: a fast analysis of tablets using near infrared (NIR) spectroscopy to assess sample homogeneity based on their global composition, followed by Raman chemical imaging of one sample per NIR profile to obtain information on sample formulation. NIR spectroscopy assisted by a principal components analysis (PCA) enabled fast discrimination of different profiles based on the excipient formulation. Raman hyperspectral imaging and multivariate curve resolution - alternating least square (MCR-ALS) provided chemical images of the distribution of the active substance and excipients within tablets and facilitated identification of the active compounds. The combination of NIR spectroscopy and Raman chemical imaging highlighted dose-to-dose variations and succeeded in the discrimination of four different formulations out of eight similar samples of anabolic tablets. Some samples contained either methandienone or methyltestosterone whereas one sample did not contain an active substance. Other ingredients were sucrose, lactose, starch or talc. Both techniques were fast and non-destructive and therefore can be carried out as exploratory methods prior to destructive screening methods. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

In situ monitoring of cocrystals in formulation development using low-frequency Raman spectroscopy.

PubMed

Otaki, Takashi; Tanabe, Yuta; Kojima, Takashi; Miura, Masaru; Ikeda, Yukihiro; Koide, Tatsuo; Fukami, Toshiro

2018-05-05

In recent years, to guarantee a quality-by-design approach to the development of pharmaceutical products, it is important to identify properties of raw materials and excipients in order to determine critical process parameters and critical quality attributes. Feedback obtained from real-time analyses using various process analytical technology (PAT) tools has been actively investigated. In this study, in situ monitoring using low-frequency (LF) Raman spectroscopy (10-200 cm -1 ), which may have higher discriminative ability among polymorphs than near-infrared spectroscopy and conventional Raman spectroscopy (200-1800 cm -1 ), was investigated as a possible application to PAT. This is because LF-Raman spectroscopy obtains information about intermolecular and/or lattice vibrations in the solid state. The monitoring results obtained from Furosemide/Nicotinamide cocrystal indicate that LF-Raman spectroscopy is applicable to in situ monitoring of suspension and fluidized bed granulation processes, and is an effective technique as a PAT tool to detect the conversion risk of cocrystals. LF-Raman spectroscopy is also used as a PAT tool to monitor reactions, crystallizations, and manufacturing processes of drug substances and products. In addition, a sequence of conversion behaviors of Furosemide/Nicotinamide cocrystals was determined by performing in situ monitoring for the first time. Copyright © 2018 Elsevier B.V. All rights reserved.

Discrimination and chemical phylogenetic study of seven species of Dendrobium using infrared spectroscopy combined with cluster analysis

NASA Astrophysics Data System (ADS)

Luo, Congpei; He, Tao; Chun, Ze

2013-04-01

Dendrobium is a commonly used and precious herb in Traditional Chinese Medicine. The high biodiversity of Dendrobium and the therapeutic needs require tools for the correct and fast discrimination of different Dendrobium species. This study investigates Fourier transform infrared spectroscopy followed by cluster analysis for discrimination and chemical phylogenetic study of seven Dendrobium species. Despite the general pattern of the IR spectra, different intensities, shapes, peak positions were found in the IR spectra of these samples, especially in the range of 1800-800 cm-1. The second derivative transformation and alcoholic extracting procedure obviously enlarged the tiny spectral differences among these samples. The results indicated each Dendrobium species had a characteristic IR spectra profile, which could be used to discriminate them. The similarity coefficients among the samples were analyzed based on their second derivative IR spectra, which ranged from 0.7632 to 0.9700, among the seven Dendrobium species, and from 0.5163 to 0.9615, among the ethanol extracts. A dendrogram was constructed based on cluster analysis the IR spectra for studying the chemical phylogenetic relationships among the samples. The results indicated that D. denneanum and D. crepidatum could be the alternative resources to substitute D. chrysotoxum, D. officinale and D. nobile which were officially recorded in Chinese Pharmacopoeia. In conclusion, with the advantages of high resolution, speediness and convenience, the experimental approach can successfully discriminate and construct the chemical phylogenetic relationships of the seven Dendrobium species.

A discrimination model in waste plastics sorting using NIR hyperspectral imaging system.

PubMed

Zheng, Yan; Bai, Jiarui; Xu, Jingna; Li, Xiayang; Zhang, Yimin

2018-02-01

Classification of plastics is important in the recycling industry. A plastic identification model in the near infrared spectroscopy wavelength range 1000-2500 nm is proposed for the characterization and sorting of waste plastics using acrylonitrile butadiene styrene (ABS), polystyrene (PS), polypropylene (PP), polyethylene (PE), polyethylene terephthalate (PET), and polyvinyl chloride (PVC). The model is built by the feature wavelengths of standard samples applying the principle component analysis (PCA), and the accuracy, property and cross-validation of the model were analyzed. The model just contains a simple equation, center of mass coordinates, and radial distance, with which it is easy to develop classification and sorting software. A hyperspectral imaging system (HIS) with the identification model verified its practical application by using the unknown plastics. Results showed that the identification accuracy of unknown samples is 100%. All results suggested that the discrimination model was potential to an on-line characterization and sorting platform of waste plastics based on HIS. Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of linear discriminant analysis and Attenuated Total Reflectance Fourier Transform Infrared microspectroscopy for diagnosis of colon cancer.

PubMed

Khanmohammadi, Mohammadreza; Bagheri Garmarudi, Amir; Samani, Simin; Ghasemi, Keyvan; Ashuri, Ahmad

2011-06-01

Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) microspectroscopy was applied for detection of colon cancer according to the spectral features of colon tissues. Supervised classification models can be trained to identify the tissue type based on the spectroscopic fingerprint. A total of 78 colon tissues were used in spectroscopy studies. Major spectral differences were observed in 1,740-900 cm(-1) spectral region. Several chemometric methods such as analysis of variance (ANOVA), cluster analysis (CA) and linear discriminate analysis (LDA) were applied for classification of IR spectra. Utilizing the chemometric techniques, clear and reproducible differences were observed between the spectra of normal and cancer cases, suggesting that infrared microspectroscopy in conjunction with spectral data processing would be useful for diagnostic classification. Using LDA technique, the spectra were classified into cancer and normal tissue classes with an accuracy of 95.8%. The sensitivity and specificity was 100 and 93.1%, respectively.

Principal component analysis of bacteria using surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Guicheteau, Jason; Christesen, Steven D.

2006-05-01

Surface-enhanced Raman scattering (SERS) provides rapid fingerprinting of biomaterial in a non-destructive manner. The problem of tissue fluorescence, which can overwhelm a normal Raman signal from biological samples, is largely overcome by treatment of biomaterials with colloidal silver. This work presents a study into the applicability of qualitative SER spectroscopy with principal component analysis (PCA) for the discrimination of four biological threat simulants; Bacillus globigii, Pantoea agglomerans, Brucella noetomae, and Yersinia rohdei. We also demonstrate differentiation of gram-negative and gram-positive species and as well as spores and vegetative cells of Bacillus globigii.

Application of micro-Fourier transform infrared spectroscopy to the examination of paint samples

NASA Astrophysics Data System (ADS)

Zięba-Palus, J.

1999-11-01

The examination and identification of automobile paints is an important problem in road accidents investigations. Since the real sample available is very small, only sensitive microtechniques can be applied. The methods of optical microscopy and micro-Fourier transform infrared spectroscopy (MK-FTIR) supported by scanning electron microscopy together with X-ray microanalysis (SEM-EDX) allow one to carry out the examination of each paint layer without any separation procedure. In this paper an attempt is made to discriminate between different automobile paints of the same colour by the use of these methods for criminalistic investigations.

Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis.

PubMed

Lee, Byeong-Ju; Kim, Hye-Youn; Lim, Sa Rang; Huang, Linfang; Choi, Hyung-Kyoon

2017-01-01

Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and lateral root) of P. ginseng. The optimal partial-least-squares regression (PLSR) models for discriminating ginseng samples were determined by selecting normalization methods, number of partial-least-squares (PLS) components, and variable influence on projection (VIP) cutoff values. The best prediction model for discriminating 5- and 6-year-old ginseng was developed using tap root, vector normalization applied after the second differentiation, one PLS component, and a VIP cutoff of 1.0 (based on the lowest root-mean-square error of prediction value). In addition, for discriminating among the three parts of P. ginseng, optimized PLSR models were established using data sets obtained from vector normalization, two PLS components, and VIP cutoff values of 1.5 (for 5-year-old ginseng) and 1.3 (for 6-year-old ginseng). To our knowledge, this is the first study to provide a novel strategy for rapidly discriminating the cultivation ages and parts of P. ginseng using FT-IR by selected normalization methods, number of PLS components, and VIP cutoff values.

Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis

PubMed Central

Lim, Sa Rang; Huang, Linfang

2017-01-01

Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and lateral root) of P. ginseng. The optimal partial-least-squares regression (PLSR) models for discriminating ginseng samples were determined by selecting normalization methods, number of partial-least-squares (PLS) components, and variable influence on projection (VIP) cutoff values. The best prediction model for discriminating 5- and 6-year-old ginseng was developed using tap root, vector normalization applied after the second differentiation, one PLS component, and a VIP cutoff of 1.0 (based on the lowest root-mean-square error of prediction value). In addition, for discriminating among the three parts of P. ginseng, optimized PLSR models were established using data sets obtained from vector normalization, two PLS components, and VIP cutoff values of 1.5 (for 5-year-old ginseng) and 1.3 (for 6-year-old ginseng). To our knowledge, this is the first study to provide a novel strategy for rapidly discriminating the cultivation ages and parts of P. ginseng using FT-IR by selected normalization methods, number of PLS components, and VIP cutoff values. PMID:29049369

Laser-induced breakdown spectroscopy-based investigation and classification of pharmaceutical tablets using multivariate chemometric analysis

PubMed Central

Myakalwar, Ashwin Kumar; Sreedhar, S.; Barman, Ishan; Dingari, Narahara Chari; Rao, S. Venugopal; Kiran, P. Prem; Tewari, Surya P.; Kumar, G. Manoj

2012-01-01

We report the effectiveness of laser-induced breakdown spectroscopy (LIBS) in probing the content of pharmaceutical tablets and also investigate its feasibility for routine classification. This method is particularly beneficial in applications where its exquisite chemical specificity and suitability for remote and on site characterization significantly improves the speed and accuracy of quality control and assurance process. Our experiments reveal that in addition to the presence of carbon, hydrogen, nitrogen and oxygen, which can be primarily attributed to the active pharmaceutical ingredients, specific inorganic atoms were also present in all the tablets. Initial attempts at classification by a ratiometric approach using oxygen to nitrogen compositional values yielded an optimal value (at 746.83 nm) with the least relative standard deviation but nevertheless failed to provide an acceptable classification. To overcome this bottleneck in the detection process, two chemometric algorithms, i.e. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA), were implemented to exploit the multivariate nature of the LIBS data demonstrating that LIBS has the potential to differentiate and discriminate among pharmaceutical tablets. We report excellent prospective classification accuracy using supervised classification via the SIMCA algorithm, demonstrating its potential for future applications in process analytical technology, especially for fast on-line process control monitoring applications in the pharmaceutical industry. PMID:22099648

NMR spectroscopy of filtered serum of prostate cancer: A new frontier in metabolomics.

PubMed

Kumar, Deepak; Gupta, Ashish; Mandhani, Anil; Sankhwar, Satya Narain

2016-09-01

To address the shortcomings of digital rectal examinations (DRE), serum prostate-specific antigen (PSA), and trans-rectal ultrasound (TRUS) for precise determination of prostate cancer (PC) and differentiation from benign prostatic hyperplasia (BPH), we applied (1) H-nuclear magnetic resonance (NMR) spectroscopy as a surrogate tactic for probing and prediction of PC and BPH. The study comprises 210 filtered sera from suspected PC, BPH, and a healthy subjects' cohort (HC). The filtered serum approach delineates to identify and quantify 52 metabolites using (1) H NMR spectroscopy. All subjects had undergone clinical evaluations (DRE, PSA, and TRUS) followed by biopsy for Gleason score, if needed. NMR-measured metabolites and clinical evaluation data were examined separately using linear multivariate discriminant function analysis (DFA) to probe the signature descriptors for each cohort. DFA indicated that glycine, sarcosine, alanine, creatine, xanthine, and hypoxanthine were able to determine abnormal prostate (BPH + PC). DFA-based classification presented high precision (86.2% by NMR and 68.1% by clinical laboratory method) in discriminating HC from BPH + PC. DFA reveals that alanine, sarcosine, creatinine, glycine, and citrate were able to discriminate PC from BPH. DFA-based categorization exhibited high accuracy (88.3% by NMR and 75.2% by clinical laboratory method) to differentiate PC from BPH. (1) H NMR-based metabolic profiling of filtered-serum sample appears to be assuring, swift, and least-invasive for probing and prediction of PC and BPH with its signature metabolic profile. This novel technique is not only on a par with histopathological evaluation of PC determination but is also comparable to liquid chromatography-based mass spectrometry to identify the metabolites. Prostate 76:1106-1119, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Advanced Signal Processing Analysis of Laser-Induced Breakdown Spectroscopy Data for the Discrimination of Obsidian Sources

DTIC Science & Technology

2012-02-09

different sources [12,13], but the analytical techniques needed for such analysis (XRD, INAA , & ICP-MS) are time consuming and require expensive...partial least-squares discriminant analysis (PLSDA) that used the SIMPLS solving method [33]. In the experi- ment design, a leave-one-sample-out (LOSO) para...REPORT Advanced signal processing analysis of laser-induced breakdown spectroscopy data for the discrimination of obsidian sources 14. ABSTRACT 16

Applications of Raman micro-spectroscopy to stem cell technology: label-free molecular discrimination and monitoring cell differentiation.

PubMed

Ghita, Adrian; Pascut, Flavius C; Sottile, Virginie; Denning, Chris; Notingher, Ioan

Stem cell therapy is widely acknowledged as a key medical technology of the 21st century which may provide treatments for many currently incurable diseases. These cells have an enormous potential for cell replacement therapies to cure diseases such as Parkinson's disease, diabetes and cardiovascular disorders, as well as in tissue engineering as a reliable cell source for providing grafts to replace and repair diseased tissues. Nevertheless, the progress in this field has been difficult in part because of lack of techniques that can measure non-invasively the molecular properties of cells. Such repeated measurements can be used to evaluate the culture conditions during differentiation, cell quality and phenotype heterogeneity of stem cell progeny. Raman spectroscopy is an optical technique based on inelastic scattering of laser photons by molecular vibrations of cellular molecules and can be used to provide chemical fingerprints of cells or organelles without fixation, lysis or use of labels and other contrast enhancing chemicals. Because differentiated cells are specialized to perform specific functions, these cells produce specific biochemicals that can be detected by Raman micro-spectroscopy. This mini-review paper describes applications of Raman micro-scpectroscopy to measure moleculare properties of stem cells during differentiation in-vitro. The paper focuses on time- and spatially-resolved Raman spectral measurements that allow repeated investigation of live stem cells in-vitro.

Novel single-cell functional analysis of red blood cells using laser tweezers Raman spectroscopy: application for sickle cell disease.

PubMed

Liu, Rui; Mao, Ziliang; Matthews, Dennis L; Li, Chin-Shang; Chan, James W; Satake, Noriko

2013-07-01

Laser tweezers Raman spectroscopy was used to characterize the oxygenation response of single normal adult, sickle, and cord blood red blood cells (RBCs) to an applied mechanical force. Individual cells were subjected to different forces by varying the laser power of a single-beam optical trap, and the intensities of several oxygenation-specific Raman spectral peaks were monitored to determine the oxygenation state of the cells. For all three cell types, an increase in laser power (or mechanical force) induced a greater deoxygenation of the cell. However, sickle RBCs deoxygenated more readily than normal RBCs when subjected to the same optical forces. Conversely, cord blood RBCs were able to maintain their oxygenation better than normal RBCs. These results suggest that differences in the chemical or mechanical properties of fetal, normal, and sickle cells affect the degree to which applied mechanical forces can deoxygenate the cell. Populations of normal, sickle, and cord RBCs were identified and discriminated based on this mechanochemical phenomenon. This study demonstrates the potential application of laser tweezers Raman spectroscopy as a single-cell, label-free analytical tool to characterize the functional (e.g., mechanical deformability, oxygen binding) properties of normal and diseased RBCs. Copyright © 2013 ISEH - Society for Hematology and Stem Cells. Published by Elsevier Inc. All rights reserved.

Discrimination of selected species of pathogenic bacteria using near-infrared Raman spectroscopy and principal components analysis

NASA Astrophysics Data System (ADS)

de Siqueira e Oliveira, Fernanda SantAna; Giana, Hector Enrique; Silveira, Landulfo

2012-10-01

A method, based on Raman spectroscopy, for identification of different microorganisms involved in bacterial urinary tract infections has been proposed. Spectra were collected from different bacterial colonies (Gram-negative: Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis, Pseudomonas aeruginosa and Enterobacter cloacae, and Gram-positive: Staphylococcus aureus and Enterococcus spp.), grown on culture medium (agar), using a Raman spectrometer with a fiber Raman probe (830 nm). Colonies were scraped from the agar surface and placed on an aluminum foil for Raman measurements. After preprocessing, spectra were submitted to a principal component analysis and Mahalanobis distance (PCA/MD) discrimination algorithm. We found that the mean Raman spectra of different bacterial species show similar bands, and S. aureus was well characterized by strong bands related to carotenoids. PCA/MD could discriminate Gram-positive bacteria with sensitivity and specificity of 100% and Gram-negative bacteria with sensitivity ranging from 58 to 88% and specificity ranging from 87% to 99%.

Bimodal spectroscopic evaluation of ultra violet-irradiated mouse skin inflammatory and precancerous stages: instrumentation, spectral feature extraction/selection and classification (k-NN, LDA and SVM)

NASA Astrophysics Data System (ADS)

Díaz-Ayil, G.; Amouroux, M.; Blondel, W. C. P. M.; Bourg-Heckly, G.; Leroux, A.; Guillemin, F.; Granjon, Y.

2009-07-01

This paper deals with the development and application of in vivo spatially-resolved bimodal spectroscopy (AutoFluorescence AF and Diffuse Reflectance DR), to discriminate various stages of skin precancer in a preclinical model (UV-irradiated mouse): Compensatory Hyperplasia CH, Atypical Hyperplasia AH and Dysplasia D. A programmable instrumentation was developed for acquiring AF emission spectra using 7 excitation wavelengths: 360, 368, 390, 400, 410, 420 and 430 nm, and DR spectra in the 390-720 nm wavelength range. After various steps of intensity spectra preprocessing (filtering, spectral correction and intensity normalization), several sets of spectral characteristics were extracted and selected based on their discrimination power statistically tested for every pair-wise comparison of histological classes. Data reduction with Principal Components Analysis (PCA) was performed and 3 classification methods were implemented (k-NN, LDA and SVM), in order to compare diagnostic performance of each method. Diagnostic performance was studied and assessed in terms of sensitivity (Se) and specificity (Sp) as a function of the selected features, of the combinations of 3 different inter-fibers distances and of the numbers of principal components, such that: Se and Sp ≈ 100% when discriminating CH vs. others; Sp ≈ 100% and Se > 95% when discriminating Healthy vs. AH or D; Sp ≈ 74% and Se ≈ 63%for AH vs. D.

Optical Spectroscopic Analysis for the Discrimination of Extra-Virgin Olive Oil.

PubMed

McReynolds, Naomi; Auñón Garcia, Juan M; Guengerich, Zoe; Smith, Terry K; Dholakia, Kishan

2016-11-01

We demonstrate the ability to discriminate between five brands of commercially available extra-virgin olive oil (EVOO) using Raman spectroscopy or fluorescence spectroscopy. Data was taken on both a 'bulk optics' free space system and on a compact handheld device, each capable of taking both Raman and fluorescence data. With the compact Raman device we achieved an average sensitivity and specificity of 98.4% and 99.6% for discrimination, respectively. Our approach illustrates that both Raman and fluorescence spectroscopy can be used for portable discrimination of EVOOs. This technique may enable detection of EVOO that has undergone counterfeiting or adulteration. The main challenge with this technique is that oxidation of EVOO causes a shift in the Raman signal over time. It would therefore be necessary to retrain the database regularly. We demonstrate preliminary data to address this issue, which may enable successful discrimination over time. We show that by discarding the first principal component, which contains information on the variations due to oxidation, we can improve discrimination efficiency. © The Author(s) 2016.

A novel combined approach of diffuse reflectance UV-Vis-NIR spectroscopy and multivariate analysis for non-destructive examination of blue ballpoint pen inks in forensic application.

PubMed

Kumar, Raj; Sharma, Vishal

2017-03-15

The present research is focused on the analysis of writing inks using destructive UV-Vis spectroscopy (dissolution of ink by the solvent) and non-destructive diffuse reflectance UV-Vis-NIR spectroscopy along with Chemometrics. Fifty seven samples of blue ballpoint pen inks were analyzed under optimum conditions to determine the differences in spectral features of inks among same and different manufacturers. Normalization was performed on the spectroscopic data before chemometric analysis. Principal Component Analysis (PCA) and K-mean cluster analysis were used on the data to ascertain whether the blue ballpoint pen inks could be differentiated by their UV-Vis/UV-Vis NIR spectra. The discriminating power is calculated by qualitative analysis by the visual comparison of the spectra (absorbance peaks), produced by the destructive and non-destructive methods. In the latter two methods, the pairwise comparison is made by incorporating the clustering method. It is found that chemometric method provides better discriminating power (98.72% and 99.46%, in destructive and non-destructive, respectively) in comparison to the qualitative analysis (69.67%). Copyright © 2016 Elsevier B.V. All rights reserved.

Study on nondestructive discrimination of genuine and counterfeit wild ginsengs using NIRS

NASA Astrophysics Data System (ADS)

Lu, Q.; Fan, Y.; Peng, Z.; Ding, H.; Gao, H.

2012-07-01

A new approach for the nondestructive discrimination between genuine wild ginsengs and the counterfeit ones by near infrared spectroscopy (NIRS) was developed. Both discriminant analysis and back propagation artificial neural network (BP-ANN) were applied to the model establishment for discrimination. Optimal modeling wavelengths were determined based on the anomalous spectral information of counterfeit samples. Through principal component analysis (PCA) of various wild ginseng samples, genuine and counterfeit, the cumulative percentages of variance of the principal components were obtained, serving as a reference for principal component (PC) factor determination. Discriminant analysis achieved an identification ratio of 88.46%. With sample' truth values as its outputs, a three-layer BP-ANN model was built, which yielded a higher discrimination accuracy of 100%. The overall results sufficiently demonstrate that NIRS combined with BP-ANN classification algorithm performs better on ginseng discrimination than discriminant analysis, and can be used as a rapid and nondestructive method for the detection of counterfeit wild ginsengs in food and pharmaceutical industry.

Discrimination of soft tissues using laser-induced breakdown spectroscopy in combination with k nearest neighbors (kNN) and support vector machine (SVM) classifiers

NASA Astrophysics Data System (ADS)

Li, Xiaohui; Yang, Sibo; Fan, Rongwei; Yu, Xin; Chen, Deying

2018-06-01

In this paper, discrimination of soft tissues using laser-induced breakdown spectroscopy (LIBS) in combination with multivariate statistical methods is presented. Fresh pork fat, skin, ham, loin and tenderloin muscle tissues are manually cut into slices and ablated using a 1064 nm pulsed Nd:YAG laser. Discrimination analyses between fat, skin and muscle tissues, and further between highly similar ham, loin and tenderloin muscle tissues, are performed based on the LIBS spectra in combination with multivariate statistical methods, including principal component analysis (PCA), k nearest neighbors (kNN) classification, and support vector machine (SVM) classification. Performances of the discrimination models, including accuracy, sensitivity and specificity, are evaluated using 10-fold cross validation. The classification models are optimized to achieve best discrimination performances. The fat, skin and muscle tissues can be definitely discriminated using both kNN and SVM classifiers, with accuracy of over 99.83%, sensitivity of over 0.995 and specificity of over 0.998. The highly similar ham, loin and tenderloin muscle tissues can also be discriminated with acceptable performances. The best performances are achieved with SVM classifier using Gaussian kernel function, with accuracy of 76.84%, sensitivity of over 0.742 and specificity of over 0.869. The results show that the LIBS technique assisted with multivariate statistical methods could be a powerful tool for online discrimination of soft tissues, even for tissues of high similarity, such as muscles from different parts of the animal body. This technique could be used for discrimination of tissues suffering minor clinical changes, thus may advance the diagnosis of early lesions and abnormalities.

Near infrared spectroscopy of human muscles

NASA Astrophysics Data System (ADS)

Gasbarrone, R.; Currà, A.; Cardillo, A.; Bonifazi, G.; Serranti, S.

2018-02-01

Optical spectroscopy is a powerful tool in research and industrial applications. Its properties of being rapid, non-invasive and not destructive make it a promising technique for qualitative as well as quantitative analysis in medicine. Recent advances in materials and fabrication techniques provided portable, performant, sensing spectrometers readily operated by user-friendly cabled or wireless systems. We used such a system to test whether infrared spectroscopy techniques, currently utilized in many areas as primary/secondary raw materials sector, cultural heritage, agricultural/food industry, environmental remote and proximal sensing, pharmaceutical industry, etc., could be applied in living humans to categorize muscles. We acquired muscles infrared spectra in the Vis-SWIR regions (350-2500 nm), utilizing an ASD FieldSpec 4 Standard-Res Spectroradiometer with a spectral sampling capability of 1.4 nm at 350-1000 nm and 1.1 nm at 1001-2500 nm. After a preliminary spectra pre-processing (i.e. signal scattering reduction), Principal Component Analysis (PCA) was applied to identify similar spectral features presence and to realize their further grouping. Partial Least-Squares Discriminant Analysis (PLS-DA) was utilized to implement discrimination/prediction models. We studied 22 healthy subjects (age 25-89 years, 11 females), by acquiring Vis-SWIR spectra from the upper limb muscles (i.e. biceps, a forearm flexor, and triceps, a forearm extensor). Spectroscopy was performed in fixed limb postures (elbow angle approximately 90‡). We found that optical spectroscopy can be applied to study human tissues in vivo. Vis-SWIR spectra acquired from the arm detect muscles, distinguish flexors from extensors.

Quantitative assessment of specific defects in roasted ground coffee via infrared-photoacoustic spectroscopy.

PubMed

Dias, Rafael Carlos Eloy; Valderrama, Patrícia; Março, Paulo Henrique; Dos Santos Scholz, Maria Brigida; Edelmann, Michael; Yeretzian, Chahan

2018-07-30

Chemical analyses and sensory evaluation are the most applied methods for quality control of roasted and ground coffee (RG). However, faster alternatives would be highly valuable. Here, we applied infrared-photoacoustic spectroscopy (FTIR-PAS) on RG powder. Mixtures of specific defective beans were blended with healthy (defect-free) Coffea arabica and Coffea canephora bases in specific ratios, forming different classes of blends. Principal Component Analysis allowed predicting the amount/fraction and nature of the defects in blends while partial Least Squares Discriminant Analysis revealed similarities between blends (=samples). A successful predictive model was obtained using six classes of blends. The model could classify 100% of the samples into four classes. The specificities were higher than 0.9. Application of FTIR-PAS on RG coffee to characterize and classify blends has shown to be an accurate, easy, quick and "green" alternative to current methods. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Species-specific detection of processed animal proteins in feed by Raman spectroscopy.

PubMed

Mandrile, Luisa; Amato, Giuseppina; Marchis, Daniela; Martra, Gianmario; Rossi, Andrea Mario

2017-08-15

The existing European Regulation (EC n° 51/2013) prohibits the use of animals meals in feedstuffs in order to prevent Bovine Spongiform Encephalopathy infection and diffusion, however the legislation is rapidly moving towards a partial lifting of the "feed ban" and the competent control organisms are urged to develop suitable analytical methods able to avoid food safety incidents related to animal origin products. The limitations of the official methods (i.e. light microscopy and Polymerase Chain Reaction) suggest exploring new analytic ways to get reliable results in a short time. The combination of spectroscopic techniques with optical microscopy allows the development of an individual particle method able to meet both selectivity and sensitivity requirements (0.1%w/w). A spectroscopic method based on Fourier Transform micro-Raman spectroscopy coupled with Discriminant Analysis is here presented. This approach could be very useful for in-situ applications, such as customs inspections, since it drastically reduces time and costs of analysis. Copyright © 2017. Published by Elsevier Ltd.

Toward a Model-Based Predictive Controller Design in Brain–Computer Interfaces

PubMed Central

Kamrunnahar, M.; Dias, N. S.; Schiff, S. J.

2013-01-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain–computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8–23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications. PMID:21267657

Toward a model-based predictive controller design in brain-computer interfaces.

PubMed

Kamrunnahar, M; Dias, N S; Schiff, S J

2011-05-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain-computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8-23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications.

Variable filter array spectrometer of VPD PbSe

NASA Astrophysics Data System (ADS)

Linares-Herrero, R.; Vergara, G.; Gutiérrez-Álvarez, R.; Fernández-Montojo, C.; Gómez, L. J.; Villamayor, V.; Baldasano-Ramírez, A.; Montojo, M. T.

2012-06-01

MWIR spectroscopy shows a large potential in the current IR devices market, due to its multiple applications (gas detection, chemical analysis, industrial monitoring, combustion and flame characterization, food packaging etc) and its outstanding performance (good sensitivity, NDT method, velocity of response, among others), opening this technique to very diverse fields of application, such as industrial monitoring and control, agriculture, medicine and environmental monitoring. However, even though a big interest on MWIR spectroscopy technique has been present in the last years, two major barriers have held it back from its widespread use outside the laboratory: the complexity and delicateness of some popular techniques such as Fourier-transform IR (FT-IR) spectrometers, and the lack of affordable specific key elements such a MWIR light sources and low cost (real uncooled) detectors. Recent developments in electrooptical components are helping to overcome these drawbacks. The need for simpler solutions for analytical measurements has prompted the development of better and more affordable uncooled MWIR detectors, electronics and optics. In this paper a new MWIR spectrometry device is presented. Based on linear arrays of different geometries (64, 128 and 256 elements), NIT has developed a MWIR Variable Filter Array Spectrometer (VFAS). This compact device, with no moving parts, based on a rugged and affordable detector, is suitable to be used in applications which demand high sensitivity, good spectral discrimination, reliability and compactness, and where an alternative to the traditional scanning instrument is desired. Some measurements carried out for several industries will be also presented.

FT-IR spectroscopy and multivariate analysis as an auxiliary tool for diagnosis of mental disorders: Bipolar and schizophrenia cases

NASA Astrophysics Data System (ADS)

Ogruc Ildiz, G.; Arslan, M.; Unsalan, O.; Araujo-Andrade, C.; Kurt, E.; Karatepe, H. T.; Yilmaz, A.; Yalcinkaya, O. B.; Herken, H.

2016-01-01

In this study, a methodology based on Fourier-transform infrared spectroscopy and principal component analysis and partial least square methods is proposed for the analysis of blood plasma samples in order to identify spectral changes correlated with some biomarkers associated with schizophrenia and bipolarity. Our main goal was to use the spectral information for the calibration of statistical models to discriminate and classify blood plasma samples belonging to bipolar and schizophrenic patients. IR spectra of 30 samples of blood plasma obtained from each, bipolar and schizophrenic patients and healthy control group were collected. The results obtained from principal component analysis (PCA) show a clear discrimination between the bipolar (BP), schizophrenic (SZ) and control group' (CG) blood samples that also give possibility to identify three main regions that show the major differences correlated with both mental disorders (biomarkers). Furthermore, a model for the classification of the blood samples was calibrated using partial least square discriminant analysis (PLS-DA), allowing the correct classification of BP, SZ and CG samples. The results obtained applying this methodology suggest that it can be used as a complimentary diagnostic tool for the detection and discrimination of these mental diseases.

Controlling protected designation of origin of wine by Raman spectroscopy.

PubMed

Mandrile, Luisa; Zeppa, Giuseppe; Giovannozzi, Andrea Mario; Rossi, Andrea Mario

2016-11-15

In this paper, a Fourier Transform Raman spectroscopy method, to authenticate the provenience of wine, for food traceability applications was developed. In particular, due to the specific chemical fingerprint of the Raman spectrum, it was possible to discriminate different wines produced in the Piedmont area (North West Italy) in accordance with i) grape varieties, ii) production area and iii) ageing time. In order to create a consistent training set, more than 300 samples from tens of different producers were analyzed, and a chemometric treatment of raw spectra was applied. A discriminant analysis method was employed in the classification procedures, providing a classification capability (percentage of correct answers) of 90% for validation of grape analysis and geographical area provenance, and a classification capability of 84% for ageing time classification. The present methodology was applied successfully to raw materials without any preliminary treatment of the sample, providing a response in a very short time. Copyright © 2016 Elsevier Ltd. All rights reserved.

Authentication of virgin olive oil by a novel curve resolution approach combined with visible spectroscopy.

PubMed

Ferreiro-González, Marta; Barbero, Gerardo F; Álvarez, José A; Ruiz, Antonio; Palma, Miguel; Ayuso, Jesús

2017-04-01

Adulteration of olive oil is not only a major economic fraud but can also have major health implications for consumers. In this study, a combination of visible spectroscopy with a novel multivariate curve resolution method (CR), principal component analysis (PCA) and linear discriminant analysis (LDA) is proposed for the authentication of virgin olive oil (VOO) samples. VOOs are well-known products with the typical properties of a two-component system due to the two main groups of compounds that contribute to the visible spectra (chlorophylls and carotenoids). Application of the proposed CR method to VOO samples provided the two pure-component spectra for the aforementioned families of compounds. A correlation study of the real spectra and the resolved component spectra was carried out for different types of oil samples (n=118). LDA using the correlation coefficients as variables to discriminate samples allowed the authentication of 95% of virgin olive oil samples. Copyright © 2016 Elsevier Ltd. All rights reserved.

Balance measured by the sway balance smart-device application does not discriminate between older persons with and without a fall history.

PubMed

Vincenzo, Jennifer L; Glenn, Jordan M; Gray, Stephanie M; Gray, Michelle

2016-08-01

Clinical functional assessments of balance often lack specificity and sensitivity in discriminating and predicting falls among community-dwelling older adults. We determined the feasibility of using a smart-device application measuring balance to discriminate fall status among older adults. We also evaluated differences between smart-device balance measurements when secured with or without a harness. A cross-sectional study design to determine the ability of the Sway Balance smart-device application (SWAY) to discriminate older adults based on fall history. The Berg Balance Scale (BBS) and Activities-Specific Balance Confidence Scale (ABC) were used as comparative, clinically based assessments. Community-dwelling older adults with (n = 25) and without (n = 32) a history of fall(s) participated. Multivariate analysis of variance was used to determine differences among assessments based on fall history. Logistic regression models determined the ability of each assessment to discriminate fall history. Older adults with and without a history of falls were not significantly different on SWAY (P = 0.92) but were different on BBS (P = 0.01), and ABC (P < 0.001). Similarly, SWAY did not discriminate fall history (P = 0.92), while BBS and ABC both discriminated fall history (P < 0.01). Paired t tests between SWAY scores with and without a harness indicated no differences (P ≥ 0.05). Among the older adults studied, the BBS and ABC measures discriminated groups defined by fall history, while the SWAY smart-device balance application did not. Modifications to the application may improve the discriminating ability of the measure in the recognition of fall status in older adults.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cherepy, Nerine J.; Sanner, Robert D.; Beck, Patrick R.

In this paper, transparent plastic scintillators based on polyvinyltoluene (PVT) have been fabricated with high loading of bismuth carboxylates for gamma spectroscopy, and with lithium carboxylates for neutron detection. When activated with a combination of standard fluors, 2,5-diphenyloxazole (PPO) and tetraphenylbutadiene (TPB), gamma light yields with 15 wt% bismuth tripivalate of 5000 Ph/MeV are measured. A PVT plastic formulation including 30 wt% lithium pivalate and 30 wt% PPO offers both pulse shape discrimination, and a neutron capture peak at ~400 keVee. Finally, in another configuration, a bismuth-loaded PVT plastic is coated with ZnS( 6Li) paint, permitting simultaneous gamma and neutronmore » detection via pulse shape discrimination with a figure-of-merit of 3.8, while offering gamma spectroscopy with energy resolution of R(662 keV)=15%.« less

Bismuth- and lithium-loaded plastic scintillators for gamma and neutron detection

NASA Astrophysics Data System (ADS)

Cherepy, Nerine J.; Sanner, Robert D.; Beck, Patrick R.; Swanberg, Erik L.; Tillotson, Thomas M.; Payne, Stephen A.; Hurlbut, Charles R.

2015-04-01

Transparent plastic scintillators based on polyvinyltoluene (PVT) have been fabricated with high loading of bismuth carboxylates for gamma spectroscopy, and with lithium carboxylates for neutron detection. When activated with a combination of standard fluors, 2,5-diphenyloxazole (PPO) and tetraphenylbutadiene (TPB), gamma light yields with 15 wt% bismuth tripivalate of 5000 Ph/MeV are measured. A PVT plastic formulation including 30 wt% lithium pivalate and 30 wt% PPO offers both pulse shape discrimination, and a neutron capture peak at 400 keVee. In another configuration, a bismuth-loaded PVT plastic is coated with ZnS(6Li) paint, permitting simultaneous gamma and neutron detection via pulse shape discrimination with a figure-of-merit of 3.8, while offering gamma spectroscopy with energy resolution of R(662 keV)=15%.

Comparative study on fast classification of brick samples by combination of principal component analysis and linear discriminant analysis using stand-off and table-top laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Vítková, Gabriela; Prokeš, Lubomír; Novotný, Karel; Pořízka, Pavel; Novotný, Jan; Všianský, Dalibor; Čelko, Ladislav; Kaiser, Jozef

2014-11-01

Focusing on historical aspect, during archeological excavation or restoration works of buildings or different structures built from bricks it is important to determine, preferably in-situ and in real-time, the locality of bricks origin. Fast classification of bricks on the base of Laser-Induced Breakdown Spectroscopy (LIBS) spectra is possible using multivariate statistical methods. Combination of principal component analysis (PCA) and linear discriminant analysis (LDA) was applied in this case. LIBS was used to classify altogether the 29 brick samples from 7 different localities. Realizing comparative study using two different LIBS setups - stand-off and table-top it is shown that stand-off LIBS has a big potential for archeological in-field measurements.

Dual-modal cancer detection based on optical pH sensing and Raman spectroscopy

NASA Astrophysics Data System (ADS)

Kim, Soogeun; Lee, Seung Ho; Min, Sun Young; Byun, Kyung Min; Lee, Soo Yeol

2017-10-01

A dual-modal approach using Raman spectroscopy and optical pH sensing was investigated to discriminate between normal and cancerous tissues. Raman spectroscopy has demonstrated the potential for in vivo cancer detection. However, Raman spectroscopy has suffered from strong fluorescence background of biological samples and subtle spectral differences between normal and disease tissues. To overcome those issues, pH sensing is adopted to Raman spectroscopy as a dual-modal approach. Based on the fact that the pH level in cancerous tissues is lower than that in normal tissues due to insufficient vasculature formation, the dual-modal approach combining the chemical information of Raman spectrum and the metabolic information of pH level can improve the specificity of cancer diagnosis. From human breast tissue samples, Raman spectra and pH levels are measured using fiber-optic-based Raman and pH probes, respectively. The pH sensing is based on the dependence of pH level on optical transmission spectrum. Multivariate statistical analysis is performed to evaluate the classification capability of the dual-modal method. The analytical results show that the dual-modal method based on Raman spectroscopy and optical pH sensing can improve the performance of cancer classification.

Combining Raman spectroscopy and digital holographic microscopy for label-free classification of human immune cells (Conference Presentation)

NASA Astrophysics Data System (ADS)

McReynolds, Naomi; Cooke, Fiona G. M.; Chen, Mingzhou; Powis, Simon J.; Dholakia, Kishan

2017-02-01

Moving towards label-free techniques for cell identification is essential for many clinical and research applications. Raman spectroscopy and digital holographic microscopy (DHM) are both label-free, non-destructive optical techniques capable of providing complimentary information. We demonstrate a multi-modal system which may simultaneously take Raman spectra and DHM images to provide both a molecular and a morphological description of our sample. In this study we use Raman spectroscopy and DHM to discriminate between three immune cell populations CD4+ T cells, B cells, and monocytes, which together comprise key functional immune cell subsets in immune responses to invading pathogens. Various parameters that may be used to describe the phase images are also examined such as pixel value histograms or texture analysis. Using our system it is possible to consider each technique individually or in combination. Principal component analysis is used on the data set to discriminate between cell types and leave-one-out cross-validation is used to estimate the efficiency of our method. Raman spectroscopy provides specific chemical information but requires relatively long acquisition times, combining this with a faster modality such as DHM could help achieve faster throughput rates. The combination of these two complimentary optical techniques provides a wealth of information for cell characterisation which is a step towards achieving label free technology for the identification of human immune cells.

Infrared and NIR Raman spectroscopy in medical microbiology

NASA Astrophysics Data System (ADS)

Naumann, Dieter

1998-04-01

FTIR and FT-NIR Raman spectra of intact microbial cells are highly specific, fingerprint-like signatures which can be used to (i) discriminate between diverse microbial species and strains, (ii) detect in situ intracellular components or structures such as inclusion bodies, storage materials or endospores, (iii) detect and quantify metabolically released CO2 in response to various different substrate, and (iv) characterize growth-dependent phenomena and cell-drug interactions. The characteristic information is extracted from the spectral contours by applying resolution enhancement techniques, difference spectroscopy, and pattern recognition methods such as factor-, cluster-, linear discriminant analysis, and artificial neural networks. Particularly interesting applications arise by means of a light microscope coupled to the spectrometer. FTIR spectra of micro-colonies containing less than 103 cells can be obtained from colony replica by a stamping technique that transfers micro-colonies growing on culture plates to a special IR-sample holder. Using a computer controlled x, y- stage together with mapping and video techniques, the fundamental tasks of microbiological analysis, namely detection, enumeration, and differentiation of micro- organisms can be integrated in one single apparatus. FTIR and NIR-FT-Raman spectroscopy can also be used in tandem to characterize medically important microorganisms. Currently novel methodologies are tested to take advantage of the complementary information of IR and Raman spectra. Representative examples on medically important microorganisms will be given that highlight the new possibilities of vibrational spectroscopies.

Thin layered drawing media probed by THz time-domain spectroscopy.

PubMed

Tasseva, J; Taschin, A; Bartolini, P; Striova, J; Fontana, R; Torre, R

2016-12-19

Dry and wet drawing materials were investigated by THz time-domain spectroscopy in transmission mode. Carbon-based and iron-gall inks have been studied, some prepared following ancient recipes and others using current synthetic materials; a commercial ink was studied as well. We measured the THz signals on the thin films of liquid inks deposited on polyethylene pellicles, comparing the results with the thick pellets of dried inks blended with polyethylene powder. This study required the implementation of an accurate experimental method and data analysis procedure able to provide a reliable extraction of the material transmission parameters from a structured sample composed of thin layers, down to a thickness of a few tens of micrometers. THz measurements on thin ink layers enabled the determination of both the absorption and the refractive index in an absolute scale in the 0.1-3 THz range, as well as the layer thickness. THz spectroscopic features of a paper sheet dyed by using one of the iron-gall inks were also investigated. Our results showed that THz time-domain spectroscopy enables the discrimination of various inks on different supports, including the application on paper, together with the proper determination of the absorption coefficients and indices of refraction.

Discriminating oat and groat kernels from other grains using near infrared spectroscopy

USDA-ARS?s Scientific Manuscript database

Oat and groats can be discriminated from other grains such as barley, wheat, rye, and triticale (non-oats) using near infrared spectroscopy. The two instruments tested were the manual version of the ARS-USDA Single Kernel Near Infrared (SKNIR) and the automated QualySense QSorter Explorer high-speed...

Early identification of cervical neoplasia with Raman spectroscopy and advanced methods for biomedical applications

NASA Astrophysics Data System (ADS)

Jess, Phillip R. T.; Smith, Daniel D. W.; Mazilu, Michael; Cormack, Iain; Riches, Andrew C.; Herrington, C. Simon; Dholakia, Kishan

2008-02-01

Early detection of malignant tumours, or their precursor lesions, can dramatically improve patient outcome. High risk human Papillomavirus (HPV), particularly HPV16, infection can lead to the initiation and development of uterine cervical neoplasia. Bearing this in mind the identification of the effects of HPV infection may have clinical value. In this manuscript we investigate the application of Raman microspectroscopy to detect the presence of HPV in cultured cells when compared with normal cells. We also investigate the effect of sample fixation, which is a common clinical practice, on the ability of Raman spectroscopy to detect the presence of HPV. Raman spectra were acquired from Primary Human Keratinocytes (PHK), PHK expressing the E7 gene of HPV 16 (PHK E7) and CaSki cells, an HPV16 containing cervical carcinoma derived cell line. The average Raman spectra display variations, mostly in peaks relating to DNA and proteins, consistent with HPV gene expression and the onset of neoplasia in both live and fixed samples. Principle component analysis was used to objectively discriminate between the cells types giving sensitivities up to 100% for the comparison between PHK and CaSki. These results show that Raman spectroscopy can discriminate between cell lines representing different stages of cervical neoplasia. Furthermore Raman spectroscopy was able to identify cells expressing the HPV 16 E7 gene suggesting the approach may be of value in clinical practice. Finally this technique was also able to detect the effects of the virus in fixed samples demonstrating the compatibility of this technique with current cervical screening methods. However if Raman spectroscopy is to make a significant impact in clinical practice the long acquisition times must be addressed. In this report we examine the potential for beam shaping and advanced to improve the signal to noise ration hence subsequently facilitating a reduction in acquisition time.

Application of laser tweezers Raman spectroscopy techniques to the monitoring of single cell response to stimuli

NASA Astrophysics Data System (ADS)

Chan, James W.; Liu, Rui; Matthews, Dennis L.

2012-06-01

Laser tweezers Raman spectroscopy (LTRS) combines optical trapping with micro-Raman spectroscopy to enable label-free biochemical analysis of individual cells and small biological particles in suspension. The integration of the two technologies greatly simplifies the sample preparation and handling of suspension cells for spectroscopic analysis in physiologically meaningful conditions. In our group, LTRS has been used to study the effects of external perturbations, both chemical and mechanical, on the biochemistry of the cell. Single cell dynamics can be studied by performing longitudinal studies to continuously monitor the response of the cell as it interacts with its environment. The ability to carry out these measurements in-vitro makes LTRS an attractive tool for many biomedical applications. Here, we discuss the use of LTRS to study the response of cancer cells to chemotherapeutics and bacteria cells to antibiotics and show that the life cycle and apoptosis of the cells can be detected. These results show the promise of LTRS for drug discovery/screening, antibiotic susceptibility testing, and chemotherapy response monitoring applications. In separate experiments, we study the response of red blood cells to the mechanical forces imposed on the cell by the optical tweezers. A laser power dependent deoxygenation of the red blood cell in the single beam trap is reported. Normal, sickle cell, and fetal red blood cells have a different behavior that enables the discrimination of the cell types based on this mechanochemical response. These results show the potential utility of LTRS for diagnosing and studying red blood cell diseases.

Are gay men and lesbians discriminated against when applying for jobs? A four-city, Internet-based field experiment.

PubMed

Bailey, John; Wallace, Michael; Wright, Bradley

2013-01-01

An Internet-based field experiment was conducted to examine potential hiring discrimination based on sexual orientation; specifically, the "first contact" between job applicants and employers was looked at. In response to Internet job postings on CareerBuilder.com®, more than 4,600 resumes were sent to employers in 4 U.S. cities: Philadelphia, Chicago, Dallas, and San Francisco. The resumes varied randomly with regard to gender, implied sexual orientation, and other characteristics. Two hypotheses were tested: first, that employers' response rates vary by the applicants' assumed sexuality; and second, that employers' Response Rates by Sexuality vary by city. Effects of city were controlled for to hold constant any variation in labor market conditions in the 4 cities. Based on employer responses to the applications, it was concluded that there is no evidence that gay men or lesbians are discriminated against in their first encounter with employers, and no significant variation across cities in these encounters was found. Implications of these results for the literature on hiring discrimination based on sexual orientation, the strengths and limitations of the research, and the potential for the Internet-based field experiment design in future studies of discrimination are discussed.

Progress in standoff surface contaminant detector platform

NASA Astrophysics Data System (ADS)

Dupuis, Julia R.; Giblin, Jay; Dixon, John; Hensley, Joel; Mansur, David; Marinelli, William J.

2017-05-01

Progress towards the development of a longwave infrared quantum cascade laser (QLC) based standoff surface contaminant detection platform is presented. The detection platform utilizes reflectance spectroscopy with application to optically thick and thin materials including solid and liquid phase chemical warfare agents, toxic industrial chemicals and materials, and explosives. The platform employs an ensemble of broadband QCLs with a spectrally selective detector to interrogate target surfaces at 10s of m standoff. A version of the Adaptive Cosine Estimator (ACE) featuring class based screening is used for detection and discrimination in high clutter environments. Detection limits approaching 0.1 μg/cm2 are projected through speckle reduction methods enabling detector noise limited performance. The design, build, and validation of a breadboard version of the QCL-based surface contaminant detector are discussed. Functional test results specific to the QCL illuminator are presented with specific emphasis on speckle reduction.

Combined Raman spectroscopy and autofluoresence imaging method for in vivo skin tumor diagnosis

NASA Astrophysics Data System (ADS)

Zakharov, V. P.; Bratchenko, I. A.; Myakinin, O. O.; Artemyev, D. N.; Khristoforova, Y. A.; Kozlov, S. V.; Moryatov, A. A.

2014-09-01

The fluorescence and Raman spectroscopy (RS) combined method of in vivo detection of malignant human skin cancer was demonstrated. The fluorescence analysis was used for detection of abnormalities during fast scanning of large tissue areas. In suspected cases of malignancy the Raman spectrum analysis of biological tissue was performed to determine the type of neoplasm. A special RS phase method was proposed for in vivo identification of skin tumor. Quadratic Discriminant Analysis was used for tumor type classification on phase planes. It was shown that the application of phase method provides a diagnosis of malignant melanoma with a sensitivity of 89% and a specificity of 87%.

Terahertz spectroscopy for the study of paraffin-embedded gastric cancer samples

NASA Astrophysics Data System (ADS)

Wahaia, Faustino; Kasalynas, Irmantas; Seliuta, Dalius; Molis, Gediminas; Urbanowicz, Andrzej; Carvalho Silva, Catia D.; Carneiro, Fatima; Valusis, Gintaras; Granja, Pedro L.

2015-01-01

Terahertz (THz) spectroscopy constitute promising technique for biomedical applications as a complementary and powerful tool for diseases screening specially for early cancer diagnostic. The THz radiation is not harmful to biological tissues. As increased blood supply in cancer-affected tissues and consequent local increase in tissue water content makes THz technology a potentially attractive. In the present work, samples of healthy and adenocarcinoma-affected gastric tissue were analyzed using transmission time-domain THz spectroscopy (THz-TDS). The work shows the capability of the technique to distinguish between normal and cancerous regions in dried and paraffin-embedded samples. Plots of absorption coefficient α and refractive index n of normal and cancer affected tissues, are presented and the conditions for discrimination between normal and affected tissues are discussed.

Fourier transform infrared spectroscopy and chemometrics for the characterization and discrimination of writing/photocopier paper types: Application in forensic document examinations

NASA Astrophysics Data System (ADS)

Kumar, Raj; Kumar, Vinay; Sharma, Vishal

2017-01-01

The aim of the present work is to explore the non-destructive application of ATR-FTIR technique for characterization and discrimination of paper samples which could be helpful to give forensic aid in resolving legal cases. Twenty-four types of paper brands were purchased from local market in and around Chandigarh, India. All the paper samples were subjected to ATR-FTIR analysis from 400 to 4000 cm- 1 wavenumber range. The qualitative feature and Chemometrics of the obtained spectral data are used for characterization and discrimination. Characterization is achieved by matching the peaks with standards of cellulose and inorganic fillers, a usual constituents of paper. Three different regions of IR, i.e. 400-2000 cm- 1, 2000-4000 cm- 1 and 400-4000 cm- 1 were selected for differentiation by Chemometrics analysis. The discrimination is achieved on the basis of three principal components, i.e. PC 1, PC 2 and PC 3. It is observed that maximum discrimination was procured in the wave number range of i.e. 2000-4000 cm- 1. Discriminating power was calculated on the basis of qualitative features as well, and it is found that the discrimination of paper samples was better achieved by Chemometrics analysis rather than qualitative features. The discriminating power by Chemometrics is 99.64% and which is larger as ever achieved by any group for present number of samples. The present result confirms that this study will be highly useful in forensic document examination work in the legal cases, where the authenticity of the document is challenged. The results are completely analytical and, therefore, overcome the problem encounter in traditional routine light/radiation scanning methods which are still in practice by various questioned document laboratories.

Multi-modal approach using Raman spectroscopy and optical coherence tomography for the discrimination of colonic adenocarcinoma from normal colon

PubMed Central

Ashok, Praveen C.; Praveen, Bavishna B.; Bellini, Nicola; Riches, Andrew; Dholakia, Kishan; Herrington, C. Simon

2013-01-01

We report a multimodal optical approach using both Raman spectroscopy and optical coherence tomography (OCT) in tandem to discriminate between colonic adenocarcinoma and normal colon. Although both of these non-invasive techniques are capable of discriminating between normal and tumour tissues, they are unable individually to provide both the high specificity and high sensitivity required for disease diagnosis. We combine the chemical information derived from Raman spectroscopy with the texture parameters extracted from OCT images. The sensitivity obtained using Raman spectroscopy and OCT individually was 89% and 78% respectively and the specificity was 77% and 74% respectively. Combining the information derived using the two techniques increased both sensitivity and specificity to 94% demonstrating that combining complementary optical information enhances diagnostic accuracy. These data demonstrate that multimodal optical analysis has the potential to achieve accurate non-invasive cancer diagnosis. PMID:24156073

A manual and an automatic TERS based virus discrimination

NASA Astrophysics Data System (ADS)

Olschewski, Konstanze; Kämmer, Evelyn; Stöckel, Stephan; Bocklitz, Thomas; Deckert-Gaudig, Tanja; Zell, Roland; Cialla-May, Dana; Weber, Karina; Deckert, Volker; Popp, Jürgen

2015-02-01

Rapid techniques for virus identification are more relevant today than ever. Conventional virus detection and identification strategies generally rest upon various microbiological methods and genomic approaches, which are not suited for the analysis of single virus particles. In contrast, the highly sensitive spectroscopic technique tip-enhanced Raman spectroscopy (TERS) allows the characterisation of biological nano-structures like virions on a single-particle level. In this study, the feasibility of TERS in combination with chemometrics to discriminate two pathogenic viruses, Varicella-zoster virus (VZV) and Porcine teschovirus (PTV), was investigated. In a first step, chemometric methods transformed the spectral data in such a way that a rapid visual discrimination of the two examined viruses was enabled. In a further step, these methods were utilised to perform an automatic quality rating of the measured spectra. Spectra that passed this test were eventually used to calculate a classification model, through which a successful discrimination of the two viral species based on TERS spectra of single virus particles was also realised with a classification accuracy of 91%.Rapid techniques for virus identification are more relevant today than ever. Conventional virus detection and identification strategies generally rest upon various microbiological methods and genomic approaches, which are not suited for the analysis of single virus particles. In contrast, the highly sensitive spectroscopic technique tip-enhanced Raman spectroscopy (TERS) allows the characterisation of biological nano-structures like virions on a single-particle level. In this study, the feasibility of TERS in combination with chemometrics to discriminate two pathogenic viruses, Varicella-zoster virus (VZV) and Porcine teschovirus (PTV), was investigated. In a first step, chemometric methods transformed the spectral data in such a way that a rapid visual discrimination of the two examined viruses was enabled. In a further step, these methods were utilised to perform an automatic quality rating of the measured spectra. Spectra that passed this test were eventually used to calculate a classification model, through which a successful discrimination of the two viral species based on TERS spectra of single virus particles was also realised with a classification accuracy of 91%. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr07033j

Raman sorting and identification of single living micro-organisms with optical tweezers

NASA Astrophysics Data System (ADS)

Xie, Changan; Chen, De; Li, Yong-Qing

2005-07-01

We report on a novel technique for sorting and identification of single biological cells and food-borne bacteria based on laser tweezers and Raman spectroscopy (LTRS). With this technique, biological cells of different physiological states in a sample chamber were identified by their Raman spectral signatures and then they were selectively manipulated into a clean collection chamber with optical tweezers through a microchannel. As an example, we sorted the live and dead yeast cells into the collection chamber and validated this with a standard staining technique. We also demonstrated that bacteria existing in spoiled foods could be discriminated from a variety of food particles based on their characteristic Raman spectra and then isolated with laser manipulation. This label-free LTRS sorting technique may find broad applications in microbiology and rapid examination of food-borne diseases.

Near-infrared confocal micro-Raman spectroscopy combined with PCA-LDA multivariate analysis for detection of esophageal cancer

NASA Astrophysics Data System (ADS)

Chen, Long; Wang, Yue; Liu, Nenrong; Lin, Duo; Weng, Cuncheng; Zhang, Jixue; Zhu, Lihuan; Chen, Weisheng; Chen, Rong; Feng, Shangyuan

2013-06-01

The diagnostic capability of using tissue intrinsic micro-Raman signals to obtain biochemical information from human esophageal tissue is presented in this paper. Near-infrared micro-Raman spectroscopy combined with multivariate analysis was applied for discrimination of esophageal cancer tissue from normal tissue samples. Micro-Raman spectroscopy measurements were performed on 54 esophageal cancer tissues and 55 normal tissues in the 400-1750 cm-1 range. The mean Raman spectra showed significant differences between the two groups. Tentative assignments of the Raman bands in the measured tissue spectra suggested some changes in protein structure, a decrease in the relative amount of lactose, and increases in the percentages of tryptophan, collagen and phenylalanine content in esophageal cancer tissue as compared to those of a normal subject. The diagnostic algorithms based on principal component analysis (PCA) and linear discriminate analysis (LDA) achieved a diagnostic sensitivity of 87.0% and specificity of 70.9% for separating cancer from normal esophageal tissue samples. The result demonstrated that near-infrared micro-Raman spectroscopy combined with PCA-LDA analysis could be an effective and sensitive tool for identification of esophageal cancer.

GRace: a MATLAB-based application for fitting the discrimination-association model.

PubMed

Stefanutti, Luca; Vianello, Michelangelo; Anselmi, Pasquale; Robusto, Egidio

2014-10-28

The Implicit Association Test (IAT) is a computerized two-choice discrimination task in which stimuli have to be categorized as belonging to target categories or attribute categories by pressing, as quickly and accurately as possible, one of two response keys. The discrimination association model has been recently proposed for the analysis of reaction time and accuracy of an individual respondent to the IAT. The model disentangles the influences of three qualitatively different components on the responses to the IAT: stimuli discrimination, automatic association, and termination criterion. The article presents General Race (GRace), a MATLAB-based application for fitting the discrimination association model to IAT data. GRace has been developed for Windows as a standalone application. It is user-friendly and does not require any programming experience. The use of GRace is illustrated on the data of a Coca Cola-Pepsi Cola IAT, and the results of the analysis are interpreted and discussed.

Terahertz time-domain attenuated total reflection spectroscopy applied to the rapid discrimination of the botanical origin of honeys

NASA Astrophysics Data System (ADS)

Liu, Wen; Zhang, Yuying; Yang, Si; Han, Donghai

2018-05-01

A new technique to identify the floral resources of honeys is demanded. Terahertz time-domain attenuated total reflection spectroscopy combined with chemometrics methods was applied to discriminate different categorizes (Medlar honey, Vitex honey, and Acacia honey). Principal component analysis (PCA), cluster analysis (CA) and partial least squares-discriminant analysis (PLS-DA) have been used to find information of the botanical origins of honeys. Spectral range also was discussed to increase the precision of PLS-DA model. The accuracy of 88.46% for validation set was obtained, using PLS-DA model in 0.5-1.5 THz. This work indicated terahertz time-domain attenuated total reflection spectroscopy was an available approach to evaluate the quality of honey rapidly.

Application of FT-IR spectroscopy on breast cancer serum analysis

NASA Astrophysics Data System (ADS)

Elmi, Fatemeh; Movaghar, Afshin Fayyaz; Elmi, Maryam Mitra; Alinezhad, Heshmatollah; Nikbakhsh, Novin

2017-12-01

Breast cancer is regarded as the most malignant tumor among women throughout the world. Therefore, early detection and proper diagnostic methods have been known to help save women's lives. Fourier Transform Infrared (FT-IR) spectroscopy, coupled with PCA-LDA analysis, is a new technique to investigate the characteristics of serum in breast cancer. In this study, 43 breast cancer and 43 healthy serum samples were collected, and the FT-IR spectra were recorded for each one. Then, PCA analysis and linear discriminant analysis (LDA) were used to analyze the spectral data. The results showed that there were differences between the spectra of the two groups. Discriminating wavenumbers were associated with several spectral differences over the 950-1200 cm- 1(sugar), 1190-1350 cm- 1 (collagen), 1475-1710 cm- 1 (protein), 1710-1760 cm- 1 (ester), 2800-3000 cm- 1 (stretching motions of -CH2 & -CH3), and 3090-3700 cm- 1 (NH stretching) regions. PCA-LDA performance on serum IR could recognize changes between the control and the breast cancer cases. The diagnostic accuracy, sensitivity, and specificity of PCA-LDA analysis for 3000-3600 cm- 1 (NH stretching) were found to be 83%, 84%, 74% for the control and 80%, 76%, 72% for the breast cancer cases, respectively. The results showed that the major spectral differences between the two groups were related to the differences in protein conformation in serum samples. It can be concluded that FT-IR spectroscopy, together with multivariate data analysis, is able to discriminate between breast cancer and healthy serum samples.

Esophageal cancer detection based on tissue surface-enhanced Raman spectroscopy and multivariate analysis

NASA Astrophysics Data System (ADS)

Feng, Shangyuan; Lin, Juqiang; Huang, Zufang; Chen, Guannan; Chen, Weisheng; Wang, Yue; Chen, Rong; Zeng, Haishan

2013-01-01

The capability of using silver nanoparticle based near-infrared surface enhanced Raman scattering (SERS) spectroscopy combined with principal component analysis (PCA) and linear discriminate analysis (LDA) to differentiate esophageal cancer tissue from normal tissue was presented. Significant differences in Raman intensities of prominent SERS bands were observed between normal and cancer tissues. PCA-LDA multivariate analysis of the measured tissue SERS spectra achieved diagnostic sensitivity of 90.9% and specificity of 97.8%. This exploratory study demonstrated great potential for developing label-free tissue SERS analysis into a clinical tool for esophageal cancer detection.

LED-based near infrared sensor for cancer diagnostics

NASA Astrophysics Data System (ADS)

Bogomolov, Andrey; Ageev, Vladimir; Zabarylo, Urszula; Usenov, Iskander; Schulte, Franziska; Kirsanov, Dmitry; Belikova, Valeria; Minet, Olaf; Feliksberger, E.; Meshkovsky, I.; Artyushenko, Viacheslav

2016-03-01

Optical spectroscopic technologies are increasingly used for cancer diagnostics. Feasibility of differentiation between malignant and healthy samples of human kidney using Fluorescence, Raman, MIR and NIR spectroscopy has been recently reported . In the present work, a simplification of NIR spectroscopy method has been studied. Traditional high-resolution NIR spectrometry was replaced by an optical sensor based on a set of light-emitting diodes at selected wavelengths as light sources and a photodiode. Two prototypes of the sensor have been developed and tested using 14 in-vitro samples of seven kidney tumor patients. Statistical evaluation of results using principal component analysis and partial least-squares discriminant analysis has been performed. Despite only partial discrimination between tumor and healthy tissue achieved by the presented new technique, the results evidence benefits of LED-based near-infrared sensing used for oncological diagnostics. Publisher's Note: This paper, originally published on 4 March, 2016, was replaced with a corrected/revised version on 7 April, 2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance.

Bismuth- and lithium-loaded plastic scintillators for gamma and neutron detection

DOE PAGES

Cherepy, Nerine J.; Sanner, Robert D.; Beck, Patrick R.; ...

2015-01-09

In this paper, transparent plastic scintillators based on polyvinyltoluene (PVT) have been fabricated with high loading of bismuth carboxylates for gamma spectroscopy, and with lithium carboxylates for neutron detection. When activated with a combination of standard fluors, 2,5-diphenyloxazole (PPO) and tetraphenylbutadiene (TPB), gamma light yields with 15 wt% bismuth tripivalate of 5000 Ph/MeV are measured. A PVT plastic formulation including 30 wt% lithium pivalate and 30 wt% PPO offers both pulse shape discrimination, and a neutron capture peak at ~400 keVee. Finally, in another configuration, a bismuth-loaded PVT plastic is coated with ZnS( 6Li) paint, permitting simultaneous gamma and neutronmore » detection via pulse shape discrimination with a figure-of-merit of 3.8, while offering gamma spectroscopy with energy resolution of R(662 keV)=15%.« less

Characterization of a tin-loaded liquid scintillator for gamma spectroscopy and neutron detection

NASA Astrophysics Data System (ADS)

Wen, Xianfei; Harvey, Taylor; Weinmann-Smith, Robert; Walker, James; Noh, Young; Farley, Richard; Enqvist, Andreas

2018-07-01

A tin-loaded liquid scintillator has been developed for gamma spectroscopy and neutron detection. The scintillator was characterized in regard to energy resolution, pulse shape discrimination, neutron light output function, and timing resolution. The loading of tin into scintillators with low effective atomic number was demonstrated to provide photopeaks with acceptable energy resolution. The scintillator was shown to have reasonable neutron/gamma discrimination capability based on the charge comparison method. The effect on the discrimination quality of the total charge integration time and the initial delay time for tail charge integration was studied. To obtain the neutron light output function, the time-of-flight technique was utilized with a 252Cf source. The light output function was validated with the MCNPX-PoliMi code by comparing the measured and simulated pule height spectra. The timing resolution of the developed scintillator was also evaluated. The tin-loading was found to have negligible impact on the scintillation decay times. However, a relatively large degradation of timing resolution was observed due to the reduced light yield.

Estimating the concentration of urea and creatinine in the human serum of normal and dialysis patients through Raman spectroscopy.

PubMed

de Almeida, Maurício Liberal; Saatkamp, Cassiano Junior; Fernandes, Adriana Barrinha; Pinheiro, Antonio Luiz Barbosa; Silveira, Landulfo

2016-09-01

Urea and creatinine are commonly used as biomarkers of renal function. Abnormal concentrations of these biomarkers are indicative of pathological processes such as renal failure. This study aimed to develop a model based on Raman spectroscopy to estimate the concentration values of urea and creatinine in human serum. Blood sera from 55 clinically normal subjects and 47 patients with chronic kidney disease undergoing dialysis were collected, and concentrations of urea and creatinine were determined by spectrophotometric methods. A Raman spectrum was obtained with a high-resolution dispersive Raman spectrometer (830 nm). A spectral model was developed based on partial least squares (PLS), where the concentrations of urea and creatinine were correlated with the Raman features. Principal components analysis (PCA) was used to discriminate dialysis patients from normal subjects. The PLS model showed r = 0.97 and r = 0.93 for urea and creatinine, respectively. The root mean square errors of cross-validation (RMSECV) for the model were 17.6 and 1.94 mg/dL, respectively. PCA showed high discrimination between dialysis and normality (95 % accuracy). The Raman technique was able to determine the concentrations with low error and to discriminate dialysis from normal subjects, consistent with a rapid and low-cost test.

Optical pathology of human brain metastasis of lung cancer using combined resonance Raman and spatial frequency spectroscopies

NASA Astrophysics Data System (ADS)

Zhou, Yan; Liu, Cheng-hui; Pu, Yang; Cheng, Gangge; Zhou, Lixin; Chen, Jun; Zhu, Ke; Alfano, Robert R.

2016-03-01

Raman spectroscopy has become widely used for diagnostic purpose of breast, lung and brain cancers. This report introduced a new approach based on spatial frequency spectra analysis of the underlying tissue structure at different stages of brain tumor. Combined spatial frequency spectroscopy (SFS), Resonance Raman (RR) spectroscopic method is used to discriminate human brain metastasis of lung cancer from normal tissues for the first time. A total number of thirty-one label-free micrographic images of normal and metastatic brain cancer tissues obtained from a confocal micro- Raman spectroscopic system synchronously with examined RR spectra of the corresponding samples were collected from the identical site of tissue. The difference of the randomness of tissue structures between the micrograph images of metastatic brain tumor tissues and normal tissues can be recognized by analyzing spatial frequency. By fitting the distribution of the spatial frequency spectra of human brain tissues as a Gaussian function, the standard deviation, σ, can be obtained, which was used to generate a criterion to differentiate human brain cancerous tissues from the normal ones using Support Vector Machine (SVM) classifier. This SFS-SVM analysis on micrograph images presents good results with sensitivity (85%), specificity (75%) in comparison with gold standard reports of pathology and immunology. The dual-modal advantages of SFS combined with RR spectroscopy method may open a new way in the neuropathology applications.

45 CFR 148.102 - Scope, applicability, and effective dates.

Code of Federal Regulations, 2014 CFR

2014-10-01

... stays in connection with childbirth, and to protections against discrimination based on genetic... benefits for mothers and newborns), and § 148.180 (prohibition of health discrimination based on genetic...

Laser-Induced Breakdown Spectroscopy Coupled with Multivariate Chemometrics for Variety Discrimination of Soil

PubMed Central

Yu, Ke-Qiang; Zhao, Yan-Ru; Liu, Fei; He, Yong

2016-01-01

The aim of this work was to analyze the variety of soil by laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics methods. 6 certified reference materials (CRMs) of soil samples were selected and their LIBS spectra were captured. Characteristic emission lines of main elements were identified based on the LIBS curves and corresponding contents. From the identified emission lines, LIBS spectra in 7 lines with high signal-to-noise ratio (SNR) were chosen for further analysis. Principal component analysis (PCA) was carried out using the LIBS spectra at 7 selected lines and an obvious cluster of 6 soils was observed. Soft independent modeling of class analogy (SIMCA) and least-squares support vector machine (LS-SVM) were introduced to establish discriminant models for classifying the 6 types of soils, and they offered the correct discrimination rates of 90% and 100%, respectively. Receiver operating characteristic (ROC) curve was used to evaluate the performance of models and the results demonstrated that the LS-SVM model was promising. Lastly, 8 types of soils from different places were gathered to conduct the same experiments for verifying the selected 7 emission lines and LS-SVM model. The research revealed that LIBS technology coupled with chemometrics could conduct the variety discrimination of soil. PMID:27279284

Improvement of Depth Profiling into Biotissues Using Micro Electrical Impedance Spectroscopy on a Needle with Selective Passivation

PubMed Central

Yun, Joho; Kim, Hyeon Woo; Lee, Jong-Hyun

2016-01-01

A micro electrical impedance spectroscopy (EIS)-on-a-needle for depth profiling (μEoN-DP) with a selective passivation layer (SPL) on a hypodermic needle was recently fabricated to measure the electrical impedance of biotissues along with the penetration depths. The SPL of the μEoN-DP enabled the sensing interdigitated electrodes (IDEs) to contribute predominantly to the measurement by reducing the relative influence of the connection lines on the sensor output. The discrimination capability of the μEoN-DP was verified using phosphate-buffered saline (PBS) at various concentration levels. The resistance and capacitance extracted through curve fitting were similar to those theoretically estimated based on the mixing ratio of PBS and deionized water; the maximum discrepancies were 8.02% and 1.85%, respectively. Depth profiling was conducted using four-layered porcine tissue to verify the effectiveness of the discrimination capability of the μEoN-DP. The magnitude and phase between dissimilar porcine tissues (fat and muscle) were clearly discriminated at the optimal frequency of 1 MHz. Two kinds of simulations, one with SPL and the other with complete passivation layer (CPL), were performed, and it was verified that the SPL was advantageous over CPL in the discrimination of biotissues in terms of sensor output. PMID:28009845

Improvement of Depth Profiling into Biotissues Using Micro Electrical Impedance Spectroscopy on a Needle with Selective Passivation.

PubMed

Yun, Joho; Kim, Hyeon Woo; Lee, Jong-Hyun

2016-12-21

A micro electrical impedance spectroscopy (EIS)-on-a-needle for depth profiling (μEoN-DP) with a selective passivation layer (SPL) on a hypodermic needle was recently fabricated to measure the electrical impedance of biotissues along with the penetration depths. The SPL of the μEoN-DP enabled the sensing interdigitated electrodes (IDEs) to contribute predominantly to the measurement by reducing the relative influence of the connection lines on the sensor output. The discrimination capability of the μEoN-DP was verified using phosphate-buffered saline (PBS) at various concentration levels. The resistance and capacitance extracted through curve fitting were similar to those theoretically estimated based on the mixing ratio of PBS and deionized water; the maximum discrepancies were 8.02% and 1.85%, respectively. Depth profiling was conducted using four-layered porcine tissue to verify the effectiveness of the discrimination capability of the μEoN-DP. The magnitude and phase between dissimilar porcine tissues (fat and muscle) were clearly discriminated at the optimal frequency of 1 MHz. Two kinds of simulations, one with SPL and the other with complete passivation layer (CPL), were performed, and it was verified that the SPL was advantageous over CPL in the discrimination of biotissues in terms of sensor output.

Dual-modal cancer detection based on optical pH sensing and Raman spectroscopy.

PubMed

Kim, Soogeun; Lee, Seung Ho; Min, Sun Young; Byun, Kyung Min; Lee, Soo Yeol

2017-10-01

A dual-modal approach using Raman spectroscopy and optical pH sensing was investigated to discriminate between normal and cancerous tissues. Raman spectroscopy has demonstrated the potential for in vivo cancer detection. However, Raman spectroscopy has suffered from strong fluorescence background of biological samples and subtle spectral differences between normal and disease tissues. To overcome those issues, pH sensing is adopted to Raman spectroscopy as a dual-modal approach. Based on the fact that the pH level in cancerous tissues is lower than that in normal tissues due to insufficient vasculature formation, the dual-modal approach combining the chemical information of Raman spectrum and the metabolic information of pH level can improve the specificity of cancer diagnosis. From human breast tissue samples, Raman spectra and pH levels are measured using fiber-optic-based Raman and pH probes, respectively. The pH sensing is based on the dependence of pH level on optical transmission spectrum. Multivariate statistical analysis is performed to evaluate the classification capability of the dual-modal method. The analytical results show that the dual-modal method based on Raman spectroscopy and optical pH sensing can improve the performance of cancer classification. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Fluorescence spectroscopy for the detection of potentially malignant disorders of the oral cavity: analysis of 30 cases

NASA Astrophysics Data System (ADS)

Francisco, A. L. N.; Correr, W. R.; Azevedo, L. H.; Galletta, V. K.; Pinto, C. A. L.; Kowalski, L. P.; Kurachi, C.

2014-01-01

Oral cancer is a major health problem worldwide and although early diagnosis of potentially malignant and malignant diseases is associated with better treatment results, a large number of cancers are initially misdiagnosed, with unfortunate consequences for long-term survival. Fluorescence spectroscopy is a noninvasive modality of diagnostic approach using induced fluorescence emission in tumors that can improve diagnostic accuracy. The objective of this study was to determine the ability to discriminate between normal oral mucosa and potentially malignant disorders by fluorescence spectroscopy. Fluorescence investigation under 408 and 532 nm excitation wavelengths was performed on 60 subjects, 30 with potentially malignant disorders and 30 volunteers with normal mucosa. Data was analyzed to correlate fluorescence patterns with clinical and histopathological diagnostics. Fluorescence spectroscopy used as a point measurement technique resulted in a great variety of spectral information. In a qualitative analysis of the fluorescence spectral characteristics of each type of injury evaluated, it was possible to discriminate between normal and abnormal oral mucosa. The results show the potential use of fluorescence spectroscopy for an improved discrimination of oral disorders.

Classification of Fusarium-Infected Korean Hulled Barley Using Near-Infrared Reflectance Spectroscopy and Partial Least Squares Discriminant Analysis

PubMed Central

Lim, Jongguk; Kim, Giyoung; Mo, Changyeun; Oh, Kyoungmin; Yoo, Hyeonchae; Ham, Hyeonheui; Kim, Moon S.

2017-01-01

The purpose of this study is to use near-infrared reflectance (NIR) spectroscopy equipment to nondestructively and rapidly discriminate Fusarium-infected hulled barley. Both normal hulled barley and Fusarium-infected hulled barley were scanned by using a NIR spectrometer with a wavelength range of 1175 to 2170 nm. Multiple mathematical pretreatments were applied to the reflectance spectra obtained for Fusarium discrimination and the multivariate analysis method of partial least squares discriminant analysis (PLS-DA) was used for discriminant prediction. The PLS-DA prediction model developed by applying the second-order derivative pretreatment to the reflectance spectra obtained from the side of hulled barley without crease achieved 100% accuracy in discriminating the normal hulled barley and the Fusarium-infected hulled barley. These results demonstrated the feasibility of rapid discrimination of the Fusarium-infected hulled barley by combining multivariate analysis with the NIR spectroscopic technique, which is utilized as a nondestructive detection method. PMID:28974012

Characterization of toners and inkjets by laser ablation spectrochemical methods and Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy

NASA Astrophysics Data System (ADS)

Trejos, Tatiana; Corzo, Ruthmara; Subedi, Kiran; Almirall, José

2014-02-01

Detection and sourcing of counterfeit currency, examination of counterfeit security documents and determination of authenticity of medical records are examples of common forensic document investigations. In these cases, the physical and chemical composition of the ink entries can provide important information for the assessment of the authenticity of the document or for making inferences about common source. Previous results reported by our group have demonstrated that elemental analysis, using either Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS) or Laser Ablation Induced Breakdown Spectroscopy (LIBS), provides an effective, practical and robust technique for the discrimination of document substrates and writing inks with minimal damage to the document. In this study, laser-based methods and Scanning Electron Microscopy-Energy Dispersive X-Ray Spectroscopy (SEM-EDS) methods were developed, optimized and validated for the forensic analysis of more complex inks such as toners and inkjets, to determine if their elemental composition can differentiate documents printed from different sources and to associate documents that originated from the same printing source. Comparison of the performance of each of these methods is presented, including the analytical figures of merit, discrimination capability and error rates. Different calibration strategies resulting in semi-quantitative and qualitative analysis, comparison methods (match criteria) and data analysis and interpretation tools were also developed. A total of 27 black laser toners originating from different manufacturing sources and/or batches were examined to evaluate the discrimination capability of each method. The results suggest that SEM-EDS offers relatively poor discrimination capability for this set (~ 70.7% discrimination of all the possible comparison pairs or a 29.3% type II error rate). Nonetheless, SEM-EDS can still be used as a complementary method of analysis since it has the advantage of being non-destructive to the sample in addition to providing imaging capabilities to further characterize toner samples by their particle morphology. Laser sampling methods resulted in an improvement of the discrimination between different sources with LIBS producing 89% discrimination and LA-ICP-MS resulting in 100% discrimination. In addition, a set of 21 black inkjet samples was examined by each method. The results show that SEM-EDS is not appropriate for inkjet examinations since their elemental composition is typically below the detection capabilities with only sulfur detected in this set, providing only 47.4% discrimination between possible comparison pairs. Laser sampling methods were shown to provide discrimination greater than 94% for this same inkjet set with false exclusion and false inclusion rates lower than 4.1% and 5.7%, for LA-ICP-MS and LIBS respectively. Overall these results confirmed the utility of the examination of printed documents by laser-based micro-spectrochemical methods. SEM-EDS analysis of toners produced a limited utility for discrimination within sources but was not an effective tool for inkjet ink discrimination. Both LA-ICP-MS and LIBS can be used in forensic laboratories to chemically characterize inks on documents and to complement the information obtained by conventional methods and enhance their evidential value.

45 CFR 148.102 - Scope, applicability, and effective dates.

Code of Federal Regulations, 2013 CFR

2013-10-01

... against discrimination based on genetic information apply to all issuers of individual health insurance... newborns), and § 148.180 (prohibition of health discrimination based on genetic information) of this part...

45 CFR 148.102 - Scope, applicability, and effective dates.

Code of Federal Regulations, 2012 CFR

2012-10-01

... against discrimination based on genetic information apply to all issuers of individual health insurance... newborns), and § 148.180 (prohibition of health discrimination based on genetic information) of this part...

The discrimination of fish egg quality and viability by using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Ishigaki, Mika; Sato, Hidetoshi

2014-03-01

Sexual reproductive body can be produced from a fertilized ovum. Once the ovum is fertilized with sperm, it runs through the cell division, differentiates to all kinds of cells, and goes to make a complete body. However, not all of them are viable and some of them stop to ontogenesis showing the developmental abnormality. In order to discriminate the egg quality, we apply Raman spectroscopy for fish egg. After the measurement, these Raman data are checked up with the information about the eggs can survive or not, and we examine what factors are important in egg components to distinguish between "good quality" and "not good quality". We present the results of assessment of egg quality, and investigate whether Raman spectroscopy can be used to a discriminate of egg quality.

Ultrafast Laser-Based Spectroscopy and Sensing: Applications in LIBS, CARS, and THz Spectroscopy

PubMed Central

Leahy-Hoppa, Megan R.; Miragliotta, Joseph; Osiander, Robert; Burnett, Jennifer; Dikmelik, Yamac; McEnnis, Caroline; Spicer, James B.

2010-01-01

Ultrafast pulsed lasers find application in a range of spectroscopy and sensing techniques including laser induced breakdown spectroscopy (LIBS), coherent Raman spectroscopy, and terahertz (THz) spectroscopy. Whether based on absorption or emission processes, the characteristics of these techniques are heavily influenced by the use of ultrafast pulses in the signal generation process. Depending on the energy of the pulses used, the essential laser interaction process can primarily involve lattice vibrations, molecular rotations, or a combination of excited states produced by laser heating. While some of these techniques are currently confined to sensing at close ranges, others can be implemented for remote spectroscopic sensing owing principally to the laser pulse duration. We present a review of ultrafast laser-based spectroscopy techniques and discuss the use of these techniques to current and potential chemical and environmental sensing applications. PMID:22399883

Laser-induced breakdown spectroscopy (LIBS): An innovative tool for studying bacteria

NASA Astrophysics Data System (ADS)

Mohaidat, Qassem I.

Laser-induced breakdown spectroscopy (LIBS) has gained a reputation as a flexible and convenient technique for rapidly determining the elemental composition of samples with minimal or no sample preparation. In this dissertation, I will describe the benefits of using LIBS for the rapid discrimination and identification of bacteria (both pathogenic and non-pathogenic) based on the relative concentration of trace inorganic elements such as Mg, P, Ca, and Na. The speed, portability, and robustness of the technique suggest that LIBS may be applicable as a rapid point-of-care medical diagnostic technology. LIBS spectra of multiple genera of bacteria such as Escherichia, Streptococcus, Mycobacterium, and Staphylococcus were acquired and successfully analyzed using a computerized discriminant function analysis (DFA). It was shown that a LIBS-based bacterial identification might be insensitive to a wide range of biological changes that could occur in the bacterial cell due to a variety of environmental stresses that the cell may encounter. The effect of reducing the number of bacterial cells on the LIBS-based classification was also studied. These results showed that with 2500 bacteria, the identification of bacterial specimens was still possible. Importantly, it was shown that bacteria in mixed samples (more than one type of bacteria being present) were identifiable. The dominant or majority component of a two-component mixture was reliably identified as long as it comprised 70% of the mixture or more. Finally, to simulate a clinical specimen in a precursor to actual clinical tests, Staphylococcus epidermidis bacteria were collected from urine samples (to simulate a urinary tract infection specimen) and were tested via LIBS without washing. The analysis showed that these bacteria possessed exactly the same spectral fingerprint as control bacteria obtained from sterile deionized water, resulting in a 100% correct classification. This indicates that the presence of other trace background biochemicals from clinical fluids will not adversely disrupt a LIBS-based identification of bacteria.

Discrimination of various paper types using diffuse reflectance ultraviolet-visible near-infrared (UV-Vis-NIR) spectroscopy: forensic application to questioned documents.

PubMed

Kumar, Raj; Kumar, Vinay; Sharma, Vishal

2015-06-01

Diffuse reflectance ultraviolet-visible-near-infrared (UV-Vis-NIR) spectroscopy is applied as a means of differentiating various types of writing, office, and photocopy papers (collected from stationery shops in India) on the basis of reflectance and absorbance spectra that otherwise seem to be almost alike in different illumination conditions. In order to minimize bias, spectra from both sides of paper were obtained. In addition, three spectra from three different locations (from one side) were recorded covering the upper, middle, and bottom portions of the paper sample, and the mean average reflectivity of both the sides was calculated. A significant difference was observed in mean average reflectivity of Side A and Side B of the paper using Student's pair >t-test. Three different approaches were used for discrimination: (1) qualitative features of the whole set of samples, (2) principal component analysis, and (3) a combination of both approaches. On the basis of the first approach, i.e., qualitative features, 96.49% discriminating power (DP) was observed, which shows highly significant results with the UV-Vis-NIR technique. In the second approach the discriminating power is further enhanced by incorporating the principal component analysis (PCA) statistical method, where this method describes each UV-Vis spectrum in a group through numerical loading values connected to the first few principal components. All components described 100% variance of the samples, but only the first three PCs are good enough to explain the variance (PC1 = 51.64%, PC2 = 47.52%, and PC3 = 0.54%) of the samples; i.e., the first three PCs described 99.70% of the data, whereas in the third approach, the four samples, C, G, K, and N, out of a total 19 samples, which were not differentiated using qualitative features (approach no. 1), were therefore subjected to PCA. The first two PCs described 99.37% of the spectral features. The discrimination was achieved by using a loading plot between PC1 and PC2. It is therefore concluded that maximum discrimination of writing, office, and photocopy paper could be achieved on the basis of the second approach. Hence, the present inexpensive analytical method can be appropriate for application to routine questioned document examination work in forensic laboratories because it provides nondestructive, quantitative, reliable, and repeatable results.

Near Infrared Spectroscopy Facilitates Rapid Identification of Both Young and Mature Amazonian Tree Species.

PubMed

Lang, Carla; Costa, Flávia Regina Capellotto; Camargo, José Luís Campana; Durgante, Flávia Machado; Vicentini, Alberto

2015-01-01

Precise identification of plant species requires a high level of knowledge by taxonomists and presence of reproductive material. This represents a major limitation for those working with seedlings and juveniles, which differ morphologically from adults and do not bear reproductive structures. Near-infrared spectroscopy (FT-NIR) has previously been shown to be effective in species discrimination of adult plants, so if young and adults have a similar spectral signature, discriminant functions based on FT-NIR spectra of adults can be used to identify leaves from young plants. We tested this with a sample of 419 plants in 13 Amazonian species from the genera Protium and Crepidospermum (Burseraceae). We obtained 12 spectral readings per plant, from adaxial and abaxial surfaces of dried leaves, and compared the rate of correct predictions of species with discriminant functions for different combinations of readings. We showed that the best models for predicting species in early developmental stages are those containing spectral data from both young and adult plants (98% correct predictions of external samples), but even using only adult spectra it is still possible to attain good levels of identification of young. We obtained an average of 75% correct identifications of young plants by discriminant equations based only on adults, when the most informative wavelengths were selected. Most species were accurately predicted (75-100% correct identifications), and only three had poor predictions (27-60%). These results were obtained despite the fact that spectra of young individuals were distinct from those of adults when species were analyzed individually. We concluded that FT-NIR has a high potential in the identification of species even at different ontogenetic stages, and that young plants can be identified based on spectra of adults with reasonable confidence.

Characterisation and identification of bacteria using SERS.

PubMed

Jarvis, Roger M; Goodacre, Royston

2008-05-01

Within microbiology Raman spectroscopy is considered as a very important whole-organism fingerprinting technique, which is used to characterise, discriminate and identify microorganisms and assess how they respond to abiotic or biotic stress. Enhancing the sensitivity of Raman spectroscopy is very beneficial for the rapid analysis of bacteria (and indeed biological systems in general), where the ultimate goal is to achieve this without the need for lengthy cell culture. Bypassing this step would provide significant benefits in many areas such as medical, environmental and industrial microbiology, microbial systems biology, biological warfare countermeasures and bioprocess monitoring. In this tutorial review we will report on the advances made in bacterial studies, a relatively new and exciting application area for SERS.

Fluorescence excitation-emission matrix (EEM) spectroscopy for rapid identification and quality evaluation of cell culture media components.

PubMed

Li, Boyan; Ryan, Paul W; Shanahan, Michael; Leister, Kirk J; Ryder, Alan G

2011-11-01

The application of fluorescence excitation-emission matrix (EEM) spectroscopy to the quantitative analysis of complex, aqueous solutions of cell culture media components was investigated. These components, yeastolate, phytone, recombinant human insulin, eRDF basal medium, and four different chemically defined (CD) media, are used for the formulation of basal and feed media employed in the production of recombinant proteins using a Chinese Hamster Ovary (CHO) cell based process. The comprehensive analysis (either identification or quality assessment) of these materials using chromatographic methods is time consuming and expensive and is not suitable for high-throughput quality control. The use of EEM in conjunction with multiway chemometric methods provided a rapid, nondestructive analytical method suitable for the screening of large numbers of samples. Here we used multiway robust principal component analysis (MROBPCA) in conjunction with n-way partial least squares discriminant analysis (NPLS-DA) to develop a robust routine for both the identification and quality evaluation of these important cell culture materials. These methods are applicable to a wide range of complex mixtures because they do not rely on any predetermined compositional or property information, thus making them potentially very useful for sample handling, tracking, and quality assessment in biopharmaceutical industries.

Determination of melamine of milk based on two-dimensional correlation infrared spectroscopy

NASA Astrophysics Data System (ADS)

Yang, Ren-jie; Liu, Rong; Xu, Kexin

2012-03-01

The adulteration of milk with harmful substances is a threat to public health and beyond question a serious crime. In order to develop a rapid, cost-effective, high-throughput analysis method for detecting of adulterants in milk, the discriminative analysis of melamine is established in milk based on the two-dimensional (2D) correlation infrared spectroscopy in present paper. Pure milk samples and adulterated milk samples with different content of melamine were prepared. Then the Fourier Transform Infrared spectra of all samples were measured at room temperature. The characteristics of pure milk and adulterated milk were studied by one-dimensional spectra. The 2D NIR and 2D IR correlation spectroscopy were calculated under the perturbation of adulteration concentration. In the range from 1400 to 1800 cm-1, two strong autopeaks were aroused by melamine in milk at 1464 cm-1 and 1560 cm-1 in synchronous spectrum. At the same time, the 1560 cm-1 band does not share cross peak with the 1464 cm-1 band, which further confirm that the two bands have the same origin. Also in the range from 4200 to 4800 cm-1, the autopeak was shown at 4648 cm-1 in synchronous spectrum of melamine in milk. 2D NIR-IR hetero-spectral correlation analysis confirmed that the bands at 1464, 1560 and 4648 cm-1 had the same origin. The results demonstrated that the adulterant can be discriminated correctly by 2D correlation infrared spectroscopy.

Multivariate qualitative analysis of banned additives in food safety using surface enhanced Raman scattering spectroscopy

NASA Astrophysics Data System (ADS)

He, Shixuan; Xie, Wanyi; Zhang, Wei; Zhang, Liqun; Wang, Yunxia; Liu, Xiaoling; Liu, Yulong; Du, Chunlei

2015-02-01

A novel strategy which combines iteratively cubic spline fitting baseline correction method with discriminant partial least squares qualitative analysis is employed to analyze the surface enhanced Raman scattering (SERS) spectroscopy of banned food additives, such as Sudan I dye and Rhodamine B in food, Malachite green residues in aquaculture fish. Multivariate qualitative analysis methods, using the combination of spectra preprocessing iteratively cubic spline fitting (ICSF) baseline correction with principal component analysis (PCA) and discriminant partial least squares (DPLS) classification respectively, are applied to investigate the effectiveness of SERS spectroscopy for predicting the class assignments of unknown banned food additives. PCA cannot be used to predict the class assignments of unknown samples. However, the DPLS classification can discriminate the class assignment of unknown banned additives using the information of differences in relative intensities. The results demonstrate that SERS spectroscopy combined with ICSF baseline correction method and exploratory analysis methodology DPLS classification can be potentially used for distinguishing the banned food additives in field of food safety.

Surface-enhanced Raman spectroscopy for differentiation between benign and malignant thyroid tissues

NASA Astrophysics Data System (ADS)

Li, Zuanfang; Li, Chao; Lin, Duo; Huang, Zufang; Pan, Jianji; Chen, Guannan; Lin, Juqiang; Liu, Nenrong; Yu, Yun; Feng, Shangyuan; Chen, Rong

2014-04-01

The aim of this study was to evaluate the potential of applying silver nano-particle based surface-enhanced Raman scattering (SERS) to discriminate different types of human thyroid tissues. SERS measurements were performed on three groups of tissue samples including thyroid cancers (n = 32), nodular goiters (n = 20) and normal thyroid tissues (n = 25). Tentative assignments of the measured tissue SERS spectra suggest interesting cancer specific biomolecular differences. The principal component analysis (PCA) and linear discriminate analysis (LDA) together with the leave-one-out, cross-validated technique yielded diagnostic sensitivities of 92%, 75% and 87.5%; and specificities of 82.6%, 89.4% and 84.4%, respectively, for differentiation among normal, nodular and malignant thyroid tissue samples. This work demonstrates that tissue SERS spectroscopy associated with multivariate analysis diagnostic algorithms has great potential for detection of thyroid cancer at the molecular level.

Forensic discrimination of three common brands of kitchen knives in China by ICP-AES and infrared absorption.

PubMed

Bai, Ru-feng; Ma, Shu-hua; Zhang, Hai-dong; Chang, Lin; Zhang, Zhong; Liu, Li; Zhang, Feng-qin; Guo, Zhao-ming; Shi, Mei-sen

2014-03-01

A block of an injury instrument will be left in wounds sometimes, and the suspect instrument can be discriminated by comparison with the block that was left through elemental analysis. In this study, three brands (Shibazi, Zhangxiaoquan, Qiaoxifu) of kitchen knives with forged, chop, and slice application series were analyzed by inductively coupled plasma atomic emission spectroscopy (ICP-AES) and Infrared Absorption to investigate the type, number of elements and the reference range used for comparing. The results show that when regarding one or more element as the discriminative threshold, together with 5% relative standard deviation (RSD) as the reference range, all the samples could be distinguished among different series. Furthermore, within the same series, the discriminative capability could reach up to 88.57% for all samples. In addition, elements with high content, such as Cr, Mn, and C, were useful to discriminate among different series, and trace elements, such as Ni, Si, and Cu, were useful within the same series. However, in practice, it is necessary to evaluate the accuracy of the method by Standard Reference Material (SRM) before an examination is performed.

Laser-induced Fluorescence Spectroscopy (LIFS) for Discrimination of Genetically Close Sweet Orange Accessions ( Citrus sinensis L. Osbeck).

PubMed

Massaiti Kuboyama Kubota, Thiago; Bebeachibuli Magalhães, Aida; Nery da Silva, Marina; Ribeiro Villas Boas, Paulino; Novelli, Valdenice M; Bastianel, Marinês; Sagawa, Cíntia H D; Cristofani-Yaly, Mariângela; Marcondes Bastos Pereira Milori, Débora

2017-02-01

Although there is substantial diversity among cultivated sweet oranges genotypes with respect to morphological, physiological, and agronomic traits, very little variation at DNA level has been observed. It is possible that this low DNA molecular variability is due to a narrow genetic basis commonly observed in this citrus group. The most different morphological characters observed were originated through mutations, which are maintained by vegetative propagation. Despite all molecular tools available for discrimination between these different accessions, in general, low polymorphism has been observed in all groups of sweet oranges and they may not be identified by molecular markers. In this context, this paper describes the results obtained by using laser-induced fluorescent spectroscopy (LIFS) as a tool to discriminate sweet orange accessions ( Citrus sinensis L. Osbeck) including common, low acidity, pigmented, and navel orange groups, with very little variation at DNA level. The findings showed that LIFS combined with statistical methods is capable to discriminate different accessions. The basic idea is that citrus leaves have multiple fluorophores and concentration depends on their genetics and metabolism. Thus, we consider that the optical properties of citrus leaves may be different, depending on variety. The results have shown that the developed method, for the best classification rate, reaches an average sensitivity and specificity of 95% and 97.5%, respectively. An interesting application of this study is the development of an economically viable tool for early identification in seedling certification, in citrus breeding programs, in cultivar protection, or in germplasm core collection.

Discrimination of several Indonesian specialty coffees using Fluorescence Spectroscopy combined with SIMCA method

NASA Astrophysics Data System (ADS)

Suhandy, D.; Yulia, M.

2018-03-01

Indonesia is one of the important producers of several specialty coffees, which have a particularly high economic value, including Civet coffee (‘kopi luwak’ in Indonesian language) and Peaberry coffee (‘kopi lanang’ in Indonesian language). The production of Civet and Peaberry coffee is very limited. In order to provide authentication of Civet and Peaberry coffee and protect consumers from adulteration, a robust and easy method for evaluating ground Civet and Peaberry coffee and detection of its adulteration is needed. In this study, we investigate the use of fluorescence spectroscopy combined with SIMCA (soft independent modelling of class analogies) method to discriminate three Indonesian specialty coffee: ground Peaberry, Civet and Pagar Alam coffee. Total 90 samples were used (30 samples for Civet, Peaberry and Pagar Alam coffee, respectively). All coffee samples were ground using a home-coffee-grinder. Since particle size in coffee powder has a significant influence on the spectra obtained, we sieved all coffee samples through a nest of U. S. standard sieves (mesh number of 40) on a Meinzer II sieve shaker for 10 minutes to obtain a particle size of 420 µm. The experiments were performed at room temperature (around 27-29°C). All samples were extracted with distilled water and then filtered. For each samples, 3 mL of extracted sample then was pipetted into 10 mm cuvettes for spectral data acquisition. The EEM (excitation-emission matrix) spectral data of coffee samples were acquired using JASCO FP-8300 Fluorescence Spectrometer. The principal component analysis (PCA) result shows that it is possible to discriminate types of coffee based on information from EEM (excitation-emission matrix) spectral data. Using SIMCA method, the discrimination model of Indonesian specialty coffee was successfully developed and resulted in high performance of discrimination with 100% of sensitivity and specificity for Peaberry, Civet and Pagar Alam coffee. This research has opened the possibility to develop a promising method to detect and evaluate authentication of Indonesian specialty coffees using fluorescence spectroscopy.

Ultrasonic standing wave preparation of a liquid cell for glucose measurements in urine by midinfrared spectroscopy and potential application to smart toilets.

PubMed

Yamamoto, Naoyuki; Kawashima, Natsumi; Kitazaki, Tomoya; Mori, Keita; Kang, Hanyue; Nishiyama, Akira; Wada, Kenji; Ishimaru, Ichiro

2018-05-01

Smart toilets could be used to monitor different components of urine in daily life for early detection of lifestyle-related diseases and prompt provision of treatment. For analysis of biological samples such as urine by midinfrared spectroscopy, thin-film samples like liquid cells are needed because of the strong absorption of midinfrared light by water. Conventional liquid cells or fixed cells are prepared based on the liquid membrane method and solution technique, but these are not quantitative and are difficult to set up and clean. We generated an ultrasonic standing wave reflection plane in a sample and produced an ultrasonic liquid cell. In this cell, the thickness of the optical path length was adjustable, as in the conventional method. The reflection plane could be generated at an arbitrary depth and internal reflected light could be detected by changing the frequency of the ultrasonic wave. We could generate refractive index boundaries using the density difference created by the ultrasonic standing wave. Creation of the reflection plane in the sample was confirmed by optical coherence tomography. Using the proposed method and midinfrared spectroscopy, we discriminated between normal urine samples spiked with glucose at different concentrations and obtained a high correlation coefficient. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Elemental analysis of cotton by laser-induced breakdown spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schenk, Emily R.; Almirall, Jose R.

Laser-induced breakdown spectroscopy (LIBS) has been applied to the elemental characterization of unprocessed cotton. This research is important in forensic and fraud detection applications to establish an elemental fingerprint of U.S. cotton by region, which can be used to determine the source of the cotton. To the best of our knowledge, this is the first report of a LIBS method for the elemental analysis of cotton. The experimental setup consists of a Nd:YAG laser that operates at the fundamental wavelength as the LIBS excitation source and an echelle spectrometer equipped with an intensified CCD camera. The relative concentrations of elementsmore » Al, Ba, Ca, Cr, Cu, Fe, Mg, and Sr from both nutrients and environmental contributions were determined by LIBS. Principal component analysis was used to visualize the differences between cotton samples based on the elemental composition by region in the U.S. Linear discriminant analysis of the LIBS data resulted in the correct classification of >97% of the cotton samples by U.S. region and >81% correct classification by state of origin.« less

Combined surface-enhanced Raman spectroscopy biotags and microfluidic platform for quantitative ratiometric discrimination between noncancerous and cancerous cells in flow

NASA Astrophysics Data System (ADS)

Pallaoro, Alessia; Hoonejani, Mehran R.; Braun, Gary B.; Meinhart, Carl; Moskovits, Martin

2013-01-01

Surface-enhanced Raman spectroscopy (SERS) biotags (SBTs) that carry peptides as cell recognition moieties were made from polymer-encapsulated silver nanoparticle dimers, infused with unique Raman reporter molecules. We previously demonstrated their potential use for identification of malignant cells, a central goal in cancer research, through a multiplexed, ratiometric method that can confidently distinguish between cancerous and noncancerous epithelial prostate cells in vitro based on receptor overexpression. Progress has been made toward the application of this quantitative methodology for the identification of cancer cells in a microfluidic flow-focusing device. Beads are used as cell mimics to evaluate the devices. Cells (and beads) are simultaneously incubated with two sets of SBTs while in suspension, then injected into the device for laser interrogation under flow. Each cell event is characterized by a composite Raman spectrum, deconvoluted into its single components to ultimately determine their relative contribution. We have found that using SBTs ratiometrically can provide cell identification in flow, insensitive to normal causes of uncertainty in optical measurements such as variations in focal plane, cell concentration, autofluorescence, and turbidity.

Discrimination of different genuine Danshen and their extracts by Fourier transform infrared spectroscopy combined with two-dimensional correlation infrared spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Xin-hu; Xu, Chang-hua; Sun, Su-qin; Huang, Jian; Zhang, Ke; Li, Guo-yu; Zhu, Yun; Zhou, Qun; Zhang, Zhi-cheng; Wang, Jin-hui

2012-11-01

In this study, six varieties of Danshen from different populations and genuine ("Daodi" in Chinese transliteration) regions were discriminated and identified by a three-step infrared spectroscopy method (Fourier transform-infrared spectroscopy (FT-IR) coupled with second derivative infrared spectroscopy (SD-IR) and two dimensional correlation infrared spectroscopy (2D-IR)). Though only small differences were found among the FT-IR spectra of the six Danshen samples, the positions and intensities of peaks at 3393, 3371, 1613, 1050, and 1036 cm-1 could be considered as the key factors to discriminate them. More significant differences were exhibited in their SD-IR, particularly for the peaks around 1080, 1144, 695, 665, 800, 1610, 1510, 1450, 1117 and 1077 cm-1. The visual 2D-IR spectra provided dynamic chemical structure information of the six Danshen samples with presenting different particular auto-peak clusters, respectively. Moreover, the contents of salvianolic acid B in all samples were measured quantitatively by a validated ultra performance liquid chromatography (UPLC), which was consistent with the FT-IR findings. This study provides a promising method for characteristics and quality control of the complicated and extremely similar herbal medicine like Danshen, which is more cost effective and time saving.

Identification of the traditional Tibetan medicine "Shaji" and their different extracts through tri-step infrared spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Yue; Li, Jingyi; Fan, Gang; Sun, Suqin; Zhang, Yuxin; Zhang, Yi; Tu, Ya

2016-11-01

Hippophae rhamnoides subsp. sinensis Rousi, Hippophae gyantsensis (Rousi) Y. S. Lian, Hippophae neurocarpa S. W. Liu & T. N. He and Hippophae tibetana Schlechtendal are typically used under one name "Shaji", to treat cardiovascular diseases and lung disorders in Tibetan medicine (TM). A complete set of infrared (IR) macro-fingerprints of these four Hippophae species should be characterized and compared simply, accurately, and in detail for identification. In the present study, tri-step IR spectroscopy, which included Fourier transform IR (FT-IR) spectroscopy, second derivative IR (SD-IR) spectroscopy and two-dimensional correlation IR (2D-IR) spectroscopy, was employed to discriminate the four Hippophae species and their corresponding extracts using different solvents. The relevant spectra exhibited the holistic chemical compositions and variations. Flavonoids, fatty acids and sugars were found to be the main chemical components. Characteristic peak positions, intensities and shapes derived from FT-IR, SD-IR and 2D-IR spectra provided valuable information for sample discrimination. Principal component analysis (PCA) of spectral differences was performed to illustrate the objective identification. Results showed that the species and their extracts can be clearly distinguished. Thus, a quick, precise and effective tri-step IR spectroscopy combined with PCA can be applied to identify and discriminate medicinal materials and their extracts in TM research.

Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy

NASA Astrophysics Data System (ADS)

Zhu, Ying; Tan, Tuck Lee

2016-04-01

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects.

Rapid analysis of microbial systems using vibrational spectroscopy and supervised learning methods: application to the discrimination between methicillin-resistant and methicillin-susceptible Staphy

NASA Astrophysics Data System (ADS)

Goodacre, Royston; Rooney, Paul J.; Kell, Douglas B.

1998-04-01

FTIR spectra were obtained from 15 methicillin-resistant and 22 methicillin-susceptible Staphylococcus aureus strains using our DRASTIC approach. Cluster analysis showed that the major source of variation between the IR spectra was not due to their resistance or susceptibility to methicillin; indeed early studies suing pyrolysis mass spectrometry had shown that this unsupervised analysis gave information on the phage group of the bacteria. By contrast, artificial neural networks, based on a supervised learning, could be trained to recognize those aspects of the IR spectra which differentiated methicillin-resistant from methicillin- susceptible strains. These results give the first demonstration that the combination of FTIR with neural networks can provide a very rapid and accurate antibiotic susceptibility testing technique.

Noncontact discrimination of animal and human blood with vacuum blood vessel and factors affect the discrimination

NASA Astrophysics Data System (ADS)

Zhang, Linna; Zhang, Shengzhao; Sun, Meixiu; Li, Hongxiao; Li, Yingxin; Fu, Zhigang; Guan, Yang; Li, Gang; Lin, Ling

2017-03-01

Discrimination of human and nonhuman blood is crucial for import-export ports and inspection and quarantine departments. Current methods are usually destructive, complicated and time-consuming. We had previously demonstrated that visible diffuse reflectance spectroscopy combining PLS-DA method can successfully realize human blood discrimination. In that research, the spectra were measured with the fiber probe under the surface of blood samples. However, open sampling may pollute the blood samples. Virulence factors in blood samples can also endanger inspectors. In this paper, we explored the classification effect with the blood samples measured in the original containers-vacuum blood vessel. Furthermore, we studied the impact of different conditions of blood samples, such as coagulation and hemolysis, on the prediction ability of the discrimination model. The calibration model built with blood samples in different conditions displayed a satisfactory prediction result. This research demonstrated that visible and near-infrared diffuse reflectance spectroscopy method was potential for noncontact discrimination of human blood.

Effect of Sample Preparation on the Discrimination of Bacterial Isolates Cultured in Liquid Nutrient Media Using Laser-Induced Breakdown Spectroscopy (LIBS).

PubMed

Gamble, Gary R; Park, Bosoon; Yoon, Seung-Chul; Lawrence, Kurt C

2016-03-01

Laser-induced breakdown spectroscopy (LIBS) is used as the basis for discrimination between two genera of gram-negative bacteria and two genera of gram-positive bacteria representing pathogenic threats commonly found in poultry processing rinse waters. Because LIBS-based discrimination relies primarily upon the relative proportions of inorganic cell components including Na, K, Mg, and Ca, this study aims to determine the effects of trace mineral content and pH found in the water source used to isolate the bacteria upon the reliability of the resulting discriminant analysis. All four genera were cultured using tryptic soy agar (TSA) as the nutrient medium, and were grown under identical environmental conditions. The only variable introduced is the source water used to isolate the cultured bacteria. Cultures of each bacterium were produced using deionized (DI) water under two atmosphere conditions, reverse osmosis (RO) water, tap water, phosphate buffered saline (PBS) water, and TRIS buffered water. After 3 days of culture growth, the bacteria were centrifuged and washed three times in the same water source. Bacteria were then freeze dried, mixed with microcrystalline cellulose, and a pellet was made for LIBS analysis. Principal component analysis (PCA) was used to extract related variations in LIBS spectral data among the four bacteria genera and six water types used to isolate the bacteria, and Mahalanobis discriminant analysis (MDA) was used for classification. Results indicate not only that the four genera can be discriminated from each other in each water type, but that each genus can be discriminated by water type used for isolation. It is concluded that in order for LIBS to be a reliable and repeatable method for discrimination of bacteria grown in liquid nutrient media, care must be taken to insure that the water source used in purification of the culture be precisely controlled regarding pH, ionic strength, and proportionate amounts of mineral cations present. © The Author(s) 2016.

Ethnicity- and sex-based discrimination and the maintenance of self-esteem.

PubMed

Lönnqvist, Jan-Erik; Hennig-Schmidt, Heike; Walkowitz, Gari

2015-01-01

The psychological underpinnings of labor market discrimination were investigated by having participants from Israel, the West Bank and Germany (N = 205) act as employers in a stylized employment task in which they ranked, set wages, and imposed a minimum effort level on applicants. State self-esteem was measured before and after the employment task, in which applicant ethnicity and sex were salient. The applicants were real people and all behavior was monetarily incentivized. Supporting the full self-esteem hypothesis of the social identity approach, low self-esteem in women was associated with assigning higher wages to women than to men, and such behavior was related to the maintenance of self-esteem. The narrower hypothesis that successful intergroup discrimination serves to protect self-esteem received broader support. Across all participants, both ethnicity- and sex-based discrimination of out-groups were associated with the maintenance of self-esteem, with the former showing a stronger association than the latter.

Crop/weed discrimination using near-infrared reflectance spectroscopy (NIRS)

NASA Astrophysics Data System (ADS)

Zhang, Yun; He, Yong

2006-09-01

The traditional uniform herbicide application often results in an over chemical residues on soil, crop plants and agriculture produce, which have imperiled the environment and food security. Near-infrared reflectance spectroscopy (NIRS) offers a promising means for weed detection and site-specific herbicide application. In laboratory, a total of 90 samples (30 for each species) of the detached leaves of two weeds, i.e., threeseeded mercury (Acalypha australis L.) and fourleafed duckweed (Marsilea quadrfolia L.), and one crop soybean (Glycine max) was investigated for NIRS on 325- 1075 nm using a field spectroradiometer. 20 absorbance samples of each species after pretreatment were exported and the lacked Y variables were assigned independent values for partial least squares (PLS) analysis. During the combined principle component analysis (PCA) on 400-1000 nm, the PC1 and PC2 could together explain over 91% of the total variance and detect the three plant species with 98.3% accuracy. The full-cross validation results of PLS, i.e., standard error of prediction (SEP) 0.247, correlation coefficient (r) 0.954 and root mean square error of prediction (RMSEP) 0.245, indicated an optimum model for weed identification. By predicting the remaining 10 samples of each species in the PLS model, the results with deviation presented a 100% crop/weed detection rate. Thus, it could be concluded that PLS was an available alternative of for qualitative weed discrimination on NTRS.

[Study on discrimination of varieties of fire resistive coating for steel structure based on near-infrared spectroscopy].

PubMed

Xue, Gang; Song, Wen-qi; Li, Shu-chao

2015-01-01

In order to achieve the rapid identification of fire resistive coating for steel structure of different brands in circulating, a new method for the fast discrimination of varieties of fire resistive coating for steel structure by means of near infrared spectroscopy was proposed. The raster scanning near infrared spectroscopy instrument and near infrared diffuse reflectance spectroscopy were applied to collect the spectral curve of different brands of fire resistive coating for steel structure and the spectral data were preprocessed with standard normal variate transformation(standard normal variate transformation, SNV) and Norris second derivative. The principal component analysis (principal component analysis, PCA)was used to near infrared spectra for cluster analysis. The analysis results showed that the cumulate reliabilities of PC1 to PC5 were 99. 791%. The 3-dimentional plot was drawn with the scores of PC1, PC2 and PC3 X 10, which appeared to provide the best clustering of the varieties of fire resistive coating for steel structure. A total of 150 fire resistive coating samples were divided into calibration set and validation set randomly, the calibration set had 125 samples with 25 samples of each variety, and the validation set had 25 samples with 5 samples of each variety. According to the principal component scores of unknown samples, Mahalanobis distance values between each variety and unknown samples were calculated to realize the discrimination of different varieties. The qualitative analysis model for external verification of unknown samples is a 10% recognition ration. The results demonstrated that this identification method can be used as a rapid, accurate method to identify the classification of fire resistive coating for steel structure and provide technical reference for market regulation.

Alternative method to trace sediment sources in a subtropical rural catchment of southern Brazil by using near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Tiecher, Tales; Caner, Laurent; Gomes Minella, Jean Paolo; Henrique Ciotti, Lucas; Antônio Bender, Marcos; dos Santos Rheinheimer, Danilo

2014-05-01

Conventional fingerprinting methods based on geochemical composition still require a time-consuming and critical preliminary sample preparation. Thus, fingerprinting characteristics that can be measured in a rapid and cheap way requiring a minimal sample preparation, such as spectroscopy methods, should be used. The present study aimed to evaluate the sediment sources contribution in a rural catchment by using conventional method based on geochemical composition and on an alternative method based on near-infrared spectroscopy. This study was carried out in a rural catchment with an area of 1,19 km2 located in southern Brazil. The sediment sources evaluated were crop fields (n=20), unpaved roads (n=10) and stream channels (n=10). Thirty suspended sediment samples were collected from eight significant storm runoff events between 2009 and 2011. Sources and sediment samples were dried at 50oC and sieved at 63 µm. The total concentration of Ag, As, B, Ba, Be, Ca, Cd, Co, Cr, Cu, Fe, K, La, Li, Mg, Mn, Mo, Na, Ni, P, Pb, Sb, Se, Sr, Ti, Tl, V and Zn were estimated by ICP-OES after microwave assisted digestion with concentrated HNO3 and HCl. Total organic carbon (TOC) was estimated by wet oxidation with K2Cr2O7 and H2SO4. The near-infrared spectra scan range was 4000 to 10000 cm-1 at a resolution of 2 cm-1, with 100 co added scans per spectrum. The steps used in the conventional method were: i) tracer selection based on Kruskal-Wallis test, ii) selection of the best set of tracers using discriminant analyses and finally iii) the use of a mixed linear model to calculate the sediment sources contribution. The steps used in the alternative method were i) principal component analyses to reduce the number of variables, ii) discriminant analyses to determine the tracer potential of the near-infrared spectroscopy, and finally iii) the use of past least square based on 48 mixtures of the sediment sources in various weight proportions to calculate the sediment sources contribution. Both conventional and alternative methods were capable to discriminate 100% of the sediment sources. Conventional fingerprinting method provided a sediment sources contribution of 33±19% by crop fields, 25±13% by unpaved roads and 42±19% by stream channels. The contribution of sediment sources obtained by alternative fingerprinting method using near-infrared spectroscopy was 71±22% of crop fields, 21±12% of unpaved roads and 14±19% of stream channels. No correlation was observed between source contribution assessed by the two methods. Notwithstanding, the average contribution of the unpaved roads was similar by both methods. The highest difference in the average contribution of crop fields and stream channels estimated by the two methods was due to similar organic matter content of these two sediment sources which hampers their discrimination by assessing the near-infrared spectra, where much of the bands are highly correlated with the TOC levels. Efforts should be taken to try to combine both the geochemical composition and near-infrared spectroscopy information on a single estimative of the sediment sources contribution.

MR-perfusion (MRP) and diffusion-weighted imaging (DWI) in prostate cancer: quantitative and model-based gadobenate dimeglumine MRP parameters in detection of prostate cancer.

PubMed

Scherr, M K; Seitz, M; Müller-Lisse, U G; Ingrisch, M; Reiser, M F; Müller-Lisse, U L

2010-12-01

Various MR methods, including MR-spectroscopy (MRS), dynamic, contrast-enhanced MRI (DCE-MRI), and diffusion-weighted imaging (DWI) have been applied to improve test quality of standard MRI of the prostate. To determine if quantitative, model-based MR-perfusion (MRP) with gadobenate dimeglumine (Gd-BOPTA) discriminates between prostate cancer, benign tissue, and transitional zone (TZ) tissue. 27 patients (age, 65±4 years; PSA 11.0±6.1 ng/ml) with clinical suspicion of prostate cancer underwent standard MRI, 3D MR-spectroscopy (MRS), and MRP with Gd-BOPTA. Based on results of combined MRI/MRS and subsequent guided prostate biopsy alone (17/27), biopsy and radical prostatectomy (9/27), or sufficient negative follow-up (7/27), maps of model-free, deconvolution-based mean transit time (dMTT) were generated for 29 benign regions (bROIs), 14 cancer regions (cROIs), and 18 regions of transitional zone (tzROIs). Applying a 2-compartment exchange model, quantitative perfusion analysis was performed including as parameters: plasma flow (PF), plasma volume (PV), plasma mean transit time (PMTT), extraction flow (EFL), extraction fraction (EFR), interstitial volume (IV) and interstitial mean transit time (IMTT). Two-sided T-tests (significance level p<0.05) discriminated bROIs vs. cROIs and cROIs vs. tzROIs, respectively. PMTT discriminated best between bROIs (11.8±3.0 s) and cROIs (24.3±9.6 s) (p<0.0001), while PF, PV, PS, EFR, IV, IMTT also differed significantly (p 0.00002-0.0136). Discrimination between cROIs and tzROIs was insignificant for all parameters except PV (14.3±2.5 ml vs. 17.6±2.6 ml, p<0.05). Besides MRI, MRS and DWI quantitative, 2-compartment MRP with Gd-BOPTA discriminates between prostate cancer and benign tissue with several parameters. However, distinction of prostate cancer and TZ does not appear to be reliable. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

An effective biometric discretization approach to extract highly discriminative, informative, and privacy-protective binary representation

NASA Astrophysics Data System (ADS)

Lim, Meng-Hui; Teoh, Andrew Beng Jin

2011-12-01

Biometric discretization derives a binary string for each user based on an ordered set of biometric features. This representative string ought to be discriminative, informative, and privacy protective when it is employed as a cryptographic key in various security applications upon error correction. However, it is commonly believed that satisfying the first and the second criteria simultaneously is not feasible, and a tradeoff between them is always definite. In this article, we propose an effective fixed bit allocation-based discretization approach which involves discriminative feature extraction, discriminative feature selection, unsupervised quantization (quantization that does not utilize class information), and linearly separable subcode (LSSC)-based encoding to fulfill all the ideal properties of a binary representation extracted for cryptographic applications. In addition, we examine a number of discriminative feature-selection measures for discretization and identify the proper way of setting an important feature-selection parameter. Encouraging experimental results vindicate the feasibility of our approach.

Fast classification of hazelnut cultivars through portable infrared spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Manfredi, Marcello; Robotti, Elisa; Quasso, Fabio; Mazzucco, Eleonora; Calabrese, Giorgio; Marengo, Emilio

2018-01-01

The authentication and traceability of hazelnuts is very important for both the consumer and the food industry, to safeguard the protected varieties and the food quality. This study investigates the use of a portable FTIR spectrometer coupled to multivariate statistical analysis for the classification of raw hazelnuts. The method discriminates hazelnuts from different origins/cultivars based on differences of the signal intensities of their IR spectra. The multivariate classification methods, namely principal component analysis (PCA) followed by linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA), with or without variable selection, allowed a very good discrimination among the groups, with PLS-DA coupled to variable selection providing the best results. Due to the fast analysis, high sensitivity, simplicity and no sample preparation, the proposed analytical methodology could be successfully used to verify the cultivar of hazelnuts, and the analysis can be performed quickly and directly on site.

NIR spectroscopy as a tool for discriminating between lichens exposed to air pollution.

PubMed

Casale, Monica; Bagnasco, Lucia; Giordani, Paolo; Mariotti, Mauro Giorgio; Malaspina, Paola

2015-09-01

Lichens are used as biomonitors of air pollution because they are extremely sensitive to the presence of substances that alter atmospheric composition. Fifty-one thalli of two different varieties of Pseudevernia furfuracea (var. furfuracea and var. ceratea) were collected far from local sources of air pollution. Twenty-six of these thalli were then exposed to the air for one month in the industrial port of Genoa, which has high levels of environmental pollution. The possibility of using Near-infrared spectroscopy (NIRS) for generating a 'fingerprint' of lichens was investigated. Chemometric methods were successfully applied to discriminate between samples from polluted and non-polluted areas. In particular, Principal Component Analysis (PCA) was applied as a multivariate display method on the NIR spectra to visualise the data structure. This showed that the difference between samples of different varieties was not significant in comparison to the difference between samples exposed to different levels of environmental pollution. Then Linear Discriminant Analysis (LDA) was carried out to discriminate between lichens based on their exposure to pollutants. The distinction between control samples (not exposed) and samples exposed to the air in the industrial port of Genoa was evaluated. On average, 95.2% of samples were correctly classified, 93.0% of total internal prediction (5 cross-validation groups) and 100.0% of external prediction (on the test set) was achieved. Copyright © 2015 Elsevier Ltd. All rights reserved.

Discriminating model for skin cancer diagnosis in vivo through Raman spectroscopy

NASA Astrophysics Data System (ADS)

Silveira, Fabrício Luiz; Pacheco, Marcos Tadeu T.; Bodanese, Benito; Zângaro, Renato Amaro; Silveira, Landulfo

2013-03-01

This work aimed the development of a discriminating model, using Raman spectroscopy, based on the estimated concentration of biochemical components presented in skin, for in vivo diagnosis. Raman spectra were collected in patients who underwent excision surgery of suspicious lesions at the lesion site and at a normal circumjacent site. It has been estimated the relative amount of selected biochemical compounds presented in skin. The Raman spectra of normal and malignant (basal cell carcinoma - BCC and squamous cell carcinoma - SCC) skin are quite similar, with some spectral differences in the regions of lipids, nucleic acids, and hemoglobin. Some biochemicals showed statistically significant differences among N, BCC and SCC, such as elastin, ceramide, melanin, nucleid acid, actin and phenylalanine. Elastin and ceramide presented significant differences between N and BCC, melanin, DNA and actin presented significant differences between N and BCC and between N and SCC, being melanin and DNA decreased in neoplasias, in contrast with actin, that increased in neoplasias. Concentration of phenylalanine was significantly increased for SCC compared to N and BCC. The relative concentration of melanin, DNA and phenylalanine showed sensitivity, specificity and accuracy of about 81%, 65% and 60%, respectively, using Mahalanobis distance as a discriminator. This model is being incorporated to a Raman system with automated data collection and processing that could be used for a future in vivo, real time discrimination algorithm.

Fourier transform infrared spectroscopy and chemometrics for the characterization and discrimination of writing/photocopier paper types: Application in forensic document examinations.

PubMed

Kumar, Raj; Kumar, Vinay; Sharma, Vishal

2017-01-05

The aim of the present work is to explore the non-destructive application of ATR-FTIR technique for characterization and discrimination of paper samples which could be helpful to give forensic aid in resolving legal cases. Twenty-four types of paper brands were purchased from local market in and around Chandigarh, India. All the paper samples were subjected to ATR-FTIR analysis from 400 to 4000cm(-1) wavenumber range. The qualitative feature and Chemometrics of the obtained spectral data are used for characterization and discrimination. Characterization is achieved by matching the peaks with standards of cellulose and inorganic fillers, a usual constituents of paper. Three different regions of IR, i.e. 400-2000cm(-1), 2000-4000cm(-1) and 400-4000cm(-1) were selected for differentiation by Chemometrics analysis. The discrimination is achieved on the basis of three principal components, i.e. PC 1, PC 2 and PC 3. It is observed that maximum discrimination was procured in the wave number range of i.e. 2000-4000cm(-1). Discriminating power was calculated on the basis of qualitative features as well, and it is found that the discrimination of paper samples was better achieved by Chemometrics analysis rather than qualitative features. The discriminating power by Chemometrics is 99.64% and which is larger as ever achieved by any group for present number of samples. The present result confirms that this study will be highly useful in forensic document examination work in the legal cases, where the authenticity of the document is challenged. The results are completely analytical and, therefore, overcome the problem encounter in traditional routine light/radiation scanning methods which are still in practice by various questioned document laboratories. Copyright © 2016 Elsevier B.V. All rights reserved.

Artificial nose, NIR and UV-visible spectroscopy for the characterisation of the PDO Chianti Classico olive oil.

PubMed

Forina, M; Oliveri, P; Bagnasco, L; Simonetti, R; Casolino, M C; Nizzi Grifi, F; Casale, M

2015-11-01

An authentication study of the Italian PDO (Protected Designation of Origin) olive oil Chianti Classico, based on artificial nose, near-infrared and UV-visible spectroscopy, with a set of samples representative of the whole Chianti Classico production area and a considerable number of samples from other Italian PDO regions was performed. The signals provided by the three analytical techniques were used both individually and jointly, after fusion of the respective variables, in order to build a model for the Chianti Classico PDO olive oil. Different signal pre-treatments were performed in order to investigate their importance and their effects in enhancing and extracting information from experimental data, correcting backgrounds or removing baseline variations. Stepwise-Linear Discriminant Analysis (STEP-LDA) was used as a feature selection technique and, afterward, Linear Discriminant Analysis (LDA) and the class-modelling technique Quadratic Discriminant Analysis-UNEQual dispersed classes (QDA-UNEQ) were applied to sub-sets of selected variables, in order to obtain efficient models capable of characterising the extra virgin olive oils produced in the Chianti Classico PDO area. Copyright © 2015 Elsevier B.V. All rights reserved.

Spectral region optimization for Raman-based optical biopsy of inflammatory lesions.

PubMed

de Carvalho, Luis Felipe das Chagas E Silva; Bitar, Renata Andrade; Arisawa, Emília Angela Loschiavo; Brandão, Adriana Aigotti Haberbeck; Honório, Kathia Maria; Cabral, Luiz Antônio Guimarães; Martin, Airton Abrahão; Martinho, Herculano da Silva; Almeida, Janete Dias

2010-08-01

The biochemical alterations between inflammatory fibrous hyperplasia (IFH) and normal tissues of buccal mucosa were probed by using the FT-Raman spectroscopy technique. The aim was to find the minimal set of Raman bands that would furnish the best discrimination. Raman-based optical biopsy is a widely recognized potential technique for noninvasive real-time diagnosis. However, few studies had been devoted to the discrimination of very common subtle or early pathologic states as inflammatory processes that are always present on, for example, cancer lesion borders. Seventy spectra of IFH from 14 patients were compared with 30 spectra of normal tissues from six patients. The statistical analysis was performed with principal components analysis and soft independent modeling class analogy cross-validated, leave-one-out methods. Bands close to 574, 1,100, 1,250 to 1,350, and 1,500 cm(-1) (mainly amino acids and collagen bands) showed the main intragroup variations that are due to the acanthosis process in the IFH epithelium. The 1,200 (C-C aromatic/DNA), 1,350 (CH(2) bending/collagen 1), and 1,730 cm(-1) (collagen III) regions presented the main intergroup variations. This finding was interpreted as originating in an extracellular matrix-degeneration process occurring in the inflammatory tissues. The statistical analysis results indicated that the best discrimination capability (sensitivity of 95% and specificity of 100%) was found by using the 530-580 cm(-1) spectral region. The existence of this narrow spectral window enabling normal and inflammatory diagnosis also had useful implications for an in vivo dispersive Raman setup for clinical applications.

Analysis of Chuanxiong Rhizoma and its active components by Fourier transform infrared spectroscopy combined with two-dimensional correlation infrared spectroscopy.

PubMed

Guo, Yizhen; Lv, Beiran; Wang, Jingjuan; Liu, Yang; Sun, Suqin; Xiao, Yao; Lu, Lina; Xiang, Li; Yang, Yanfang; Qu, Lei; Meng, Qinghong

2016-01-15

As complicated mixture systems, active components of Chuanxiong Rhizoma are very difficult to identify and discriminate. In this paper, the macroscopic IR fingerprint method including Fourier transform infrared spectroscopy (FT-IR), the second derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2DCOS-IR), was applied to study and identify Chuanxiong raw materials and its different segmented production of HPD-100 macroporous resin. Chuanxiong Rhizoma is rich in sucrose. In the FT-IR spectra, water eluate is more similar to sucrose than the powder and the decoction. Their second derivative spectra amplified the differences and revealed the potentially characteristic IR absorption bands and combined with the correlation coefficient, concluding that 50% ethanol eluate had more ligustilide than other eluates. Finally, it can be found from 2DCOS-IR spectra that proteins were extracted by ethanol from Chuanxiong decoction by HPD-100 macroporous resin. It was demonstrated that the above three-step infrared spectroscopy could be applicable for quick, non-destructive and effective analysis and identification of very complicated and similar mixture systems of traditional Chinese medicines. Copyright © 2015 Elsevier B.V. All rights reserved.

Exploring Geographical Differentiation of the Hoelen Medicinal Mushroom, Wolfiporia extensa (Agaricomycetes), Using Fourier-Transform Infrared Spectroscopy Combined with Multivariate Analysis.

PubMed

Li, Yan; Zhang, Ji; Zhao, Yanli; Liu, Honggao; Wang, Yuanzhong; Jin, Hang

2016-01-01

In this study the geographical differentiation of dried sclerotia of the medicinal mushroom Wolfiporia extensa, obtained from different regions in Yunnan Province, China, was explored using Fourier-transform infrared (FT-IR) spectroscopy coupled with multivariate data analysis. The FT-IR spectra of 97 samples were obtained for wave numbers ranging from 4000 to 400 cm-1. Then, the fingerprint region of 1800-600 cm-1 of the FT-IR spectrum, rather than the full spectrum, was analyzed. Different pretreatments were applied on the spectra, and a discriminant analysis model based on the Mahalanobis distance was developed to select an optimal pretreatment combination. Two unsupervised pattern recognition procedures- principal component analysis and hierarchical cluster analysis-were applied to enhance the authenticity of discrimination of the specimens. The results showed that excellent classification could be obtained after optimizing spectral pretreatment. The tested samples were successfully discriminated according to their geographical locations. The chemical properties of dried sclerotia of W. extensa were clearly dependent on the mushroom's geographical origins. Furthermore, an interesting finding implied that the elevations of collection areas may have effects on the chemical components of wild W. extensa sclerotia. Overall, this study highlights the feasibility of FT-IR spectroscopy combined with multivariate data analysis in particular for exploring the distinction of different regional W. extensa sclerotia samples. This research could also serve as a basis for the exploitation and utilization of medicinal mushrooms.

Standoff detection of chemical and biological threats using laser-induced breakdown spectroscopy.

PubMed

Gottfried, Jennifer L; De Lucia, Frank C; Munson, Chase A; Miziolek, Andrzej W

2008-04-01

Laser-induced breakdown spectroscopy (LIBS) is a promising technique for real-time chemical and biological warfare agent detection in the field. We have demonstrated the detection and discrimination of the biological warfare agent surrogates Bacillus subtilis (BG) (2% false negatives, 0% false positives) and ovalbumin (0% false negatives, 1% false positives) at 20 meters using standoff laser-induced breakdown spectroscopy (ST-LIBS) and linear correlation. Unknown interferent samples (not included in the model), samples on different substrates, and mixtures of BG and Arizona road dust have been classified with reasonable success using partial least squares discriminant analysis (PLS-DA). A few of the samples tested such as the soot (not included in the model) and the 25% BG:75% dust mixture resulted in a significant number of false positives or false negatives, respectively. Our preliminary results indicate that while LIBS is able to discriminate biomaterials with similar elemental compositions at standoff distances based on differences in key intensity ratios, further work is needed to reduce the number of false positives/negatives by refining the PLS-DA model to include a sufficient range of material classes and carefully selecting a detection threshold. In addition, we have demonstrated that LIBS can distinguish five different organophosphate nerve agent simulants at 20 meters, despite their similar stoichiometric formulas. Finally, a combined PLS-DA model for chemical, biological, and explosives detection using a single ST-LIBS sensor has been developed in order to demonstrate the potential of standoff LIBS for universal hazardous materials detection.

Discrimination of premalignant conditions of oral cancer using Raman spectroscopy of urinary metabolites

NASA Astrophysics Data System (ADS)

Elumalai, Brindha; Rajasekaran, Ramu; Aruna, Prakasarao; Koteeswaran, Dornadula; Ganesan, Singaravelu

2015-03-01

Oral cancers are considered to be one of the most commonly occurring malignancy worldwide. Over 70% of the cases report to the doctor only in advanced stages of the disease, resulting in poor survival rates. Hence it is necessary to detect the disease at the earliest which may increase the five year survival rate up to 90%. Among various optical spectroscopic techniques, Raman spectroscopy has been emerged as a tool in identifying several diseased conditions, including oral cancers. Around 30 - 80% of the malignancies of the oral cavity arise from premalignant lesions. Hence, understanding the molecular/spectral differences at the premalignant stage may help in identifying the cancer at the earliest and increase patient's survival rate. Among various bio-fluids such as blood, urine and saliva, urine is considered as one of the diagnostically potential bio-fluids, as it has many metabolites. The distribution and the physiochemical properties of the urinary metabolites may vary due to the changes associated with the pathologic conditions. The present study is aimed to characterize the urine of 70 healthy subjects and 51 pre-malignant patients using Raman spectroscopy under 785nm excitation, to know the molecular/spectral differences between healthy subjects and premalignant conditions of oral malignancy. Principal component analysis based Linear discriminant analysis were also made to find the statistical significance and the present technique yields the sensitivity and specificity of 86.3% and 92.9% with an overall accuracy of 90.9% in the discrimination of premalignant conditions from healthy subjects urine.

[Discrimination of varieties of brake fluid using visual-near infrared spectra].

PubMed

Jiang, Lu-lu; Tan, Li-hong; Qiu, Zheng-jun; Lu, Jiang-feng; He, Yong

2008-06-01

A new method was developed to fast discriminate brands of brake fluid by means of visual-near infrared spectroscopy. Five different brands of brake fluid were analyzed using a handheld near infrared spectrograph, manufactured by ASD Company, and 60 samples were gotten from each brand of brake fluid. The samples data were pretreated using average smoothing and standard normal variable method, and then analyzed using principal component analysis (PCA). A 2-dimensional plot was drawn based on the first and the second principal components, and the plot indicated that the clustering characteristic of different brake fluid is distinct. The foregoing 6 principal components were taken as input variable, and the band of brake fluid as output variable to build the discriminate model by stepwise discriminant analysis method. Two hundred twenty five samples selected randomly were used to create the model, and the rest 75 samples to verify the model. The result showed that the distinguishing rate was 94.67%, indicating that the method proposed in this paper has good performance in classification and discrimination. It provides a new way to fast discriminate different brands of brake fluid.

Neural Correlates of Infant Accent Discrimination: An fNIRS Study

ERIC Educational Resources Information Center

Cristia, Alejandrina; Minagawa-Kawai, Yasuyo; Egorova, Natalia; Gervain, Judit; Filippin, Luca; Cabrol, Dominique; Dupoux, Emmanuel

2014-01-01

The present study investigated the neural correlates of infant discrimination of very similar linguistic varieties (Quebecois and Parisian French) using functional Near InfraRed Spectroscopy. In line with previous behavioral and electrophysiological data, there was no evidence that 3-month-olds discriminated the two regional accents, whereas…

[The NIR spectra based variety discrimination for single soybean seed].

PubMed

Zhu, Da-Zhou; Wang, Kun; Zhou, Guang-Hua; Hou, Rui-Feng; Wang, Cheng

2010-12-01

With the development of soybean producing and processing, the quality breeding becomes more and more important for soybean breeders. Traditional sampling detection methods for soybean quality need to destroy the seed, and does not satisfy the requirement of earlier generation materials sieving for breeding. Near infrared (NIR) spectroscopy has been widely used for soybean quality detection. However, all these applications were referred to mass samples, and they were not suitable for little or single seed detection in breeding procedure. In the present study, the acousto--optic tunable filter (AOTF) NIR spectroscopy was used to measure the single soybean seed. Two varieties of soybean were measured, which contained 60 KENJIANDOU43 seeds and 60 ZHONGHUANG13 seeds. The results showed that NIR spectra combined with soft independent modeling of class analogy (SIMCA) could accurately discriminate the soybean varieties. The classification accuracy for KENJIANDOU43 seeds and ZHONGHUANG13 was 100%. The spectra of single soybean seed were measured at different positions, and it showed that the seed shape has significant influence on the measurement of spectra, therefore, the key point for single seed measurement was how to accurately acquire the spectra and keep their representativeness. The spectra for soybeans with glossy surface had high repeatability, while the spectra of seeds with external defects had significant difference for several measurements. For the fast sieving of earlier generation materials in breeding, one could firstly eliminate the seeds with external defects, then apply NIR spectra for internal quality detection, and in this way the influence of seed shape and external defects could be reduced.

Resonance Raman Spectroscopy of human brain metastasis of lung cancer analyzed by blind source separation

NASA Astrophysics Data System (ADS)

Zhou, Yan; Liu, Cheng-Hui; Pu, Yang; Cheng, Gangge; Yu, Xinguang; Zhou, Lixin; Lin, Dongmei; Zhu, Ke; Alfano, Robert R.

2017-02-01

Resonance Raman (RR) spectroscopy offers a novel Optical Biopsy method in cancer discrimination by a means of enhancement in Raman scattering. It is widely acknowledged that the RR spectrum of tissue is a superposition of spectra of various key building block molecules. In this study, the Resonance Raman (RR) spectra of human metastasis of lung cancerous and normal brain tissues excited by a visible selected wavelength at 532 nm are used to explore spectral changes caused by the tumor evolution. The potential application of RR spectra human brain metastasis of lung cancer was investigated by Blind Source Separation such as Principal Component Analysis (PCA). PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components (PCs). The results show significant RR spectra difference between human metastasis of lung cancerous and normal brain tissues analyzed by PCA. To evaluate the efficacy of for cancer detection, a linear discriminant analysis (LDA) classifier is utilized to calculate the sensitivity, and specificity and the receiver operating characteristic (ROC) curves are used to evaluate the performance of this criterion. Excellent sensitivity of 0.97, specificity (close to 1.00) and the Area Under ROC Curve (AUC) of 0.99 values are achieved under best optimal circumstance. This research demonstrates that RR spectroscopy is effective for detecting changes of tissues due to the development of brain metastasis of lung cancer. RR spectroscopy analyzed by blind source separation may have potential to be a new armamentarium.

Optical spectroscopic analysis for the discrimination of extra-virgin olive-oil (Conference Presentation)

NASA Astrophysics Data System (ADS)

McReynolds, Naomi; Auñón Garcia, Juan M.; Guengerich, Zoe; Smith, Terry K.; Dholakia, Kishan

2017-02-01

We present an optical spectroscopic technique, making use of both Raman signals and fluorescence spectroscopy, for the identification of five brands of commercially available extra-virgin olive-oil (EVOO). We demonstrate our technique on both a `bulk-optics' free-space system and a compact device. Using the compact device, which is capable of recording both Raman and fluorescence signals, we achieved an average sensitivity and specificity of 98.4% and 99.6% for discrimination, respectively. Our approach demonstrates that both Raman and fluorescence spectroscopy can be used for portable discrimination of EVOOs which obviates the need to use centralised laboratories and opens up the prospect of in-field testing. This technique may enable detection of EVOO that has undergone counterfeiting or adulteration. One of the main challenges facing Raman spectroscopy for use in quality control of EVOOs is that the oxidation of EVOO, which naturally occurs due to aging, causes shifts in Raman spectra with time, which implies regular retraining would be necessary. We present a potential method of analysis to minimize the effect that aging has on discrimination efficiency; we show that by discarding the first principal component, which contains information on the variations due to oxidation, we can improve discrimination efficiency thus improving the robustness of our technique.

Metabonomics uncovers a reversible proatherogenic lipid profile during infliximab therapy of inflammatory bowel disease.

PubMed

Bjerrum, Jacob Tveiten; Steenholdt, Casper; Ainsworth, Mark; Nielsen, Ole Haagen; Reed, Michelle Ac; Atkins, Karen; Günther, Ulrich Leonhard; Hao, Fuhua; Wang, Yulan

2017-10-16

One-third of inflammatory bowel disease (IBD) patients show no response to infliximab (IFX) induction therapy, and approximately half of patients responding become unresponsive over time. Thus, identification of potential treatment response biomarkers are of great clinical significance. This study employs spectroscopy-based metabolic profiling of serum from patients with IBD treated with IFX and healthy subjects (1) to substantiate the use of spectroscopy as a semi-invasive diagnostic tool, (2) to identify potential biomarkers of treatment response and (3) to characterise the metabolic changes during management of patients with tumour necrosis factor-α inhibitors. Successive serum samples collected during IFX induction treatment (weeks 0, 2, 6 and 14) from 87 IBD patients and 37 controls were analysed by 1 H nuclear magnetic resonance (NMR) spectroscopy. Data were analysed with principal components analysis and orthogonal projection to latent structures discriminant analysis using SIMCA-P+ v12 and MATLAB. Metabolic profiles were significantly different between active ulcerative colitis and controls, active Crohn's disease and controls, and quiescent Crohn's disease and controls. Metabolites holding differential power belonged primarily to lipids and phospholipids with proatherogenic characteristics and metabolites in the pyruvate metabolism, suggestive of an intense inflammation-driven energy demand. IBD patients not responding to IFX were identified as a potentially distinct group based on their metabolic profile, although no applicable response biomarkers could be singled out in the current setting. 1 H NMR spectroscopy of serum samples is a powerful semi-invasive diagnostic tool in flaring IBD. With its use, we provide unique insights into the metabolic changes taking place during induction treatment with IFX. Of distinct clinical relevance is the identification of a reversible proatherogenic lipid profile in IBD patients with active disease, which partially explains the increased risk of cardiovascular disease associated with IBD.

Micro-Raman spectroscopy and chemometrical analysis for the distinction of copper phthalocyanine polymorphs in paint layers.

PubMed

Defeyt, C; Van Pevenage, J; Moens, L; Strivay, D; Vandenabeele, P

2013-11-01

In art analysis, copper phthalocyanine (CuPc) is often identified as an important pigment (PB15) in 20th century artworks. Raman spectroscopy is a very valuable technique for the detection of this pigment in paint systems. However, PB15 is used in different polymorphic forms and identification of the polymorph could retrieve information on the production process of the pigment at the moment. Raman spectroscopy, being a molecular spectroscopic method of analysis, is able to discriminate between polymorphs of crystals. However, in the case of PB15, spectral interpretation is not straightforward, and Raman data treatment requires some improvements concerning the PB15 polymorphic discrimination in paints. Here, Raman spectroscopy is combined with chemometrical analysis in order to develop a procedure allowing us to identify the PB15 crystalline structure in painted layers and in artworks. The results obtained by Linear Discriminant Analysis (LDA), using intensity ratios as variables, demonstrate the ability of this procedure to predict the crystalline structure of a PB15 pigment in unknown paint samples. Copyright © 2013 Elsevier B.V. All rights reserved.

Multivariate qualitative analysis of banned additives in food safety using surface enhanced Raman scattering spectroscopy.

PubMed

He, Shixuan; Xie, Wanyi; Zhang, Wei; Zhang, Liqun; Wang, Yunxia; Liu, Xiaoling; Liu, Yulong; Du, Chunlei

2015-02-25

A novel strategy which combines iteratively cubic spline fitting baseline correction method with discriminant partial least squares qualitative analysis is employed to analyze the surface enhanced Raman scattering (SERS) spectroscopy of banned food additives, such as Sudan I dye and Rhodamine B in food, Malachite green residues in aquaculture fish. Multivariate qualitative analysis methods, using the combination of spectra preprocessing iteratively cubic spline fitting (ICSF) baseline correction with principal component analysis (PCA) and discriminant partial least squares (DPLS) classification respectively, are applied to investigate the effectiveness of SERS spectroscopy for predicting the class assignments of unknown banned food additives. PCA cannot be used to predict the class assignments of unknown samples. However, the DPLS classification can discriminate the class assignment of unknown banned additives using the information of differences in relative intensities. The results demonstrate that SERS spectroscopy combined with ICSF baseline correction method and exploratory analysis methodology DPLS classification can be potentially used for distinguishing the banned food additives in field of food safety. Copyright © 2014 Elsevier B.V. All rights reserved.

Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy.

PubMed

Zhu, Ying; Tan, Tuck Lee

2016-04-15

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects. Copyright © 2016 Elsevier B.V. All rights reserved.

Simultaneous determination of fluoxetine and norfluoxetine enantiomers using isotope discrimination mass spectroscopy solution method and its application in the CYP2C9-mediated stereoselective interactions.

PubMed

Yu, Lushan; Wang, Shengjia; Jiang, Huidi; Zhou, Hui; Zeng, Su

2012-05-04

In this study, we developed an LC-MS/MS method based on an isotope discrimination mass spectroscopy solution (IDMSS) technology to simultaneously quantify enantiomers of fluoxetine (FLX) and norfluoxetine (NFLX) in a CYP2C9 incubation mixture. S-FLX and S-NFLX were labeled to form S-FLX-d5 and S-NFLX-d5. The method has several advantages over conventional chiral separation methods, in terms of the analysis period, resolution, and lower limit of quantification. The primary advantage of the method is that the two enantiomers can always be simultaneously determined by mass spectroscopy regardless if they are separated on column or not, owing to which it has high throughput and high sensitivity. The lower limit of quantification (amount on column) is 12.5 and 1.25 pg for FLX and NFLX, respectively. The retention time of FLX, NFLX, and the internal standard is only 1.9 min. The calibration curves were linear over the concentration range of 0.1-100 ng/ml for NFLX and 1-1000 ng/ml for FLX with an accepted reproducible (RSD<10%) and accurate (CV<10%). No significant kinetic isotope effect was found in the metabolism of S-FLX-d5 catalyzed by CYP2C9*1 and CYP2C9*2. The half-maximal inhibitory concentration values between R-FLX and S-FLX catalyzed by CYP2C9*1 and CYP2C9*2 were determined in this study. The inhibitory effects of R- to S-FLX were stronger than those of S- to R-FLX in both CYP2C9*1 and CYP2C9*2. The IDMSS technology is useful for stereoselective study of chiral compound in vitro. Copyright © 2012 Elsevier B.V. All rights reserved.

New methods for time-resolved fluorescence spectroscopy data analysis based on the Laguerre expansion technique--applications in tissue diagnosis.

PubMed

Jo, J A; Marcu, L; Fang, Q; Papaioannou, T; Qiao, J H; Fishbein, M C; Beseth, B; Dorafshar, A H; Reil, T; Baker, D; Freischlag, J

2007-01-01

A new deconvolution method for the analysis of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data is introduced and applied for tissue diagnosis. The intrinsic TR-LIFS decays are expanded on a Laguerre basis, and the computed Laguerre expansion coefficients (LEC) are used to characterize the sample fluorescence emission. The method was applied for the diagnosis of atherosclerotic vulnerable plaques. At a first stage, using a rabbit atherosclerotic model, 73 TR-LIFS in-vivo measurements from the normal and atherosclerotic aorta segments of eight rabbits were taken. The Laguerre deconvolution technique was able to accurately deconvolve the TR-LIFS measurements. More interesting, the LEC reflected the changes in the arterial biochemical composition and provided discrimination of lesions rich in macrophages/foam-cells with high sensitivity (> 85%) and specificity (> 95%). At a second stage, 348 TR-LIFS measurements were obtained from the explanted carotid arteries of 30 patients. Lesions with significant inflammatory cells (macrophages/foam-cells and lymphocytes) were detected with high sensitivity (> 80%) and specificity (> 90%), using LEC-based classifiers. This study has demonstrated the potential of using TR-LIFS information by means of LEC for in vivo tissue diagnosis, and specifically for detecting inflammation in atherosclerotic lesions, a key marker of plaque vulnerability.

Differentiation of the root of Cultivated Ginseng, Mountain Cultivated Ginseng and Mountain Wild Ginseng using FT-IR and two-dimensional correlation IR spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Dan; Li, Yong-Guo; Xu, Hong; Sun, Su-Qin; Wang, Zheng-Tao

2008-07-01

Ginseng is one of the most widely used herbal medicines. Based on the grown environments and the cultivate method, three kinds of ginseng, Cultivated Ginseng (CG), Mountain Cultivated Ginseng (MCG) and Mountain Wild Ginseng (MWG) are classified. A novel and scientific-oriented method was developed and established to discriminate and identify three kinds of ginseng using Fourier transform infrared spectroscopy (FT-IR), secondary derivative IR spectra and two-dimensional correlation infrared spectroscopy (2D-IR). The findings indicated that the relative contents of starch in the CG were more than that in MCG and MWG, while the relative contents of calcium oxalate and lipids in MWG were more than that in CG and MCG, and the relative contents of fatty acid in MCG were more than that in CG and MWG. The hierarchical cluster analysis was applied to data analysis of MWG, CG and MWG, which could be classified successfully. The results demonstrated the macroscopic IR fingerprint method, including FT-IR, secondary derivative IR and 2D-IR, can be applied to discriminate different ginsengs rapidly, effectively and non-destructively.

The discrimination of 72 nitrate, chlorate and perchlorate salts using IR and Raman spectroscopy

NASA Astrophysics Data System (ADS)

Zapata, Félix; García-Ruiz, Carmen

2018-01-01

Inorganic oxidizing energetic salts including nitrates, chlorates and perchlorates are widely used in the manufacture of not only licit pyrotechnic compositions, but also illicit homemade explosive mixtures. Their identification in forensic laboratories is usually accomplished by either capillary electrophoresis or ion chromatography, with the disadvantage of dissociating the salt into its ions. On the contrary, vibrational spectroscopy, including IR and Raman, enables the non-invasive identification of the salt, i.e. avoiding its dissociation. This study focuses on the discrimination of all nitrate, chlorate and perchlorate salts that are commercially available, using both Raman and IR spectroscopy, with the aim of testing whether every salt can be unequivocally identified. Besides the visual spectra comparison by assigning every band with the corresponding molecular vibrational mode, a statistical analysis based on Pearson correlation was performed to ensure an objective identification, either using Raman, IR or both. Positively, 25 salts (out of 72) were unequivocally identified using Raman, 30 salts when using IR and 44 when combining both techniques. Negatively, some salts were undistinguishable even using both techniques demonstrating there are some salts that provide very similar Raman and IR spectra.

Nondestructive identification for red ink entries of seals by Raman and Fourier transform infrared spectrometry.

PubMed

Wang, Xiang-Feng; Yu, Jing; Zhang, Ai-Lan; Zhou, Dai-Wei; Xie, Meng-Xia

2012-11-01

Determination of the red ink entries of seals on documents can provide valuable evidences for solving related crimes, distinguishing the truth of artworks, and so establishment of nondestructive approaches would play a key role in forensic analysis and related aspects. Raman and FT-IR spectroscopy have been applied for analyzing 105 kinds of red ink entries on documents. The dye components of the ink entries were identified by FT-Raman and confocal Raman microspectroscopy, and then the ink entries were classified into four groups based on these dye components. The ink entries were further discriminated by their FT-IR spectra according to adsorption peaks of the main components, the relative intensities of the characteristic bands and the profiles of the spectra. The results showed that 70 ink entries out of 105 have been individually identified and the remaining 35 ink entries can be divided into 13 subclasses. Combination of Raman and FT-IR spectroscopic methods can provide a powerful nondestructive discriminating tool for identification of the red ink entries of seals on papers. These approaches would have potential application in archeology, art and forensic science. Copyright © 2012 Elsevier B.V. All rights reserved.

Combining vibrational biomolecular spectroscopy with chemometric techniques for the study of response and sensitivity of molecular structures/functional groups mainly related to lipid biopolymer to various processing applications.

PubMed

Yu, Gloria Qingyu; Yu, Peiqiang

2015-09-01

The objectives of this project were to (1) combine vibrational spectroscopy with chemometric multivariate techniques to determine the effect of processing applications on molecular structural changes of lipid biopolymer that mainly related to functional groups in green- and yellow-type Crop Development Centre (CDC) pea varieties [CDC strike (green-type) vs. CDC meadow (yellow-type)] that occurred during various processing applications; (2) relatively quantify the effect of processing applications on the antisymmetric CH3 ("CH3as") and CH2 ("CH2as") (ca. 2960 and 2923 cm(-1), respectively), symmetric CH3 ("CH3s") and CH2 ("CH2s") (ca. 2873 and 2954 cm(-1), respectively) functional groups and carbonyl C=O ester (ca. 1745 cm(-1)) spectral intensities as well as their ratios of antisymmetric CH3 to antisymmetric CH2 (ratio of CH3as to CH2as), ratios of symmetric CH3 to symmetric CH2 (ratio of CH3s to CH2s), and ratios of carbonyl C=O ester peak area to total CH peak area (ratio of C=O ester to CH); and (3) illustrate non-invasive techniques to detect the sensitivity of individual molecular functional group to the various processing applications in the recently developed different types of pea varieties. The hypothesis of this research was that processing applications modified the molecular structure profiles in the processed products as opposed to original unprocessed pea seeds. The results showed that the different processing methods had different impacts on lipid molecular functional groups. Different lipid functional groups had different sensitivity to various heat processing applications. These changes were detected by advanced molecular spectroscopy with chemometric techniques which may be highly related to lipid utilization and availability. The multivariate molecular spectral analyses, cluster analysis, and principal component analysis of original spectra (without spectral parameterization) are unable to fully distinguish the structural differences in the antisymmetric and symmetric CH3 and CH2 spectral region (ca. 3001-2799 cm(-1)) and carbonyl C=O ester band region (ca. 1771-1714 cm(-1)). This result indicated that the sensitivity to detect treatment difference by multivariate analysis of cluster analysis (CLA) and principal components analysis (PCA) might be lower compared with univariate molecular spectral analysis. In the future, other more sensitive techniques such as "discriminant analysis" could be considered for discriminating and classifying structural differences. Molecular spectroscopy can be used as non-invasive technique to study processing-induced structural changes that are related to lipid compound in legume seeds.

Sensitive detection of point mutation using exponential strand displacement amplification-based surface enhanced Raman spectroscopy.

PubMed

Huang, Si-Qiang; Hu, Juan; Zhu, Guichi; Zhang, Chun-Yang

2015-03-15

Accurate identification of point mutation is particularly imperative in the field of biomedical research and clinical diagnosis. Here, we develop a sensitive and specific method for point mutation assay using exponential strand displacement amplification (SDA)-based surface enhanced Raman spectroscopy (SERS). In this method, a discriminating probe and a hairpin probe are designed to specifically recognize the sequence of human K-ras gene. In the presence of K-ras mutant target (C→T), the 3'-terminal of discriminating probe and the 5'-terminal of hairpin probe can be ligated to form a SDA template. Subsequently, the 3'-terminal of hairpin probe can function as a primer to initiate the SDA reaction, producing a large amount of triggers. The resultant triggers can further hybridize with the discriminating probes to initiate new rounds of SDA reaction, leading to an exponential amplification reaction. With the addition of capture probe-modified gold nanoparticles (AuNPs) and the Rox-labeled reporter probes, the amplified triggers can be assembled on the surface of AuNPs through the formation of sandwich hybrids of capture probe-trigger-reporter probe, generating a strong Raman signal. While in the presence of K-ras wild-type target (C), neither ligation nor SDA reaction can be initiated and no Raman signal is observed. The proposed method exhibits high sensitivity with a detection limit of 1.4pM and can accurately discriminate as low as 1% variant frequency from the mixture of mutant target and wild-type target. Importantly, this method can be further applied to analyze the mutant target in the spiked HEK293T cell lysate, holding great potential for genetic analysis and disease prognosis. Copyright © 2014 Elsevier B.V. All rights reserved.

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Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-02

... Act of 1973 Discrimination Complaint Form. The Department of Justice, Civil Rights Division... Act of 1973 Discrimination Complaint Form. (3) The agency form number and applicable component of the...: Individuals alleging discrimination by public entities based on disability. Under title II of the Americans...

Fourier transform infrared spectroscopy combined with chemometrics for discrimination of Curcuma longa, Curcuma xanthorrhiza and Zingiber cassumunar

NASA Astrophysics Data System (ADS)

Rohaeti, Eti; Rafi, Mohamad; Syafitri, Utami Dyah; Heryanto, Rudi

2015-02-01

Turmeric (Curcuma longa), java turmeric (Curcuma xanthorrhiza) and cassumunar ginger (Zingiber cassumunar) are widely used in traditional Indonesian medicines (jamu). They have similar color for their rhizome and possess some similar uses, so it is possible to substitute one for the other. The identification and discrimination of these closely-related plants is a crucial task to ensure the quality of the raw materials. Therefore, an analytical method which is rapid, simple and accurate for discriminating these species using Fourier transform infrared spectroscopy (FTIR) combined with some chemometrics methods was developed. FTIR spectra were acquired in the mid-IR region (4000-400 cm-1). Standard normal variate, first and second order derivative spectra were compared for the spectral data. Principal component analysis (PCA) and canonical variate analysis (CVA) were used for the classification of the three species. Samples could be discriminated by visual analysis of the FTIR spectra by using their marker bands. Discrimination of the three species was also possible through the combination of the pre-processed FTIR spectra with PCA and CVA, in which CVA gave clearer discrimination. Subsequently, the developed method could be used for the identification and discrimination of the three closely-related plant species.

Triglyceride dependent differentiation of obesity in adipose tissues by FTIR spectroscopy coupled with chemometrics.

PubMed

Kucuk Baloglu, Fatma; Baloglu, Onur; Heise, Sebastian; Brockmann, Gudrun; Severcan, Feride

2017-10-01

The excess deposition of triglycerides in adipose tissue is the main reason of obesity and causes excess release of fatty acids to the circulatory system resulting in obesity and insulin resistance. Body mass index and waist circumference are not precise measure of obesity and obesity related metabolic diseases. Therefore, in the current study, it was aimed to propose triglyceride bands located at 1770-1720 cm -1 spectral region as a more sensitive obesity related biomarker using the diagnostic potential of Fourier Transform Infrared (FTIR) spectroscopy in subcutaneous (SCAT) and visceral (VAT) adipose tissues. The adipose tissue samples were obtained from 10 weeks old male control (DBA/2J) (n = 6) and four different obese BFMI mice lines (n = 6 per group). FTIR spectroscopy coupled with hierarchical cluster analysis (HCA) and principal component analysis (PCA) was applied to the spectra of triglyceride bands as a diagnostic tool in the discrimination of the samples. Successful discrimination of the obese, obesity related insulin resistant and control groups were achieved with high sensitivity and specificity. The results revealed the power of FTIR spectroscopy coupled with chemometric approaches in internal diagnosis of abdominal obesity based on the spectral differences in the triglyceride region that can be used as a spectral marker. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Discriminating Bio-aerosols from Non-Bio-aerosols in Real-Time by Pump-Probe Spectroscopy

PubMed Central

Sousa, Gustavo; Gaulier, Geoffrey; Bonacina, Luigi; Wolf, Jean-Pierre

2016-01-01

The optical identification of bioaerosols in the atmosphere and its discrimination against combustion related particles is a major issue for real-time, field compatible instruments. In the present paper, we show that by embedding advanced pump-probe depletion spectroscopy schemes in a portable instrument, it is possible to discriminate amino acid containing airborne particles (bacteria, humic particles, etc.) from poly-cyclic aromatic hydrocarbon containing combustion particles (Diesel droplets, soot, vehicle exhausts) with high selectivity. Our real-time, multi-modal device provides, in addition to the pump-probe depletion information, fluorescence spectra (over 32 channels), fluorescence lifetime and Mie scattering patterns of each individually flowing particle in the probed air. PMID:27619546

Discriminating Bio-aerosols from Non-Bio-aerosols in Real-Time by Pump-Probe Spectroscopy

NASA Astrophysics Data System (ADS)

Sousa, Gustavo; Gaulier, Geoffrey; Bonacina, Luigi; Wolf, Jean-Pierre

2016-09-01

The optical identification of bioaerosols in the atmosphere and its discrimination against combustion related particles is a major issue for real-time, field compatible instruments. In the present paper, we show that by embedding advanced pump-probe depletion spectroscopy schemes in a portable instrument, it is possible to discriminate amino acid containing airborne particles (bacteria, humic particles, etc.) from poly-cyclic aromatic hydrocarbon containing combustion particles (Diesel droplets, soot, vehicle exhausts) with high selectivity. Our real-time, multi-modal device provides, in addition to the pump-probe depletion information, fluorescence spectra (over 32 channels), fluorescence lifetime and Mie scattering patterns of each individually flowing particle in the probed air.

Discriminating Bio-aerosols from Non-Bio-aerosols in Real-Time by Pump-Probe Spectroscopy.

PubMed

Sousa, Gustavo; Gaulier, Geoffrey; Bonacina, Luigi; Wolf, Jean-Pierre

2016-09-13

The optical identification of bioaerosols in the atmosphere and its discrimination against combustion related particles is a major issue for real-time, field compatible instruments. In the present paper, we show that by embedding advanced pump-probe depletion spectroscopy schemes in a portable instrument, it is possible to discriminate amino acid containing airborne particles (bacteria, humic particles, etc.) from poly-cyclic aromatic hydrocarbon containing combustion particles (Diesel droplets, soot, vehicle exhausts) with high selectivity. Our real-time, multi-modal device provides, in addition to the pump-probe depletion information, fluorescence spectra (over 32 channels), fluorescence lifetime and Mie scattering patterns of each individually flowing particle in the probed air.

Non-invasive sex assessment in bovine semen by Raman spectroscopy

NASA Astrophysics Data System (ADS)

De Luca, A. C.; Managó, S.; Ferrara, M. A.; Rendina, I.; Sirleto, L.; Puglisi, R.; Balduzzi, D.; Galli, A.; Ferraro, P.; Coppola, G.

2014-05-01

X- and Y-chromosome-bearing sperm cell sorting is of great interest, especially for animal production management systems and genetic improvement programs. Here, we demonstrate an optical method based on Raman spectroscopy to separate X- and Y-chromosome-bearing sperm cells, overcoming many of the limitations associated with current sex-sorting protocols. A priori Raman imaging of bull spermatozoa was utilized to select the sampling points (head-neck region), which were then used to discriminate cells based on a spectral classification model. Main variations of Raman peaks associated with the DNA content were observed together with a variation due to the sex membrane proteins. Next, we used principal component analysis to determine the efficiency of our device as a cell sorting method. The results (>90% accuracy) demonstrated that Raman spectroscopy is a powerful candidate for the development of a highly efficient, non-invasive, and non-destructive tool for sperm sexing.

Age-based hiring discrimination as a function of equity norms and self-perceived objectivity.

PubMed

Lindner, Nicole M; Graser, Alexander; Nosek, Brian A

2014-01-01

Participants completed a questionnaire priming them to perceive themselves as either objective or biased, either before or after evaluating a young or old job applicant for a position linked to youthful stereotypes. Participants agreed that they were objective and tended to disagree that they were biased. Extending past research, both the objective and bias priming conditions led to an increase in age discrimination compared to the control condition. We also investigated whether equity norms reduced age discrimination, by manipulating the presence or absence of an equity statement reminding decision-makers of the legal prohibitions against discrimination "on the basis of age, disability, national or ethnic origin, race, religion, or sex." The presence of equity norms increased enthusiasm for both young and old applicants when participants were not already primed to think of themselves as objective, but did not reduce age-based hiring discrimination. Equity norms had no effect when individuals thought of themselves as objective - they preferred the younger more than the older job applicant. However, the presence of equity norms did affect individuals' perceptions of which factors were important to their hiring decisions, increasing the perceived importance of applicants' expertise and decreasing the perceived importance of the applicants' age. The results suggest that interventions that rely exclusively on decision-makers' intentions to behave equitably may be ineffective.

Discrimination of tomatoes bred by spaceflight mutagenesis using visible/near infrared spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Shao, Yongni; Xie, Chuanqi; Jiang, Linjun; Shi, Jiahui; Zhu, Jiajin; He, Yong

2015-04-01

Visible/near infrared spectroscopy (Vis/NIR) based on sensitive wavelengths (SWs) and chemometrics was proposed to discriminate different tomatoes bred by spaceflight mutagenesis from their leafs or fruits (green or mature). The tomato breeds were mutant M1, M2 and their parent. Partial least squares (PLS) analysis and least squares-support vector machine (LS-SVM) were implemented for calibration models. PLS analysis was implemented for calibration models with different wavebands including the visible region (400-700 nm) and the near infrared region (700-1000 nm). The best PLS models were achieved in the visible region for the leaf and green fruit samples and in the near infrared region for the mature fruit samples. Furthermore, different latent variables (4-8 LVs for leafs, 5-9 LVs for green fruits, and 4-9 LVs for mature fruits) were used as inputs of LS-SVM to develop the LV-LS-SVM models with the grid search technique and radial basis function (RBF) kernel. The optimal LV-LS-SVM models were achieved with six LVs for the leaf samples, seven LVs for green fruits, and six LVs for mature fruits, respectively, and they outperformed the PLS models. Moreover, independent component analysis (ICA) was executed to select several SWs based on loading weights. The optimal LS-SVM model was achieved with SWs of 550-560 nm, 562-574 nm, 670-680 nm and 705-715 nm for the leaf samples; 548-556 nm, 559-564 nm, 678-685 nm and 962-974 nm for the green fruit samples; and 712-718 nm, 720-729 nm, 968-978 nm and 820-830 nm for the mature fruit samples. All of them had better performance than PLS and LV-LS-SVM, with the parameters of correlation coefficient (rp), root mean square error of prediction (RMSEP) and bias of 0.9792, 0.2632 and 0.0901 based on leaf discrimination, 0.9837, 0.2783 and 0.1758 based on green fruit discrimination, 0.9804, 0.2215 and -0.0035 based on mature fruit discrimination, respectively. The overall results indicated that ICA was an effective way for the selection of SWs, and the Vis/NIR combined with LS-SVM models had the capability to predict the different breeds (mutant M1, mutant M2 and their parent) of tomatoes from leafs and fruits.

Discriminant analysis of Raman spectra for body fluid identification for forensic purposes.

PubMed

Sikirzhytski, Vitali; Virkler, Kelly; Lednev, Igor K

2010-01-01

Detection and identification of blood, semen and saliva stains, the most common body fluids encountered at a crime scene, are very important aspects of forensic science today. This study targets the development of a nondestructive, confirmatory method for body fluid identification based on Raman spectroscopy coupled with advanced statistical analysis. Dry traces of blood, semen and saliva obtained from multiple donors were probed using a confocal Raman microscope with a 785-nm excitation wavelength under controlled laboratory conditions. Results demonstrated the capability of Raman spectroscopy to identify an unknown substance to be semen, blood or saliva with high confidence.

Ethnicity- and Sex-Based Discrimination and the Maintenance of Self-Esteem

PubMed Central

2015-01-01

The psychological underpinnings of labor market discrimination were investigated by having participants from Israel, the West Bank and Germany (N = 205) act as employers in a stylized employment task in which they ranked, set wages, and imposed a minimum effort level on applicants. State self-esteem was measured before and after the employment task, in which applicant ethnicity and sex were salient. The applicants were real people and all behavior was monetarily incentivized. Supporting the full self-esteem hypothesis of the social identity approach, low self-esteem in women was associated with assigning higher wages to women than to men, and such behavior was related to the maintenance of self-esteem. The narrower hypothesis that successful intergroup discrimination serves to protect self-esteem received broader support. Across all participants, both ethnicity- and sex-based discrimination of out-groups were associated with the maintenance of self-esteem, with the former showing a stronger association than the latter. PMID:25978646

Semi-quantitative prediction of a multiple API solid dosage form with a combination of vibrational spectroscopy methods.

PubMed

Hertrampf, A; Sousa, R M; Menezes, J C; Herdling, T

2016-05-30

Quality control (QC) in the pharmaceutical industry is a key activity in ensuring medicines have the required quality, safety and efficacy for their intended use. QC departments at pharmaceutical companies are responsible for all release testing of final products but also all incoming raw materials. Near-infrared spectroscopy (NIRS) and Raman spectroscopy are important techniques for fast and accurate identification and qualification of pharmaceutical samples. Tablets containing two different active pharmaceutical ingredients (API) [bisoprolol, hydrochlorothiazide] in different commercially available dosages were analysed using Raman- and NIR Spectroscopy. The goal was to define multivariate models based on each vibrational spectroscopy to discriminate between different dosages (identity) and predict their dosage (semi-quantitative). Furthermore the combination of spectroscopic techniques was investigated. Therefore, two different multiblock techniques based on PLS have been applied: multiblock PLS (MB-PLS) and sequential-orthogonalised PLS (SO-PLS). NIRS showed better results compared to Raman spectroscopy for both identification and quantitation. The multiblock techniques investigated showed that each spectroscopy contains information not present or captured with the other spectroscopic technique, thus demonstrating that there is a potential benefit in their combined use for both identification and quantitation purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

Trimodal spectra for high discrimination of benign and malignant prostate tissue

NASA Astrophysics Data System (ADS)

Al Salhi, Mohamad; Masilamani, Vadivel; Trinka, Vijmasi; Rabah, Danny; Al Turki, Mohammed R.

2011-02-01

High false positives and over diagnosis is a major problem with management of prostate cancer. A non-invasive or a minimally invasive technique to accurately distinguish malignant prostate cancers from benign tumors will be extremely helpful to overcome this problem. In this paper, we had used three different fluorescence spectroscopy techniques viz., Fluorescence Emission Spectrum (FES), Stokes' Shift Spectrum (SSS) and Reflectance Spectrum (RS) to discriminate benign prostate tumor tissues (N=12) and malignant prostate cancer tissues (N=8). These fluorescence techniques were used to determine the relative concentration of naturally occurring biomolecules such as tryptophan, elastin, NADH and flavin which are found to be out of proportion in cancer tissues. Our studies show that combining all three techniques, benign and malignant prostate tissues could be classified with accuracy greater than 90%. This preliminary report is based on in vitro spectroscopy analysis. However, by employing fluorescence endoscopy techniques, this can be extended to in vivo analysis as well. This technique has the potential to identify malignant prostate tissues without surgery.

Classification of java tea (Orthosiphon aristatus) quality using FTIR spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Heryanto, R.; Pradono, D. I.; Marlina, E.; Darusman, L. K.

2017-05-01

Java tea (Orthosiphon aristatus) is a plant that widely used as a medicinal herb in Indonesia. Its quality is varying depends on various factors, such as cultivating area, climate and harvesting time. This study aimed to investigate the effectiveness of FTIR spectroscopy coupled with chemometrics for discriminating the quality of java tea from different cultivating area. FTIR spectra of ethanolic extracts were collected from five different regions of origin of java tea. Prior to chemometrics evaluation, spectra were pre-processed by using baselining, normalization and derivatization. Principal Components Analysis (PCA) was used to reduce the spectra to two PCs, which explained 73% of the total variance. Score plot of two PCs showed groupings of the samples according to their regions of origin. Furthermore, Partial Least Squares-Discriminant Analysis (PLSDA) was applied to the pre-processed data. The approach produced an external validation success rate of 100%. This study shows that FTIR analysis and chemometrics has discriminatory power to classify java tea based on its quality related to the region of origin.

Discrimination and Measurements of Three Flavonols with Similar Structure Using Terahertz Spectroscopy and Chemometrics

NASA Astrophysics Data System (ADS)

Yan, Ling; Liu, Changhong; Qu, Hao; Liu, Wei; Zhang, Yan; Yang, Jianbo; Zheng, Lei

2018-03-01

Terahertz (THz) technique, a recently developed spectral method, has been researched and used for the rapid discrimination and measurements of food compositions due to its low-energy and non-ionizing characteristics. In this study, THz spectroscopy combined with chemometrics has been utilized for qualitative and quantitative analysis of myricetin, quercetin, and kaempferol with concentrations of 0.025, 0.05, and 0.1 mg/mL. The qualitative discrimination was achieved by KNN, ELM, and RF models with the spectra pre-treatments. An excellent discrimination (100% CCR in the prediction set) could be achieved using the RF model. Furthermore, the quantitative analyses were performed by partial least square regression (PLSR) and least squares support vector machine (LS-SVM). Comparing to the PLSR models, the LS-SVM yielded better results with low RMSEP (0.0044, 0.0039, and 0.0048), higher Rp (0.9601, 0.9688, and 0.9359), and higher RPD (8.6272, 9.6333, and 7.9083) for myricetin, quercetin, and kaempferol, respectively. Our results demonstrate that THz spectroscopy technique is a powerful tool for identification of three flavonols with similar chemical structures and quantitative determination of their concentrations.

Study on fast discrimination of varieties of yogurt using Vis/NIR-spectroscopy

NASA Astrophysics Data System (ADS)

He, Yong; Feng, Shuijuan; Deng, Xunfei; Li, Xiaoli

2006-09-01

A new approach for discrimination of varieties of yogurt by means of VisINTR-spectroscopy was present in this paper. Firstly, through the principal component analysis (PCA) of spectroscopy curves of 5 typical kinds of yogurt, the clustering of yogurt varieties was processed. The analysis results showed that the cumulate reliabilities of PC1 and PC2 (the first two principle components) were more than 98.956%, and the cumulate reliabilities from PC1 to PC7 (the first seven principle components) was 99.97%. Secondly, a discrimination model of Artificial Neural Network (ANN-BP) was set up. The first seven principles components of the samples were applied as ANN-BP inputs, and the value of type of yogurt were applied as outputs, then the three-layer ANN-BP model was build. In this model, every variety yogurt includes 27 samples, the total number of sample is 135, and the rest 25 samples were used as prediction set. The results showed the distinguishing rate of the five yogurt varieties was 100%. It presented that this model was reliable and practicable. So a new approach for the rapid and lossless discrimination of varieties of yogurt was put forward.

Accelerating two-dimensional nuclear magnetic resonance correlation spectroscopy via selective coherence transfer

NASA Astrophysics Data System (ADS)

Ye, Qimiao; Chen, Lin; Qiu, Wenqi; Lin, Liangjie; Sun, Huijun; Cai, Shuhui; Wei, Zhiliang; Chen, Zhong

2017-01-01

Nuclear magnetic resonance (NMR) spectroscopy serves as an important tool for both qualitative and quantitative analyses of various systems in chemistry, biology, and medicine. However, applications of one-dimensional 1H NMR are often restrained by the presence of severe overlap among different resonances. The advent of two-dimensional (2D) 1H NMR constitutes a promising alternative by extending the crowded resonances into a plane and thereby alleviating the spectral congestions. However, the enhanced ability in discriminating resonances is achieved at the cost of extended experimental duration due to necessity of various scans with progressive delays to construct the indirect dimension. Therefore, in this study, we propose a selective coherence transfer (SECOT) method to accelerate acquisitions of 2D correlation spectroscopy by converting chemical shifts into spatial positions within the effective sample length and then performing an echo planar spectroscopic imaging module to record the spatial and spectral information, which generates 2D correlation spectrum after 2D Fourier transformation. The feasibility and effectiveness of SECOT have been verified by a set of experiments under both homogeneous and inhomogeneous magnetic fields. Moreover, evaluations of SECOT for quantitative analyses are carried out on samples with a series of different concentrations. Based on these experimental results, the SECOT may open important perspectives for fast, accurate, and stable investigations of various chemical systems both qualitatively and quantitatively.

Non-Gated Laser Induced Breakdown Spectroscopy Provides a Powerful Segmentation Tool on Concomitant Treatment of Characteristic and Continuum Emission

PubMed Central

Dasari, Ramachandra Rao; Barman, Ishan; Gundawar, Manoj Kumar

2014-01-01

We demonstrate the application of non-gated laser induced breakdown spectroscopy (LIBS) for characterization and classification of organic materials with similar chemical composition. While use of such a system introduces substantive continuum background in the spectral dataset, we show that appropriate treatment of the continuum and characteristic emission results in accurate discrimination of pharmaceutical formulations of similar stoichiometry. Specifically, our results suggest that near-perfect classification can be obtained by employing suitable multivariate analysis on the acquired spectra, without prior removal of the continuum background. Indeed, we conjecture that pre-processing in the form of background removal may introduce spurious features in the signal. Our findings in this report significantly advance the prior results in time-integrated LIBS application and suggest the possibility of a portable, non-gated LIBS system as a process analytical tool, given its simple instrumentation needs, real-time capability and lack of sample preparation requirements. PMID:25084522

Rapid detection of foodborne microorganisms on food surface using Fourier transform Raman spectroscopy

NASA Astrophysics Data System (ADS)

Yang, Hong; Irudayaraj, Joseph

2003-02-01

Fourier transform (FT) Raman spectroscopy was used for non-destructive characterization and differentiation of six different microorganisms including the pathogen Escherichia coli O157:H7 on whole apples. Mahalanobis distance metric was used to evaluate and quantify the statistical differences between the spectra of six different microorganisms. The same procedure was extended to discriminate six different strains of E. coli. The FT-Raman procedure was not only successful in discriminating the different E. coli strain but also accurately differentiated the pathogen from non-pathogens. Results demonstrate that FT-Raman spectroscopy can be an excellent tool for rapid examination of food surfaces for microorganism contamination and for the classification of microbial cultures.

A Functional Near-Infrared Spectroscopy Study of Sustained Attention to Local and Global Target Features

ERIC Educational Resources Information Center

De Joux, Neil; Russell, Paul N.; Helton, William S.

2013-01-01

Despite a long history of vigilance research, the role of global and local feature discrimination in vigilance tasks has been relatively neglected. In this experiment participants performed a sustained attention task requiring either global or local shape stimuli discrimination. Reaction time to local feature discriminations was characterized by a…

Discrimination of whisky brands and counterfeit identification by UV-Vis spectroscopy and multivariate data analysis.

PubMed

Martins, Angélica Rocha; Talhavini, Márcio; Vieira, Maurício Leite; Zacca, Jorge Jardim; Braga, Jez Willian Batista

2017-08-15

The discrimination of whisky brands and counterfeit identification were performed by UV-Vis spectroscopy combined with partial least squares for discriminant analysis (PLS-DA). In the proposed method all spectra were obtained with no sample preparation. The discrimination models were built with the employment of seven whisky brands: Red Label, Black Label, White Horse, Chivas Regal (12years), Ballantine's Finest, Old Parr and Natu Nobilis. The method was validated with an independent test set of authentic samples belonging to the seven selected brands and another eleven brands not included in the training samples. Furthermore, seventy-three counterfeit samples were also used to validate the method. Results showed correct classification rates for genuine and false samples over 98.6% and 93.1%, respectively, indicating that the method can be helpful for the forensic analysis of whisky samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

PubMed Central

Xue, Ming; Yang, Hua; Zheng, Shibao; Zhou, Yi; Yu, Zhenghua

2014-01-01

To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT) is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU) strategy is proposed for sparse coefficient learning. To formulate the training and classification process, a multiple linear classifier group based on a K-combined voting (KCV) function is proposed. As the dictionary evolves, the models are also trained to timely adapt the target appearance variation. Qualitative and quantitative evaluations on challenging image sequences compared with state-of-the-art algorithms demonstrate that the proposed tracking algorithm achieves a more favorable performance. We also illustrate its relay application in visual sensor networks. PMID:24549252

Are insurance companies liable under the Americans with Disabilities Act?

PubMed

Manning, J S

2000-03-01

Federal courts have split on the question of the applicability of the Americans with Disabilities Act to insurance coverage decisions that insurance companies make on the basis of disability; they have similarly split on other issues pertaining to the scope of that Act's application. In deciding whether to read the Act as prohibiting discrimination in insurance decisions that are often crucial in the lives of people with disabilities, courts have faced two problems. First, where it prohibits discrimination in the equal enjoyment of the goods and services of places of public accommodation, the Act's area of concern may be limited to the ability of people with disabilities to gain physical access to facilities; or that area may extend to all forms of disability-based discrimination in the provision of goods and services. This Comment argues that the language and legislative history of the Act are consistent only with the latter view. Second, the provision limiting the Act's applicability to insurance may create an exemption for all insurance decisions; or it may protect only the ability of an insurance company to make an insurance decision to the disadvantage of an insured with a disability where actuarial data support the decision. This comment argues that the ambiguous language of the limiting provision should be resolved in favor of the latter view. Legislative history and the broader background of the history of insurance discrimination law support this resolution. Consequently, the Act should be interpreted as prohibiting disability-based discrimination by insurance companies in selling insurance policies and as defining discrimination as making disability-based insurance decisions without the support of actuarial data. By accepting this interpretation, courts can help stop the pattern of judicial narrowing of the Act's application through inappropriately restrictive statutory construction.

Fast detection of tobacco mosaic virus infected tobacco using laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Peng, Jiyu; Song, Kunlin; Zhu, Hongyan; Kong, Wenwen; Liu, Fei; Shen, Tingting; He, Yong

2017-03-01

Tobacco mosaic virus (TMV) is one of the most devastating viruses to crops, which can cause severe production loss and affect the quality of products. In this study, we have proposed a novel approach to discriminate TMV-infected tobacco based on laser-induced breakdown spectroscopy (LIBS). Two different kinds of tobacco samples (fresh leaves and dried leaf pellets) were collected for spectral acquisition, and partial least squared discrimination analysis (PLS-DA) was used to establish classification models based on full spectrum and observed emission lines. The influences of moisture content on spectral profile, signal stability and plasma parameters (temperature and electron density) were also analysed. The results revealed that moisture content in fresh tobacco leaves would worsen the stability of analysis, and have a detrimental effect on the classification results. Good classification results were achieved based on the data from both full spectrum and observed emission lines of dried leaves, approaching 97.2% and 88.9% in the prediction set, respectively. In addition, support vector machine (SVM) could improve the classification results and eliminate influences of moisture content. The preliminary results indicate that LIBS coupled with chemometrics could provide a fast, efficient and low-cost approach for TMV-infected disease detection in tobacco leaves.

Fast detection of tobacco mosaic virus infected tobacco using laser-induced breakdown spectroscopy

PubMed Central

Peng, Jiyu; Song, Kunlin; Zhu, Hongyan; Kong, Wenwen; Liu, Fei; Shen, Tingting; He, Yong

2017-01-01

Tobacco mosaic virus (TMV) is one of the most devastating viruses to crops, which can cause severe production loss and affect the quality of products. In this study, we have proposed a novel approach to discriminate TMV-infected tobacco based on laser-induced breakdown spectroscopy (LIBS). Two different kinds of tobacco samples (fresh leaves and dried leaf pellets) were collected for spectral acquisition, and partial least squared discrimination analysis (PLS-DA) was used to establish classification models based on full spectrum and observed emission lines. The influences of moisture content on spectral profile, signal stability and plasma parameters (temperature and electron density) were also analysed. The results revealed that moisture content in fresh tobacco leaves would worsen the stability of analysis, and have a detrimental effect on the classification results. Good classification results were achieved based on the data from both full spectrum and observed emission lines of dried leaves, approaching 97.2% and 88.9% in the prediction set, respectively. In addition, support vector machine (SVM) could improve the classification results and eliminate influences of moisture content. The preliminary results indicate that LIBS coupled with chemometrics could provide a fast, efficient and low-cost approach for TMV-infected disease detection in tobacco leaves. PMID:28300144

Rapid characterization of transgenic and non-transgenic soybean oils by chemometric methods using NIR spectroscopy

NASA Astrophysics Data System (ADS)

Luna, Aderval S.; da Silva, Arnaldo P.; Pinho, Jéssica S. A.; Ferré, Joan; Boqué, Ricard

Near infrared (NIR) spectroscopy and multivariate classification were applied to discriminate soybean oil samples into non-transgenic and transgenic. Principal Component Analysis (PCA) was applied to extract relevant features from the spectral data and to remove the anomalous samples. The best results were obtained when with Support Vectors Machine-Discriminant Analysis (SVM-DA) and Partial Least Squares-Discriminant Analysis (PLS-DA) after mean centering plus multiplicative scatter correction. For SVM-DA the percentage of successful classification was 100% for the training group and 100% and 90% in validation group for non transgenic and transgenic soybean oil samples respectively. For PLS-DA the percentage of successful classification was 95% and 100% in training group for non transgenic and transgenic soybean oil samples respectively and 100% and 80% in validation group for non transgenic and transgenic respectively. The results demonstrate that NIR spectroscopy can provide a rapid, nondestructive and reliable method to distinguish non-transgenic and transgenic soybean oils.

The application of Near-Infrared Reflectance Spectroscopy (NIRS) to detect melamine adulteration of soya bean meal.

PubMed

Haughey, Simon A; Graham, Stewart F; Cancouët, Emmanuelle; Elliott, Christopher T

2013-02-15

Soya bean products are used widely in the animal feed industry as a protein based feed ingredient and have been found to be adulterated with melamine. This was highlighted in the Chinese scandal of 2008. Dehulled soya (GM and non-GM), soya hulls and toasted soya were contaminated with melamine and spectra were generated using Near Infrared Reflectance Spectroscopy (NIRS). By applying chemometrics to the spectral data, excellent calibration models and prediction statistics were obtained. The coefficients of determination (R(2)) were found to be 0.89-0.99 depending on the mathematical algorithm used, the data pre-processing applied and the sample type used. The corresponding values for the root mean square error of calibration and prediction were found to be 0.081-0.276% and 0.134-0.368%, respectively, again depending on the chemometric treatment applied to the data and sample type. In addition, adopting a qualitative approach with the spectral data and applying PCA, it was possible to discriminate between the four samples types and also, by generation of Cooman's plots, possible to distinguish between adulterated and non-adulterated samples. Copyright © 2012 Elsevier Ltd. All rights reserved.

Evaluation of human serum of severe rheumatoid arthritis by confocal Raman spectroscopy

NASA Astrophysics Data System (ADS)

Carvalho, C. S.; Raniero, L.; Santo, A. M. E.; Pinheiro, M. M.; Andrade, L. E. C.; Cardoso, M. A. G.; Junior, J. S.; Martin, A. A.

2010-02-01

Rheumatoid Arthritis is a systemic chronic inflammatory disease, recurrent and systemic, initiated by autoantibodies and maintained by inflammatory mechanisms cellular applicants. The evaluation of this disease to promote early diagnosis, need an associations of many tools, such as clinical, physical examination and thorough medical history. However, there is no satisfactory consensus due to its complexity. In the present work, confocal Raman spectroscopy was used to evaluate the biochemical composition of human serum of 40 volunteers, 24 patients with rheumatoid arthritis presenting clinical signs and symptoms, and 16 healthy donors. The technique of latex agglutination for the polystyrene covered with human immunoglobulin G and PCR (protein c-reactive) was performed for confirmation of possible false-negative results within the groups, facilitating the statistical interpretation and validation of the technique. This study aimed to verify the changes for the characteristics Raman peaks of biomolecules such as immunoglobulins amides and protein. The results were highly significant with a good separation between groups mentioned. The discriminant analysis was performed through the principal components and correctly identified 92% of the donors. Based on these results, we observed the behavior of arthritis autoimmune, evident in certain spectral regions that characterize the serological differences between the groups.

Estimation of different source contributions to sediment organic matter in an agricultural-forested watershed using end member mixing analyses based on stable isotope ratios and fluorescence spectroscopy.

PubMed

Derrien, Morgane; Kim, Min-Seob; Ock, Giyoung; Hong, Seongjin; Cho, Jinwoo; Shin, Kyung-Hoon; Hur, Jin

2018-03-15

The two popular source tracing tools of stable isotope ratios (δ 13 C and δ 15 N) and fluorescence spectroscopy were used to estimate the relative source contributions to sediment organic matter (SeOM) at five different river sites in an agricultural-forested watershed (Soyang Lake watershed), and their capabilities for the source assignment were compared. Bulk sediments were used for the stable isotopes, while alkaline extractable organic matter (AEOM) from sediments was used to obtain fluorescent indices for SeOM. Several source discrimination indices were fully compiled for a range of the SeOM sources distributed in the catchments of the watershed, which included soils, forest leaves, crop (C3 and C4) and riparian plants, periphyton, and organic fertilizers. The relative source contributions to the river sediment samples were estimated via end member mixing analysis (EMMA) based on several selected discrimination indices. The EMMA based on the isotopes demonstrated that all sediments were characterized by a medium to a high contribution of periphyton ranging from ~30% to 70% except for one site heavily affected by forest and agricultural fields with relatively high contributions of terrestrial materials. The EMMA based on fluorescence parameters, however, did not show similar results with low contributions from forest leaf and periphyton. The characteristics of the studied watershed were more consistent with the source contributions determined by the isotope ratios. The discrepancy in the EMMA capability for source assignments between the two analytical tools can be explained by the limited analytical window of fluorescence spectroscopy for non-fluorescent dissolved organic matter (FDOM) and the inability of AEOM to represent original bulk particulate organic matter (POM). Copyright © 2017 Elsevier B.V. All rights reserved.

A compact pulse shape discriminator module for large neutron detector arrays

NASA Astrophysics Data System (ADS)

Venkataramanan, S.; Gupta, Arti; Golda, K. S.; Singh, Hardev; Kumar, Rakesh; Singh, R. P.; Bhowmik, R. K.

2008-11-01

A cost-effective high-performance pulse shape discriminator module has been developed to process signals from organic liquid scintillator-based neutron detectors. This module is especially designed for the large neutron detector array used for studies of nuclear reaction dynamics at the Inter University Accelerator Center (IUAC). It incorporates all the necessary pulse processing circuits required for neutron spectroscopy in a novel fashion by adopting the zero crossover technique for neutron-gamma (n- γ) pulse shape discrimination. The detailed layout of the circuit and different features of the module are described in the present paper. The quality of n- γ separation obtained with this electronics is much better than that of commercial modules especially in the low-energy region. The results obtained with our module are compared with similar setups available in other laboratories.

Influence of variable selection on partial least squares discriminant analysis models for explosive residue classification

NASA Astrophysics Data System (ADS)

De Lucia, Frank C., Jr.; Gottfried, Jennifer L.

2011-02-01

Using a series of thirteen organic materials that includes novel high-nitrogen energetic materials, conventional organic military explosives, and benign organic materials, we have demonstrated the importance of variable selection for maximizing residue discrimination with partial least squares discriminant analysis (PLS-DA). We built several PLS-DA models using different variable sets based on laser induced breakdown spectroscopy (LIBS) spectra of the organic residues on an aluminum substrate under an argon atmosphere. The model classification results for each sample are presented and the influence of the variables on these results is discussed. We found that using the whole spectra as the data input for the PLS-DA model gave the best results. However, variables due to the surrounding atmosphere and the substrate contribute to discrimination when the whole spectra are used, indicating this may not be the most robust model. Further iterative testing with additional validation data sets is necessary to determine the most robust model.

Analysis of Processed Foods Containing Oils and Fats by Time of Flight Mass Spectrometry with an APCI Direct Probe.

PubMed

Ito, Shihomi; Chikasou, Masato; Inohana, Shuichi; Fujita, Kazuhiro

2016-01-01

Discriminating vegetable oils and animal and milk fats by infrared absorption spectroscopy is difficult due to similarities in their spectral patterns. Therefore, a rapid and simple method for analyzing vegetable oils, animal fats, and milk fats using TOF/MS with an APCI direct probe ion source was developed. This method enabled discrimination of these oils and fats based on mass spectra and detailed analyses of the ions derived from sterols, even in samples consisting of only a few milligrams. Analyses of the mass spectra of processed foods containing oils and milk fats, such as butter, cheese, and chocolate, enabled confirmation of the raw material origin based on specific ions derived from the oils and fats used to produce the final product.

Rapid profiling of Swiss cheese by attenuated total reflectance (ATR) infrared spectroscopy and descriptive sensory analysis.

PubMed

Kocaoglu-Vurma, N A; Eliardi, A; Drake, M A; Rodriguez-Saona, L E; Harper, W J

2009-08-01

The acceptability of cheese depends largely on the flavor formed during ripening. The flavor profiles of cheeses are complex and region- or manufacturer-specific which have made it challenging to understand the chemistry of flavor development and its correlation with sensory properties. Infrared spectroscopy is an attractive technology for the rapid, sensitive, and high-throughput analysis of foods, providing information related to its composition and conformation of food components from the spectra. Our objectives were to establish infrared spectral profiles to discriminate Swiss cheeses produced by different manufacturers in the United States and to develop predictive models for determination of sensory attributes based on infrared spectra. Fifteen samples from 3 Swiss cheese manufacturers were received and analyzed using attenuated total reflectance infrared spectroscopy (ATR-IR). The spectra were analyzed using soft independent modeling of class analogy (SIMCA) to build a classification model. The cheeses were profiled by a trained sensory panel using descriptive sensory analysis. The relationship between the descriptive sensory scores and ATR-IR spectra was assessed using partial least square regression (PLSR) analysis. SIMCA discriminated the Swiss cheeses based on manufacturer and production region. PLSR analysis generated prediction models with correlation coefficients of validation (rVal) between 0.69 and 0.96 with standard error of cross-validation (SECV) ranging from 0.04 to 0.29. Implementation of rapid infrared analysis by the Swiss cheese industry would help to streamline quality assurance.

Perspectives of shaped pulses for EPR spectroscopy

NASA Astrophysics Data System (ADS)

Spindler, Philipp E.; Schöps, Philipp; Kallies, Wolfgang; Glaser, Steffen J.; Prisner, Thomas F.

2017-07-01

This article describes current uses of shaped pulses, generated by an arbitrary waveform generator, in the field of EPR spectroscopy. We show applications of sech/tanh and WURST pulses to dipolar spectroscopy, including new pulse schemes and procedures, and discuss the more general concept of optimum-control-based pulses for applications in EPR spectroscopy. The article also describes a procedure to correct for experimental imperfections, mostly introduced by the microwave resonator, and discusses further potential applications and limitations of such pulses.

Fourier transform infrared spectroscopy combined with chemometrics for discrimination of Curcuma longa, Curcuma xanthorrhiza and Zingiber cassumunar.

PubMed

Rohaeti, Eti; Rafi, Mohamad; Syafitri, Utami Dyah; Heryanto, Rudi

2015-02-25

Turmeric (Curcuma longa), java turmeric (Curcuma xanthorrhiza) and cassumunar ginger (Zingiber cassumunar) are widely used in traditional Indonesian medicines (jamu). They have similar color for their rhizome and possess some similar uses, so it is possible to substitute one for the other. The identification and discrimination of these closely-related plants is a crucial task to ensure the quality of the raw materials. Therefore, an analytical method which is rapid, simple and accurate for discriminating these species using Fourier transform infrared spectroscopy (FTIR) combined with some chemometrics methods was developed. FTIR spectra were acquired in the mid-IR region (4000-400 cm(-1)). Standard normal variate, first and second order derivative spectra were compared for the spectral data. Principal component analysis (PCA) and canonical variate analysis (CVA) were used for the classification of the three species. Samples could be discriminated by visual analysis of the FTIR spectra by using their marker bands. Discrimination of the three species was also possible through the combination of the pre-processed FTIR spectra with PCA and CVA, in which CVA gave clearer discrimination. Subsequently, the developed method could be used for the identification and discrimination of the three closely-related plant species. Copyright © 2014 Elsevier B.V. All rights reserved.

Generation and detection of pulsed T-rays for use in the study of biological and bioterrorism issues

NASA Astrophysics Data System (ADS)

Jedju, Thomas M.; Bosacchi, Bruno; Warren, Warren S.; Nahata, Ajay; Kuenstner, Todd

2004-09-01

Terahertz (T-rays) spectroscopy has recently emerged as a powerful method to access a heretofore barely explored region of the electromagnetic spectrum where fundamental molecular resonances occur. Besides their importance for fundamental research, these resonances could be used as signatures in the identification of molecular species and as sensitive probes in a wide variety of molecular processes. In this paper we consider the potential of THz spectroscopy in the application to relevant biomedical and homeland security problems such as the analysis of normal and diseased tissues and the detection of toxic biomolecules. As examples, we present preliminary experimental data which suggest that THz spectroscopy: 1) can discriminate between cancerous and normal tissue, and 2) can reveal the presence of foreign substances hidden in an envelope and even allow their specific identification. This capability is of particular relevance as a straightforward homeland security tool for the detection of anthrax and other biotoxic molecules.

Detection of high-risk atherosclerotic lesions by time-resolved fluorescence spectroscopy based on the Laguerre deconvolution technique

NASA Astrophysics Data System (ADS)

Jo, J. A.; Fang, Q.; Papaioannou, T.; Qiao, J. H.; Fishbein, M. C.; Beseth, B.; Dorafshar, A. H.; Reil, T.; Baker, D.; Freischlag, J.; Marcu, L.

2006-02-01

This study introduces new methods of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data analysis for tissue characterization. These analytical methods were applied for the detection of atherosclerotic vulnerable plaques. Upon pulsed nitrogen laser (337 nm, 1 ns) excitation, TR-LIFS measurements were obtained from carotid atherosclerotic plaque specimens (57 endarteroctomy patients) at 492 distinct areas. The emission was both spectrally- (360-600 nm range at 5 nm interval) and temporally- (0.3 ns resolution) resolved using a prototype clinically compatible fiber-optic catheter TR-LIFS apparatus. The TR-LIFS measurements were subsequently analyzed using a standard multiexponential deconvolution and a recently introduced Laguerre deconvolution technique. Based on their histopathology, the lesions were classified as early (thin intima), fibrotic (collagen-rich intima), and high-risk (thin cap over necrotic core and/or inflamed intima). Stepwise linear discriminant analysis (SLDA) was applied for lesion classification. Normalized spectral intensity values and Laguerre expansion coefficients (LEC) at discrete emission wavelengths (390, 450, 500 and 550 nm) were used as features for classification. The Laguerre based SLDA classifier provided discrimination of high-risk lesions with high sensitivity (SE>81%) and specificity (SP>95%). Based on these findings, we believe that TR-LIFS information derived from the Laguerre expansion coefficients can provide a valuable additional dimension for the diagnosis of high-risk vulnerable atherosclerotic plaques.

Laws on Sex Discrimination in Employment. Federal Civil Rights Act, Title VII State Fair Employment Practices Laws, Executive Orders.

ERIC Educational Resources Information Center

Women's Bureau (DOL), Washington, DC.

This report describes the applicable laws regarding sex discrimination in employment. In addition to Federal law and two relevant Executive Orders, the report includes 21 state laws and the District of Columbia's law prohibiting discrimination based on sex. This document is a revision of ED 014 611. (BH)

Charged-particle spectroscopy in organic semiconducting single crystals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ciavatti, A.; Basiricò, L.; Fraboni, B.

2016-04-11

The use of organic materials as radiation detectors has grown, due to the easy processability in liquid phase at room temperature and the possibility to cover large areas by means of low cost deposition techniques. Direct charged-particle detectors based on solution-grown Organic Semiconducting Single Crystals (OSSCs) are shown to be capable to detect charged particles in pulse mode, with very good peak discrimination. The direct charged-particle detection in OSSCs has been assessed both in the planar and in the vertical axes, and a digital pulse processing algorithm has been used to perform pulse height spectroscopy and to study the chargemore » collection efficiency as a function of the applied bias voltage. Taking advantage of the charge spectroscopy and the good peak discrimination of pulse height spectra, an Hecht-like behavior of OSSCs radiation detectors is demonstrated. It has been possible to estimate the mobility-lifetime value in organic materials, a fundamental parameter for the characterization of radiation detectors, whose results are equal to μτ{sub coplanar} = (5 .5 ± 0.6 ) × 10{sup −6} cm{sup 2}/V and μτ{sub sandwich} = (1 .9 ± 0.2 ) × 10{sup −6} cm{sup 2}/V, values comparable to those of polycrystalline inorganic detectors. Moreover, alpha particles Time-of-Flight experiments have been carried out to estimate the drift mobility value. The results reported here indicate how charged-particle detectors based on OSSCs possess a great potential as low-cost, large area, solid-state direct detectors operating at room temperature. More interestingly, the good detection efficiency and peak discrimination observed for charged-particle detection in organic materials (hydrogen-rich molecules) are encouraging for their further exploitation in the detection of thermal and high-energy neutrons.« less

Does Shape Discrimination by the Mouth Activate the Parietal and Occipital Lobes? – Near-Infrared Spectroscopy Study

PubMed Central

Kagawa, Tomonori; Narita, Noriyuki; Iwaki, Sunao; Kawasaki, Shingo; Kamiya, Kazunobu; Minakuchi, Shunsuke

2014-01-01

A cross-modal association between somatosensory tactile sensation and parietal and occipital activities during Braille reading was initially discovered in tests with blind subjects, with sighted and blindfolded healthy subjects used as controls. However, the neural background of oral stereognosis remains unclear. In the present study, we investigated whether the parietal and occipital cortices are activated during shape discrimination by the mouth using functional near-infrared spectroscopy (fNIRS). Following presentation of the test piece shape, a sham discrimination trial without the test pieces induced posterior parietal lobe (BA7), extrastriate cortex (BA18, BA19), and striate cortex (BA17) activation as compared with the rest session, while shape discrimination of the test pieces markedly activated those areas as compared with the rest session. Furthermore, shape discrimination of the test pieces specifically activated the posterior parietal cortex (precuneus/BA7), extrastriate cortex (BA18, 19), and striate cortex (BA17), as compared with sham sessions without a test piece. We concluded that oral tactile sensation is recognized through tactile/visual cross-modal substrates in the parietal and occipital cortices during shape discrimination by the mouth. PMID:25299397

Does shape discrimination by the mouth activate the parietal and occipital lobes? - near-infrared spectroscopy study.

PubMed

Kagawa, Tomonori; Narita, Noriyuki; Iwaki, Sunao; Kawasaki, Shingo; Kamiya, Kazunobu; Minakuchi, Shunsuke

2014-01-01

A cross-modal association between somatosensory tactile sensation and parietal and occipital activities during Braille reading was initially discovered in tests with blind subjects, with sighted and blindfolded healthy subjects used as controls. However, the neural background of oral stereognosis remains unclear. In the present study, we investigated whether the parietal and occipital cortices are activated during shape discrimination by the mouth using functional near-infrared spectroscopy (fNIRS). Following presentation of the test piece shape, a sham discrimination trial without the test pieces induced posterior parietal lobe (BA7), extrastriate cortex (BA18, BA19), and striate cortex (BA17) activation as compared with the rest session, while shape discrimination of the test pieces markedly activated those areas as compared with the rest session. Furthermore, shape discrimination of the test pieces specifically activated the posterior parietal cortex (precuneus/BA7), extrastriate cortex (BA18, 19), and striate cortex (BA17), as compared with sham sessions without a test piece. We concluded that oral tactile sensation is recognized through tactile/visual cross-modal substrates in the parietal and occipital cortices during shape discrimination by the mouth.

Analysis and identification of two similar traditional Chinese medicines by using a three-stage infrared spectroscopy: Ligusticum chuanxiong, Angelica sinensis and their different extracts

NASA Astrophysics Data System (ADS)

Xiang, Li; Wang, Jingjuan; Zhang, Guijun; Rong, Lixin; Wu, Haozhong; Sun, Suqin; Guo, Yizhen; Yang, Yanfang; Lu, Lina; Qu, Lei

2016-11-01

Rhizoma Chuanxiong (CX) and Radix Angelica sinensis (DG) are very important Traditional Chinese Medicine (TCM) and usually used in clinic. They both are from the Umbelliferae family, and have almost similar chemical constituents with each other. It is complicated, time-consuming and laborious to discriminate them by using the chromatographic methods such as high performance liquid chromatography (HPLC) and gas chromatography (GC). Therefore, to find a fast, applicable and effective identification method for two herbs is urged in quality research of TCM. In this paper, by using a three-stage infrared spectroscopy (Fourier transform infrared spectroscopy (FT-IR), the second derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2D-IR)), we analyzed and discriminated CX, DG and their different extracts (aqueous extract, alcoholic extract and petroleum ether extract). In FT-IR, all the CX and DG samples' spectra seemed similar, but they had their own unique macroscopic fingerprints to identify. Through comparing with the spectra of sucrose and the similarity calculation, we found the content of sucrose in DG raw materials was higher than in CX raw materials. The significant differences in alcoholic extract appeared that in CX alcoholic extract, the peaks at 1743 cm-1 was obviously stronger than the peak at same position in DG alcoholic extract. Besides in petroleum ether extract, we concluded CX contained much more ligustilide than DG by the similarity calculation. With the function of SD-IR, some tiny differences were amplified and overlapped peaks were also unfolded in FT-IR. In the range of 1100-1175 cm-1, there were six peaks in the SD-IR spectra of DG and the intensity, shape and location of those six peaks were similar to that of sucrose, while only two peaks could be observed in that of CX and those two peaks were totally different from sucrose in shape and relative intensity. This result was consistent with that of the FT-IR. Several undetected characteristic fingerprints in FT-IR and SD-IR spectra were further disclosed by 2D-IR spectra. In the range of 1120-1500 cm-1, the FT-IR spectra and the SD-IR spectra of aqueous extract of CX and DG were almost similar and hard to be discriminated, but the 2D-IR spectra were markedly different. These findings indicated that the three-stage infrared spectroscopy can identify not only the main compositions in these two medicinal materials and their different extracts, but also can compare the differences of categories and quantities of chemical constituents between the similar samples. In conclusion, the three-stage infrared spectroscopy could identify the two similar TCM (CX and DG) quickly and effectively.

Application of laser-induced breakdown spectroscopy (LIBS) as a tool to determine the origin of 'conflict minerals'

NASA Astrophysics Data System (ADS)

Hark, R. R.; Harmon, R. S.; Remus, J. J.; East, L. J.; Wise, M. A.; Tansi, B. M.; Shughrue, K. M.; Dunsin, K. S.; Liu, C.

2012-04-01

Laser-induced breakdown spectroscopy (LIBS) offers a means of rapidly distinguishing different places of origin for a mineral because the LIBS plasma emission spectrum provides the complete chemical composition (i.e. geochemical fingerprint) of a mineral in real-time. An application of this approach with potentially significant commercial and political importance is the spectral fingerprinting of the 'conflict minerals' columbite-tantalite ("coltan"). Following a successful pilot study of three columbite-tantalite suites from the United States and Canada, a more geographically diverse set of samples from 37 locations worldwide were analyzed using a commercial laboratory LIBS system and a subset of samples also analyzed using a prototype broadband field-portable system. The spectral range from 250-490 nm was chosen for the laboratory analysis to encompass many of the intense emission lines for the major elements (Ta, Nb, Fe, Mn) and the significant trace elements (e.g., W, Ti, Zr, Sn, U, Sb, Ca, Zn, Pb, Y, Mg, and Sc) known to commonly substitute in the columbite-tantalite solid solution series crystal structure and in the columbite group minerals. The field-portable instrument offered an increased spectral range (198-1005 nm), over which all elements have spectral emission lines, and higher resolution than the laboratory instrument. In both cases, the LIBS spectra were analyzed using advanced multivariate statistical signal processing techniques. Partial Least Squares Discriminant Analysis (PLSDA) resulted in a correct place-level geographic classification at success rates between 90 and 100%. The possible role of rare-earth elements (REE's) as a factor contributing to the high levels of sample discrimination was explored. Given the fact that it can be deployed as a man-portable analytical technology, these results lend additional evidence that LIBS has the potential to be utilized in the field as a real-time tool to discriminate between columbite-tantalite ores of different provenance.

Ultraviolet spectroscopy combined with ultra-fast liquid chromatography and multivariate statistical analysis for quality assessment of wild Wolfiporia extensa from different geographical origins.

PubMed

Li, Yan; Zhang, Ji; Jin, Hang; Liu, Honggao; Wang, Yuanzhong

2016-08-05

A quality assessment system comprised of a tandem technique of ultraviolet (UV) spectroscopy and ultra-fast liquid chromatography (UFLC) aided by multivariate analysis was presented for the determination of geographic origin of Wolfiporia extensa collected from five regions in Yunnan Province of China. Characteristic UV spectroscopic fingerprints of samples were determined based on its methanol extract. UFLC was applied for the determination of pachymic acid (a biomarker) presented in individual test samples. The spectrum data matrix and the content of pachymic acid were integrated and analyzed by partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA). The results showed that chemical properties of samples were clearly dominated by the epidermis and inner part as well as geographical origins. The relationships among samples obtained from these five regions have been also presented. Moreover, an interesting finding implied that geographical origins had much greater influence on the chemical properties of epidermis compared with that of the inner part. This study demonstrated that a rapid tool for accurate discrimination of W. extensa by UV spectroscopy and UFLC could be available for quality control of complicated medicinal mushrooms. Copyright © 2016 Elsevier B.V. All rights reserved.

Fluorescence lifetime in cardiovascular diagnostics

NASA Astrophysics Data System (ADS)

Marcu, Laura

2010-01-01

We review fluorescence lifetime techniques including time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) and fluorescence lifetime imaging microscopy (FLIM) instrumentation and associated methodologies that allow for characterization and diagnosis of atherosclerotic plaques. Emphasis is placed on the translational research potential of TR-LIFS and FLIM and on determining whether intrinsic fluorescence signals can be used to provide useful contrast for the diagnosis of high-risk atherosclerotic plaque. Our results demonstrate that these techniques allow for the discrimination of important biochemical features involved in atherosclerotic plaque instability and rupture and show their potential for future intravascular applications.

Fluorescence lifetime in cardiovascular diagnostics.

PubMed

Marcu, Laura

2010-01-01

We review fluorescence lifetime techniques including time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) and fluorescence lifetime imaging microscopy (FLIM) instrumentation and associated methodologies that allow for characterization and diagnosis of atherosclerotic plaques. Emphasis is placed on the translational research potential of TR-LIFS and FLIM and on determining whether intrinsic fluorescence signals can be used to provide useful contrast for the diagnosis of high-risk atherosclerotic plaque. Our results demonstrate that these techniques allow for the discrimination of important biochemical features involved in atherosclerotic plaque instability and rupture and show their potential for future intravascular applications.

Xe isotope detection and discrimination using beta spectroscopy with coincident gamma spectroscopy

NASA Astrophysics Data System (ADS)

Reeder, P. L.; Bowyer, T. W.

1998-02-01

Beta spectroscopic techniques show promise of significant improvements for a beta-gamma coincidence counter that is part of a system for analyzing Xe automatically separated from air. The previously developed counting system for 131mXe, 133mXe, 133gXe, and 135gXe can be enhanced to give additional discrimination between these Xe isotopes by using the plastic scintillation sample cell as a beta spectrometer to resolve the conversion electron peaks. The automated system will be a key factor in monitoring the Comprehensive Test Ban Treaty.

Geographical traceability of Marsdenia tenacissima by Fourier transform infrared spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Li, Chao; Yang, Sheng-Chao; Guo, Qiao-Sheng; Zheng, Kai-Yan; Wang, Ping-Li; Meng, Zhen-Gui

2016-01-01

A combination of Fourier transform infrared spectroscopy with chemometrics tools provided an approach for studying Marsdenia tenacissima according to its geographical origin. A total of 128 M. tenacissima samples from four provinces in China were analyzed with FTIR spectroscopy. Six pattern recognition methods were used to construct the discrimination models: support vector machine-genetic algorithms, support vector machine-particle swarm optimization, K-nearest neighbors, radial basis function neural network, random forest and support vector machine-grid search. Experimental results showed that K-nearest neighbors was superior to other mathematical algorithms after data were preprocessed with wavelet de-noising, with a discrimination rate of 100% in both the training and prediction sets. This study demonstrated that FTIR spectroscopy coupled with K-nearest neighbors could be successfully applied to determine the geographical origins of M. tenacissima samples, thereby providing reliable authentication in a rapid, cheap and noninvasive way.

Rapid on-line detection and grading of wooden breast myopathy in chicken fillets by near-infrared spectroscopy.

PubMed

Wold, Jens Petter; Veiseth-Kent, Eva; Høst, Vibeke; Løvland, Atle

2017-01-01

The main objective of this work was to develop a method for rapid and non-destructive detection and grading of wooden breast (WB) syndrome in chicken breast fillets. Near-infrared (NIR) spectroscopy was chosen as detection method, and an industrial NIR scanner was applied and tested for large scale on-line detection of the syndrome. Two approaches were evaluated for discrimination of WB fillets: 1) Linear discriminant analysis based on NIR spectra only, and 2) a regression model for protein was made based on NIR spectra and the estimated concentrations of protein were used for discrimination. A sample set of 197 fillets was used for training and calibration. A test set was recorded under industrial conditions and contained spectra from 79 fillets. The classification methods obtained 99.5-100% correct classification of the calibration set and 100% correct classification of the test set. The NIR scanner was then installed in a commercial chicken processing plant and could detect incidence rates of WB in large batches of fillets. Examples of incidence are shown for three broiler flocks where a high number of fillets (9063, 6330 and 10483) were effectively measured. Prevalence of WB of 0.1%, 6.6% and 8.5% were estimated for these flocks based on the complete sample volumes. Such an on-line system can be used to alleviate the challenges WB represents to the poultry meat industry. It enables automatic quality sorting of chicken fillets to different product categories. Manual laborious grading can be avoided. Incidences of WB from different farms and flocks can be tracked and information can be used to understand and point out main causes for WB in the chicken production. This knowledge can be used to improve the production procedures and reduce today's extensive occurrence of WB.

Spectral imaging applications: Remote sensing, environmental monitoring, medicine, military operations, factory automation and manufacturing

NASA Technical Reports Server (NTRS)

Gat, N.; Subramanian, S.; Barhen, J.; Toomarian, N.

1996-01-01

This paper reviews the activities at OKSI related to imaging spectroscopy presenting current and future applications of the technology. The authors discuss the development of several systems including hardware, signal processing, data classification algorithms and benchmarking techniques to determine algorithm performance. Signal processing for each application is tailored by incorporating the phenomenology appropriate to the process, into the algorithms. Pixel signatures are classified using techniques such as principal component analyses, generalized eigenvalue analysis and novel very fast neural network methods. The major hyperspectral imaging systems developed at OKSI include the Intelligent Missile Seeker (IMS) demonstration project for real-time target/decoy discrimination, and the Thermal InfraRed Imaging Spectrometer (TIRIS) for detection and tracking of toxic plumes and gases. In addition, systems for applications in medical photodiagnosis, manufacturing technology, and for crop monitoring are also under development.

Discriminant Analysis of Raman Spectra for Body Fluid Identification for Forensic Purposes

PubMed Central

Sikirzhytski, Vitali; Virkler, Kelly; Lednev, Igor K.

2010-01-01

Detection and identification of blood, semen and saliva stains, the most common body fluids encountered at a crime scene, are very important aspects of forensic science today. This study targets the development of a nondestructive, confirmatory method for body fluid identification based on Raman spectroscopy coupled with advanced statistical analysis. Dry traces of blood, semen and saliva obtained from multiple donors were probed using a confocal Raman microscope with a 785-nm excitation wavelength under controlled laboratory conditions. Results demonstrated the capability of Raman spectroscopy to identify an unknown substance to be semen, blood or saliva with high confidence. PMID:22319277

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

NASA Astrophysics Data System (ADS)

Belianinov, Alex; Ganesh, Panchapakesan; Lin, Wenzhi; Sales, Brian C.; Sefat, Athena S.; Jesse, Stephen; Pan, Minghu; Kalinin, Sergei V.

2014-12-01

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1-xSex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

Provenance establishment of coffee using solution ICP-MS and ICP-AES.

PubMed

Valentin, Jenna L; Watling, R John

2013-11-01

Statistical interpretation of the concentrations of 59 elements, determined using solution based inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma emission spectroscopy (ICP-AES), was used to establish the provenance of coffee samples from 15 countries across five continents. Data confirmed that the harvest year, degree of ripeness and whether the coffees were green or roasted had little effect on the elemental composition of the coffees. The application of linear discriminant analysis and principal component analysis of the elemental concentrations permitted up to 96.9% correct classification of the coffee samples according to their continent of origin. When samples from each continent were considered separately, up to 100% correct classification of coffee samples into their countries, and plantations of origin was achieved. This research demonstrates the potential of using elemental composition, in combination with statistical classification methods, for accurate provenance establishment of coffee. Copyright © 2013 Elsevier Ltd. All rights reserved.

Near infrared spectroscopy is suitable for the classification of hazelnuts according to Protected Designation of Origin.

PubMed

Moscetti, Roberto; Radicetti, Emanuele; Monarca, Danilo; Cecchini, Massimo; Massantini, Riccardo

2015-10-01

This study investigates the possibility of using near infrared spectroscopy for the authentication of the 'Nocciola Romana' hazelnut (Corylus avellana L. cvs Tonda Gentile Romana and Nocchione) as a Protected Designation of Origin (PDO) hazelnut from central Italy. Algorithms for the selection of the optimal pretreatments were tested in combination with the following discriminant routines: k-nearest neighbour, soft independent modelling of class analogy, partial least squares discriminant analysis and support vector machine discriminant analysis. The best results were obtained using a support vector machine discriminant analysis routine. Thus, classification performance rates with specificities, sensitivities and accuracies as high as 96.0%, 95.0% and 95.5%, respectively, were achieved. Various pretreatments, such as standard normal variate, mean centring and a Savitzky-Golay filter with seven smoothing points, were used. The optimal wavelengths for classification were mainly correlated with lipids, although some contribution from minor constituents, such as proteins and carbohydrates, was also observed. Near infrared spectroscopy could classify hazelnut according to the PDO 'Nocciola Romana' designation. Thus, the experimentation lays the foundations for a rapid, online, authentication system for hazelnut. However, model robustness should be improved taking into account agro-pedo-climatic growing conditions. © 2014 Society of Chemical Industry.

Rapid discrimination of the causal agents of urinary tract infection using ToF-SIMS with chemometric cluster analysis

NASA Astrophysics Data System (ADS)

Fletcher, John S.; Henderson, Alexander; Jarvis, Roger M.; Lockyer, Nicholas P.; Vickerman, John C.; Goodacre, Royston

2006-07-01

Advances in time of flight secondary ion mass spectrometry (ToF-SIMS) have enabled this technique to become a powerful tool for the analysis of biological samples. Such samples are often very complex and as a result full interpretation of the acquired data can be extremely difficult. To simplify the interpretation of these information rich data, the use of chemometric techniques is becoming widespread in the ToF-SIMS community. Here we discuss the application of principal components-discriminant function analysis (PC-DFA) to the separation and classification of a number of bacterial samples that are known to be major causal agents of urinary tract infection. A large data set has been generated using three biological replicates of each isolate and three machine replicates were acquired from each biological replicate. Ordination plots generated using the PC-DFA are presented demonstrating strain level discrimination of the bacteria. The results are discussed in terms of biological differences between certain species and with reference to FT-IR, Raman spectroscopy and pyrolysis mass spectrometric studies of similar samples.

Gadolinium-Based GaN for Neutron Detection with Gamma Discrimination

DTIC Science & Technology

2016-06-01

spectroscopy system: 1, Earth ground; 2, Shielding and vacuum chamber; 3, Probe station; 4, Ohmic contact; 5, Schottky Contact; 6, BNC cable; 7...NUMBER 6. AUTHOR( S ) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) 8...PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING / MONITORING AGENCY NAME( S ) AND ADDRESS(ES) 10. SPONSOR

Advances in Neutron Spectroscopy with Deuterated Organic Scintillators

NASA Astrophysics Data System (ADS)

Febbraro, Michael; Pain, Steve; Becchetti, Frederick

2015-10-01

Deuterated organic scintillators have shown promise as neutron detectors for nuclear science as well as applications in nuclear non-proliferation and safeguards. In particular, they can extract neutron spectra without the use of neutron time-of-flight measurement (n-ToF) utilizing spectrum unfolding techniques. This permits the measure of cross sections of bound and unbound states with high efficiency and angular coverage. In the case of measurements with radioactive ion beams where low beam intensities limit long path n-ToF, short path n-ToF can be used to discriminate neutrons of interest from room return and background neutrons. This presentation will provide recent advances with these types of detectors. Digital pulse-shape discrimination using fast waveform digitizers, spectrum unfolding methods for extraction of neutron spectra, and a new safer deuterated-xylene formulation EJ-301D will be discussed. In addition, experimental results from measurements of discrete and continuous neutron spectra which illustrate the advantage of these detectors for certain applications in nuclear physics research and nuclear security will be shown. This work is supported by NSF and DOE.

[Discrimination of types of polyacrylamide based on near infrared spectroscopy coupled with least square support vector machine].

PubMed

Zhang, Hong-Guang; Yang, Qin-Min; Lu, Jian-Gang

2014-04-01

In this paper, a novel discriminant methodology based on near infrared spectroscopic analysis technique and least square support vector machine was proposed for rapid and nondestructive discrimination of different types of Polyacrylamide. The diffuse reflectance spectra of samples of Non-ionic Polyacrylamide, Anionic Polyacrylamide and Cationic Polyacrylamide were measured. Then principal component analysis method was applied to reduce the dimension of the spectral data and extract of the principal compnents. The first three principal components were used for cluster analysis of the three different types of Polyacrylamide. Then those principal components were also used as inputs of least square support vector machine model. The optimization of the parameters and the number of principal components used as inputs of least square support vector machine model was performed through cross validation based on grid search. 60 samples of each type of Polyacrylamide were collected. Thus a total of 180 samples were obtained. 135 samples, 45 samples for each type of Polyacrylamide, were randomly split into a training set to build calibration model and the rest 45 samples were used as test set to evaluate the performance of the developed model. In addition, 5 Cationic Polyacrylamide samples and 5 Anionic Polyacrylamide samples adulterated with different proportion of Non-ionic Polyacrylamide were also prepared to show the feasibilty of the proposed method to discriminate the adulterated Polyacrylamide samples. The prediction error threshold for each type of Polyacrylamide was determined by F statistical significance test method based on the prediction error of the training set of corresponding type of Polyacrylamide in cross validation. The discrimination accuracy of the built model was 100% for prediction of the test set. The prediction of the model for the 10 mixing samples was also presented, and all mixing samples were accurately discriminated as adulterated samples. The overall results demonstrate that the discrimination method proposed in the present paper can rapidly and nondestructively discriminate the different types of Polyacrylamide and the adulterated Polyacrylamide samples, and offered a new approach to discriminate the types of Polyacrylamide.

Toward the characterization of biological toxins using field-based FT-IR spectroscopic instrumentation

NASA Astrophysics Data System (ADS)

Schiering, David W.; Walton, Robert B.; Brown, Christopher W.; Norman, Mark L.; Brewer, Joseph; Scott, James

2004-12-01

IR spectroscopy is a broadly applicable technique for the identification of covalent materials. Recent advances in instrumentation have made Fourier Transform infrared (FT-IR) spectroscopy available for field characterization of suspect materials. Presently, this instrumentation is broadly deployed and used for the identification of potential chemical hazards. This discussion concerns work towards expanding the analytical utility of field-based FT-IR spectrometry in the characterization of biological threats. Two classes of materials were studied: biologically produced chemical toxins which were non-peptide in nature and peptide toxin. The IR spectroscopic identification of aflatoxin-B1, trichothecene T2 mycotoxin, and strychnine was evaluated using the approach of spectral searching against large libraries of materials. For pure components, the IR method discriminated the above toxins at better than the 99% confidence level. The ability to identify non-peptide toxins in mixtures was also evaluated using a "spectral stripping" search approach. For the mixtures evaluated, this method was able to identify the mixture components from ca. 32K spectral library entries. Castor bean extract containing ricin was used as a representative peptide toxin. Due to similarity in protein spectra, a SIMCA pattern recognition methodology was evaluated for classifying peptide toxins. In addition to castor bean extract the method was validated using bovine serum albumin and myoglobin as simulants. The SIMCA approach was successful in correctly classifying these samples at the 95% confidence level.

Discrimination of rectal cancer through human serum using surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Li, Xiaozhou; Yang, Tianyue; Li, Siqi; Zhang, Su; Jin, Lili

2015-05-01

In this paper, surface-enhanced Raman spectroscopy (SERS) was used to detect the changes in blood serum components that accompany rectal cancer. The differences in serum SERS data between rectal cancer patients and healthy controls were examined. Postoperative rectal cancer patients also participated in the comparison to monitor the effects of cancer treatments. The results show that there are significant variations at certain wavenumbers which indicates alteration of corresponding biological substances. Principal component analysis (PCA) and parameters of intensity ratios were used on the original SERS spectra for the extraction of featured variables. These featured variables then underwent linear discriminant analysis (LDA) and classification and regression tree (CART) for the discrimination analysis. Accuracies of 93.5 and 92.4 % were obtained for PCA-LDA and parameter-CART, respectively.

The Raman spectrum character of skin tumor induced by UVB

NASA Astrophysics Data System (ADS)

Wu, Shulian; Hu, Liangjun; Wang, Yunxia; Li, Yongzeng

2016-03-01

In our study, the skin canceration processes induced by UVB were analyzed from the perspective of tissue spectrum. A home-made Raman spectral system with a millimeter order excitation laser spot size combined with a multivariate statistical analysis for monitoring the skin changed irradiated by UVB was studied and the discrimination were evaluated. Raman scattering signals of the SCC and normal skin were acquired. Spectral differences in Raman spectra were revealed. Linear discriminant analysis (LDA) based on principal component analysis (PCA) were employed to generate diagnostic algorithms for the classification of skin SCC and normal. The results indicated that Raman spectroscopy combined with PCA-LDA demonstrated good potential for improving the diagnosis of skin cancers.

Characterization and Discrimination of Gram-Positive Bacteria Using Raman Spectroscopy with the Aid of Principal Component Analysis.

PubMed

Colniță, Alia; Dina, Nicoleta Elena; Leopold, Nicolae; Vodnar, Dan Cristian; Bogdan, Diana; Porav, Sebastian Alin; David, Leontin

2017-09-01

Raman scattering and its particular effect, surface-enhanced Raman scattering (SERS), are whole-organism fingerprinting spectroscopic techniques that gain more and more popularity in bacterial detection. In this work, two relevant Gram-positive bacteria species, Lactobacillus casei ( L. casei ) and Listeria monocytogenes ( L. monocytogenes ) were characterized based on their Raman and SERS spectral fingerprints. The SERS spectra were used to identify the biochemical structures of the bacterial cell wall. Two synthesis methods of the SERS-active nanomaterials were used and the recorded spectra were analyzed. L. casei and L. monocytogenes were successfully discriminated by applying Principal Component Analysis (PCA) to their specific spectral data.

Characterization and Discrimination of Gram-Positive Bacteria Using Raman Spectroscopy with the Aid of Principal Component Analysis

PubMed Central

Leopold, Nicolae; Vodnar, Dan Cristian; Bogdan, Diana; Porav, Sebastian Alin; David, Leontin

2017-01-01

Raman scattering and its particular effect, surface-enhanced Raman scattering (SERS), are whole-organism fingerprinting spectroscopic techniques that gain more and more popularity in bacterial detection. In this work, two relevant Gram-positive bacteria species, Lactobacillus casei (L. casei) and Listeria monocytogenes (L. monocytogenes) were characterized based on their Raman and SERS spectral fingerprints. The SERS spectra were used to identify the biochemical structures of the bacterial cell wall. Two synthesis methods of the SERS-active nanomaterials were used and the recorded spectra were analyzed. L. casei and L. monocytogenes were successfully discriminated by applying Principal Component Analysis (PCA) to their specific spectral data. PMID:28862655

NMR-based metabolomic analysis of spatial variation in soft corals.

PubMed

He, Qing; Sun, Ruiqi; Liu, Huijuan; Geng, Zhufeng; Chen, Dawei; Li, Yinping; Han, Jiao; Lin, Wenhan; Du, Shushan; Deng, Zhiwei

2014-03-28

Soft corals are common marine organisms that inhabit tropical and subtropical oceans. They are shown to be rich source of secondary metabolites with biological activities. In this work, soft corals from two geographical locations were investigated using ¹H-NMR spectroscopy coupled with multivariate statistical analysis at the metabolic level. A partial least-squares discriminant analysis showed clear separation among extracts of soft corals grown in Sanya Bay and Weizhou Island. The specific markers that contributed to discrimination between soft corals in two origins belonged to terpenes, sterols and N-containing compounds. The satisfied precision of classification obtained indicates this approach using combined ¹H-NMR and chemometrics is effective to discriminate soft corals collected in different geographical locations. The results revealed that metabolites of soft corals evidently depended on living environmental condition, which would provide valuable information for further relevant coastal marine environment evaluation.

Incorporation of support vector machines in the LIBS toolbox for sensitive and robust classification amidst unexpected sample and system variability

PubMed Central

ChariDingari, Narahara; Barman, Ishan; Myakalwar, Ashwin Kumar; Tewari, Surya P.; Kumar, G. Manoj

2012-01-01

Despite the intrinsic elemental analysis capability and lack of sample preparation requirements, laser-induced breakdown spectroscopy (LIBS) has not been extensively used for real world applications, e.g. quality assurance and process monitoring. Specifically, variability in sample, system and experimental parameters in LIBS studies present a substantive hurdle for robust classification, even when standard multivariate chemometric techniques are used for analysis. Considering pharmaceutical sample investigation as an example, we propose the use of support vector machines (SVM) as a non-linear classification method over conventional linear techniques such as soft independent modeling of class analogy (SIMCA) and partial least-squares discriminant analysis (PLS-DA) for discrimination based on LIBS measurements. Using over-the-counter pharmaceutical samples, we demonstrate that application of SVM enables statistically significant improvements in prospective classification accuracy (sensitivity), due to its ability to address variability in LIBS sample ablation and plasma self-absorption behavior. Furthermore, our results reveal that SVM provides nearly 10% improvement in correct allocation rate and a concomitant reduction in misclassification rates of 75% (cf. PLS-DA) and 80% (cf. SIMCA)-when measurements from samples not included in the training set are incorporated in the test data – highlighting its robustness. While further studies on a wider matrix of sample types performed using different LIBS systems is needed to fully characterize the capability of SVM to provide superior predictions, we anticipate that the improved sensitivity and robustness observed here will facilitate application of the proposed LIBS-SVM toolbox for screening drugs and detecting counterfeit samples as well as in related areas of forensic and biological sample analysis. PMID:22292496

Incorporation of support vector machines in the LIBS toolbox for sensitive and robust classification amidst unexpected sample and system variability.

PubMed

Dingari, Narahara Chari; Barman, Ishan; Myakalwar, Ashwin Kumar; Tewari, Surya P; Kumar Gundawar, Manoj

2012-03-20

Despite the intrinsic elemental analysis capability and lack of sample preparation requirements, laser-induced breakdown spectroscopy (LIBS) has not been extensively used for real-world applications, e.g., quality assurance and process monitoring. Specifically, variability in sample, system, and experimental parameters in LIBS studies present a substantive hurdle for robust classification, even when standard multivariate chemometric techniques are used for analysis. Considering pharmaceutical sample investigation as an example, we propose the use of support vector machines (SVM) as a nonlinear classification method over conventional linear techniques such as soft independent modeling of class analogy (SIMCA) and partial least-squares discriminant analysis (PLS-DA) for discrimination based on LIBS measurements. Using over-the-counter pharmaceutical samples, we demonstrate that the application of SVM enables statistically significant improvements in prospective classification accuracy (sensitivity), because of its ability to address variability in LIBS sample ablation and plasma self-absorption behavior. Furthermore, our results reveal that SVM provides nearly 10% improvement in correct allocation rate and a concomitant reduction in misclassification rates of 75% (cf. PLS-DA) and 80% (cf. SIMCA)-when measurements from samples not included in the training set are incorporated in the test data-highlighting its robustness. While further studies on a wider matrix of sample types performed using different LIBS systems is needed to fully characterize the capability of SVM to provide superior predictions, we anticipate that the improved sensitivity and robustness observed here will facilitate application of the proposed LIBS-SVM toolbox for screening drugs and detecting counterfeit samples, as well as in related areas of forensic and biological sample analysis.

Fluorescence and reflectance properties of hemoglobin-pigmented skin disorders

NASA Astrophysics Data System (ADS)

Troyanova, P.; Borisova, E.; Avramov, L.

2007-06-01

There has been growing interest in clinical application of laser-induced autofluorescence (LIAF) and reflectance spectroscopy (RS) to differentiate disease from normal surrounding tissue, including skin pathologies. Pigmented cutaneous lesions diagnosis plays important role in clinical practice, as malignant melanoma, which is characterized with greatest mortality from all skin cancer types, must be carefully discriminated form other colorized pathologies. The goals of this work were investigation of cutaneous hemoglobin-pigmented lesions (heamangioma, angiokeratoma, and fibroma) by the methods of LIAFS and RS. Spectra from healthy skin areas near to the lesion were detected to be used posteriori in analysis. Fluorescence and reflectance of cutaneous hemoglobin-pigmented lesions are used to develop criterion for differentiation from other pigmented pathologies. Origins of the spectral features obtained are discussed and determination of lesion types is achieved using selected spectral features. The spectral results, obtained were used to develop multispectral diagnostic algorithms based on the most prominent spectral features from the fluorescence and reflectance spectra of the lesions investigated. In comparison between normal skin and different cutaneous lesion types and between lesion types themselves sensitivities and specificities higher than 90 % were achieved. These results show a perspective possibility to differentiate hemoglobin-pigmented lesions from other pigmented pathologies using non-invasive and real time discrimination procedure.

Rapid discrimination of three Uighur medicine of Eremurus by FT-IR combined with 2DCOS-IR

NASA Astrophysics Data System (ADS)

Zhu, Yun; Xu, Chang-hua; Huang, Jian; Li, Guo-yu; Zhou, Qun; Liu, Xin-Hu; Sun, Su-qin; Wang, Jin-hui

2014-07-01

As complicated mixture systems, traditional Chinese medicines (TCMs) are difficult to be identified and discriminated, especially for the drug samples originated from the same source. In this study, a tri-step infrared spectroscopy method, i.e., conventional infrared spectroscopy (FT-IR) combined with second derivatives spectra and two-dimensional correlation infrared spectroscopy (2DCOS-IR), was employed to study and identify three Uighur drugs of Eremurus in Xinjiang, i.e. Eremurus altaicus (Pall.) Stev (AET), E. inderiensis (M.Bieb.)Regel(CB), E. anisopterus (Kar.et Kir.) Regel(YC). It was founded that the conventional IR spectra of the three species Eremurus were very similar based on the peak positions and shapes, indicating that the three had similar chemical profiles. On the basis of the different IR spectra of reference compounds and microscopic identification, the roots of YC, CB and AET all have comparable amount of calcium oxalate. The second derivative spectra of Eremurus enhanced the spectral resolution and amplified the small differences, especially at about 1468 cm-1, 1454 cm-1, and 1164 cm-1, and subsequently provided some dissimilarity in their calcium oxalate content. AET has relatively higher content of calcium oxalate but the lower content of anthraquinones. Moreover, the 2D-IR spectra revealed tiny differences among the three species by providing dynamic structural information of their chemical components in a more direct and visual way. The differences embodied mainly on the intensity of the auto-peaks at 971 cm-1, 1008 cm-1, 1468 cm-1 and 1578 cm-1. As a result, it was demonstrated that the macroscopic IR fingerprint method could discriminate the three similar Uighur drugs, YC, CB and AET.

Raman imaging at biological interfaces: applications in breast cancer diagnosis.

PubMed

Surmacki, Jakub; Musial, Jacek; Kordek, Radzislaw; Abramczyk, Halina

2013-05-24

One of the most important areas of Raman medical diagnostics is identification and characterization of cancerous and noncancerous tissues. The methods based on Raman scattering has shown significant potential for probing human breast tissue to provide valuable information for early diagnosis of breast cancer. A vibrational fingerprint from the biological tissue provides information which can be used to identify, characterize and discriminate structures in breast tissue, both in the normal and cancerous environment. The paper reviews recent progress in understanding structure and interactions at biological interfaces of the human tissue by using confocal Raman imaging and IR spectroscopy. The important differences between the noncancerous and cancerous human breast tissues were found in regions characteristic for vibrations of carotenoids, fatty acids, proteins, and interfacial water. Particular attention was paid to the role played by unsaturated fatty acids and their derivatives as well as carotenoids and interfacial water. We demonstrate that Raman imaging has reached a clinically relevant level in regard to breast cancer diagnosis applications. The results presented in the paper may have serious implications on understanding mechanisms of interactions in living cells under realistically crowded conditions of biological tissue.

Habits with killer instincts: in vivo analysis on the severity of oral mucosal alterations using autofluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Nazeer Shaiju, S.; Ariya, Saraswathy; Asish, Rajasekharan; Salim Haris, Padippurakkakath; Anita, Balan; Arun Kumar, Gupta; Jayasree, Ramapurath S.

2011-08-01

Oral habits like chewing and smoking are main causes of oral cancer, which has a higher mortality rate than many other cancer forms. Currently, the long term survival rate of oral cancer is less than 50%, as a majority of cases are detected very late. The clinician's main challenge is to differentiate among a multitude of red, white, or ulcerated lesions. Hence, new noninvasive, reliable, and fast techniques for the discrimination of oral cavity disorders are to be developed. This study includes autofluorescence spectroscopic screening of normal volunteers with and without lifestyle oral habits and patients with oral submucous fibrosis (OSF). The spectra from different sites of habitués, non-habitués, and OSF patients were analyzed using the intensity ratio, redox ratio, and linear discriminant analysis (LDA). The spectral disparities among these groups are well demonstrated in the emission regions of collagen and Flavin adenine dinucleotide. We observed that LDA gives better efficiency of classification than the intensity ratio technique. Even the differentiation of habitués and non-habitués could be well established with LDA. The study concludes that the clinical application of autofluorescence spectroscopy along with LDA, yields spontaneous screening among individuals, facilitating better patient management for clinicians and better quality of life for patients.

In vivo Raman spectroscopic identification of premalignant lesions in oral buccal mucosa

NASA Astrophysics Data System (ADS)

Singh, S. P.; Deshmukh, Atul; Chaturvedi, Pankaj; Murali Krishna, C.

2012-10-01

Cancers of oral cavities are one of the most common malignancies in India and other south-Asian countries. Tobacco habits are the main etiological factors for oral cancer. Identification of premalignant lesions is required for improving survival rates related to oral cancer. Optical spectroscopy methods are projected as alternative/adjunct for cancer diagnosis. Earlier studies have demonstrated the feasibility of classifying normal, premalignant, and malignant oral ex-vivo tissues. We intend to evaluate potentials of Raman spectroscopy in detecting premalignant conditions. Spectra were recorded from premalignant patches, contralateral normal (opposite to tumor site), and cancerous sites of subjects with oral cancers and also from age-matched healthy subjects with and without tobacco habits. A total of 861 spectra from 104 subjects were recorded using a fiber-optic probe-coupled HE-785 Raman spectrometer. Spectral differences in the 1200- to 1800-cm-1 region were subjected to unsupervised principal component analysis and supervised linear discriminant analysis followed by validation with leave-one-out and an independent test data set. Results suggest that premalignant conditions can be objectively discriminated with both normal and cancerous sites as well as from healthy controls with and without tobacco habits. Findings of the study further support efficacy of Raman spectroscopic approaches in oral-cancer applications.

Multivariate Analysis of Combined Fourier Transform Near-Infrared Spectrometry (FT-NIR) and Raman Datasets for Improved Discrimination of Drying Oils.

PubMed

Carlesi, Serena; Ricci, Marilena; Cucci, Costanza; La Nasa, Jacopo; Lofrumento, Cristiana; Picollo, Marcello; Becucci, Maurizio

2015-07-01

This work explores the application of chemometric techniques to the analysis of lipidic paint binders (i.e., drying oils) by means of Raman and near-infrared spectroscopy. These binders have been widely used by artists throughout history, both individually and in mixtures. We prepared various model samples of the pure binders (linseed, poppy seed, and walnut oils) obtained from different manufacturers. These model samples were left to dry and then characterized by Raman and reflectance near-infrared spectroscopy. Multivariate analysis was performed by applying principal component analysis (PCA) on the first derivative of the corresponding Raman spectra (1800-750 cm(-1)), near-infrared spectra (6000-3900 cm(-1)), and their combination to test whether spectral differences could enable samples to be distinguished on the basis of their composition. The vibrational bands we found most useful to discriminate between the different products we studied are the fundamental ν(C=C) stretching and methylenic stretching and bending combination bands. The results of the multivariate analysis demonstrated the potential of chemometric approaches for characterizing and identifying drying oils, and also for gaining a deeper insight into the aging process. Comparison with high-performance liquid chromatography data was conducted to check the PCA results.

Toward the development of Raman spectroscopy as a nonperturbative online monitoring tool for gasoline adulteration.

PubMed

Tan, Khay M; Barman, Ishan; Dingari, Narahara C; Singh, Gajendra P; Chia, Tet F; Tok, Wee L

2013-02-05

There is a critical need for a real-time, nonperturbative probe for monitoring the adulteration of automotive gasoline. Running on adulterated fuel leads to a substantive increase in air pollution, because of increased tailpipe emissions of harmful pollutants, as well as a reduction in engine performance. Consequently, both classification of the gasoline type and quantification of the adulteration content are of great significance for quality control. Gasoline adulteration detection is currently carried out in the laboratory with gas chromatography, which is time-consuming and costly. Here, we propose the application of Raman spectroscopic measurements for on-site rapid detection of gasoline adulteration. In this proof-of-principle report, we demonstrate the effectiveness of Raman spectra, in conjunction with multivariate analysis methods, in classifying the base oil types and simultaneously detecting the adulteration content in a wide range of commercial gasoline mixtures, both in their native states and spiked with different adulterants. In particular, we show that Raman spectra acquired with an inexpensive noncooled detector provides adequate specificity to clearly discriminate between the gasoline samples and simultaneously characterize the specific adulterant content with a limit of detection below 5%. Our promising results in this study illustrate, for the first time, the capability and the potential of Raman spectroscopy, together with multivariate analysis, as a low-cost, powerful tool for on-site rapid detection of gasoline adulteration and opens substantive avenues for applications in related fields of quality control in the oil industry.

Assessment of the discrimination of animal fat by FT-Raman spectroscopy

NASA Astrophysics Data System (ADS)

Abbas, O.; Fernández Pierna, J. A.; Codony, R.; von Holst, C.; Baeten, V.

2009-04-01

In recent years, there has been an increased attention towards the composition of feeding fats. In the aftermath of the BSE crisis all animal by-products utilised in animal nutrition have been subjected to close scrutiny. Regulation requires that the material belongs to the category of animal by-products fit for human consumption. This implies the use of reliable techniques in order to insure the safety of products. The feasibility of using rapid and non-destructive methods, to control the composition of feedstuffs on animal fats has been studied. Fourier Transform Raman spectroscopy has been chosen for its advantage to give detailed structural information. Data were treated using chemometric methods as PCA and PLS-DA which have permitted to separate well the different classes of animal fats. The same methodology was applied on fats from various types of feedstock and production technology processes. PLS-DA model for the discrimination of animal fats from the other categories presents a sensitivity and a specificity of 0.958 and 0.914, respectively. These results encourage the use of FT-Raman spectroscopy to discriminate animal fats.

Discrimination of three Pegaga (Centella) varieties and determination of growth-lighting effects on metabolites content based on the chemometry of 1H nuclear magnetic resonance spectroscopy.

PubMed

H, Maulidiani; Khatib, Alfi; Shaari, Khozirah; Abas, Faridah; Shitan, Mahendran; Kneer, Ralf; Neto, Victor; Lajis, Nordin H

2012-01-11

The metabolites of three species of Apiaceae, also known as Pegaga, were analyzed utilizing (1)H NMR spectroscopy and multivariate data analysis. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) resolved the species, Centella asiatica, Hydrocotyle bonariensis, and Hydrocotyle sibthorpioides, into three clusters. The saponins, asiaticoside and madecassoside, along with chlorogenic acids were the metabolites that contributed most to the separation. Furthermore, the effects of growth-lighting condition to metabolite contents were also investigated. The extracts of C. asiatica grown in full-day light exposure exhibited a stronger radical scavenging activity and contained more triterpenes (asiaticoside and madecassoside), flavonoids, and chlorogenic acids as compared to plants grown in 50% shade. This study established the potential of using a combination of (1)H NMR spectroscopy and multivariate data analyses in differentiating three closely related species and the effects of growth lighting, based on their metabolite contents and identification of the markers contributing to their differences.

Discrimination of tomatoes bred by spaceflight mutagenesis using visible/near infrared spectroscopy and chemometrics.

PubMed

Shao, Yongni; Xie, Chuanqi; Jiang, Linjun; Shi, Jiahui; Zhu, Jiajin; He, Yong

2015-04-05

Visible/near infrared spectroscopy (Vis/NIR) based on sensitive wavelengths (SWs) and chemometrics was proposed to discriminate different tomatoes bred by spaceflight mutagenesis from their leafs or fruits (green or mature). The tomato breeds were mutant M1, M2 and their parent. Partial least squares (PLS) analysis and least squares-support vector machine (LS-SVM) were implemented for calibration models. PLS analysis was implemented for calibration models with different wavebands including the visible region (400-700 nm) and the near infrared region (700-1000 nm). The best PLS models were achieved in the visible region for the leaf and green fruit samples and in the near infrared region for the mature fruit samples. Furthermore, different latent variables (4-8 LVs for leafs, 5-9 LVs for green fruits, and 4-9 LVs for mature fruits) were used as inputs of LS-SVM to develop the LV-LS-SVM models with the grid search technique and radial basis function (RBF) kernel. The optimal LV-LS-SVM models were achieved with six LVs for the leaf samples, seven LVs for green fruits, and six LVs for mature fruits, respectively, and they outperformed the PLS models. Moreover, independent component analysis (ICA) was executed to select several SWs based on loading weights. The optimal LS-SVM model was achieved with SWs of 550-560 nm, 562-574 nm, 670-680 nm and 705-71 5 nm for the leaf samples; 548-556 nm, 559-564 nm, 678-685 nm and 962-974 nm for the green fruit samples; and 712-718 nm, 720-729 nm, 968-978 nm and 820-830 nm for the mature fruit samples. All of them had better performance than PLS and LV-LS-SVM, with the parameters of correlation coefficient (rp), root mean square error of prediction (RMSEP) and bias of 0.9792, 0.2632 and 0.0901 based on leaf discrimination, 0.9837, 0.2783 and 0.1758 based on green fruit discrimination, 0.9804, 0.2215 and -0.0035 based on mature fruit discrimination, respectively. The overall results indicated that ICA was an effective way for the selection of SWs, and the Vis/NIR combined with LS-SVM models had the capability to predict the different breeds (mutant M1, mutant M2 and their parent) of tomatoes from leafs and fruits. Copyright © 2015 Elsevier B.V. All rights reserved.

Diagnosing clean margins through Raman spectroscopy in human and animal mammary tumour surgery: a short review

PubMed Central

Birtoiu, I. A.; Rizea, C.; Togoe, D.; Munteanu, R. M.; Micsa, C.; Rusu, M. I.; Tautan, M.; Braic, L.; Scoicaru, L. O.; Parau, A.; Becherescu-Barbu, N. D.; Udrea, M. V.; Tonetto, A.; Notonier, R.

2016-01-01

Breast cancer frequency in human and other mammal female populations has worryingly increased lately. The acute necessity for taxonomy of the aetiological factors along with seeking for new diagnostic tools and therapy procedures aimed at reducing mortality have yielded in an intense research effort worldwide. Surgery is a regular method to counteract extensive development of breast cancer and prevent metastases provided that negative surgical margins are achieved. This highly technical challenge requires fast, extremely sensitive and selective discrimination between malignant and benign tissues even down to molecular level. The particular advantages of Raman spectroscopy, such as high chemical specificity, and the ability to measure raw samples and optical responses in the visible or near-infrared spectral range, have recently recommended it as a means with elevated potential in precise diagnostic in oncology surgery. This review spans mainly the latter 10 years of exceptional efforts of scientists implementing Raman spectroscopy as a nearly real-time diagnostic tool for clean margins assessment in mastectomy and lumpectomy. Although greatly contributing to medical discoveries for the wealth of humanity, animals as patients have benefitted less from advances in surgery diagnostic using Raman spectroscopy. This work also dedicates a few lines to applications of surface enhanced Raman spectroscopy in veterinary oncological surgery. PMID:27920899

Application of inorganic element ratios to chemometrics for determination of the geographic origin of welsh onions.

PubMed

Ariyama, Kaoru; Horita, Hiroshi; Yasui, Akemi

2004-09-22

The composition of concentration ratios of 19 inorganic elements to Mg (hereinafter referred to as 19-element/Mg composition) was applied to chemometric techniques to determine the geographic origin (Japan or China) of Welsh onions (Allium fistulosum L.). Using a composition of element ratios has the advantage of simplified sample preparation, and it was possible to determine the geographic origin of a Welsh onion within 2 days. The classical technique based on 20 element concentrations was also used along with the new simpler one based on 19 elements/Mg in order to validate the new technique. Twenty elements, Na, P, K, Ca, Mg, Mn, Fe, Cu, Zn, Sr, Ba, Co, Ni, Rb, Mo, Cd, Cs, La, Ce, and Tl, in 244 Welsh onion samples were analyzed by flame atomic absorption spectroscopy, inductively coupled plasma atomic emission spectrometry, and inductively coupled plasma mass spectrometry. Linear discriminant analysis (LDA) on 20-element concentrations and 19-element/Mg composition was applied to these analytical data, and soft independent modeling of class analogy (SIMCA) on 19-element/Mg composition was applied to these analytical data. The results showed that techniques based on 19-element/Mg composition were effective. LDA, based on 19-element/Mg composition for classification of samples from Japan and from Shandong, Shanghai, and Fujian in China, classified 101 samples used for modeling 97% correctly and predicted another 119 samples excluding 24 nonauthentic samples 93% correctly. In discriminations by 10 times of SIMCA based on 19-element/Mg composition modeled using 101 samples, 220 samples from known production areas including samples used for modeling and excluding 24 nonauthentic samples were predicted 92% correctly.

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy.

PubMed

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. The results showed that 86.0% ([Formula: see text]) of participants can be correctly classified in leave-one-out cross-validation. The most discriminative brain regions included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex. This study demonstrated that, in a small sample, multivariate pattern analysis can effectively identify ADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

Determination of the Characteristics and Classification of Near-Infrared Spectra of Patchouli Oil (Pogostemon Cablin Benth.) from Different Origin

NASA Astrophysics Data System (ADS)

Diego, M. C. R.; Purwanto, Y. A.; Sutrisno; Budiastra, I. W.

2018-05-01

Research related to the non-destructive method of near-infrared (NIR) spectroscopy in aromatic oil is still in development in Indonesia. The objectives of the study were to determine the characteristics of the near-infrared spectra of patchouli oil and classify it based on its origin. The samples were selected from seven different places in Indonesia (Bogor and Garut from West Java, Aceh, and Jambi from Sumatra and Konawe, Masamba and Kolaka from Sulawesi Island). The spectral data of patchouli oil was obtained by FT-NIR spectrometer at the wavelength of 1000-2500 nm, and after that, the samples were subjected to composition analysis using Gas Chromatography-Mass Spectrometry. The transmittance and absorbance spectra were analyzed and then principal component analysis (PCA) was carried out. Discriminant analysis (DA) of the principal component was developed to classify patchouli oil based on its origin. The result shows that the data of both spectra (transmittance and absorbance spectra) by the PC analysis give a similar result for discriminating the seven types of patchouli oil due to their distribution and behavior. The DA of the three principal component in both data processed spectra could classify patchouli oil accurately. This result exposed that NIR spectroscopy can be successfully used as a correct method to classify patchouli oil based on its origin.

Student Discrimination in Higher Education: A Review of the Law.

ERIC Educational Resources Information Center

Sherman, Morton; Zirkel, Perry

1980-01-01

Surveys legal developments in the area of discrimination against students in higher education. Under the heading of the class (such as race, sex, or handicap) affected, constitutional, statutory, and administrative bases are described along with applicable judicial decisions. (Author/IRT)

Analytical Applications Of High-Resolution Molecular Fluorescence Spectroscopy In Low Temperature Solid Matrices

NASA Astrophysics Data System (ADS)

Hofstraat, Johannes W.; van Zeijl, W. J.; Smedes, F.; Ariese, Freek; Gooijer, Cees; Velthorst, Nel H.; Locher, R.; Renn, Alois; Wild, Urs P.

1989-05-01

High-resolution fluorescence spectroscopy may be used to obtain highly specific, vibrationally resolved spectral signatures of molecules. Two techniques are presented that both make use of low temperature, solid matrices. In Shpol'skii spectroscopy highly resolved spectra are obtained by employing n-alkanes as solvents that form neat crystalline matrices at low temperatures in which the guest molecules occupy well defined substitutional sites. Fluorescence line-narrowing spectroscopy is based on the application of selective (mostly laser-) excitation of the guest molecules. Principles and analytical applications of both techniques will be discussed. Specific attention will be paid to the determination of pyrene in bird meat by means of Shpol'skii spectroscopy and to the possibilities of applying two-dimensional fluorescence line-narrowing spectroscopy.

Hyperspectral imaging for diagnosis and quality control in agri-food and industrial sectors

NASA Astrophysics Data System (ADS)

García-Allende, P. Beatriz; Conde, Olga M.; Mirapeix, Jesus; Cobo, Adolfo; Lopez-Higuera, Jose M.

2010-04-01

Optical spectroscopy has been utilized in various fields of science, industry and medicine, since each substance is discernible from all others by its spectral properties. However, optical spectroscopy traditionally generates information on the bulk properties of the whole sample, and mainly in the agri-food industry some product properties result from the heterogeneity in its composition. This monitoring is considerably more challenging and can be successfully achieved by the so-called hyperspectral imaging technology, which allows the simultaneous determination of the optical spectrum and the spatial location of an object in a surface. In addition, it is a nonintrusive and non-contact technique which gives rise to a great potential for industrial applications and it does not require any particular preparation of the samples, which is a primary concern in food monitoring. This work illustrates an overview of approaches based on this technology to address different problems in agri-food and industrial sectors. The hyperspectral system was originally designed and tested for raw material on-line discrimination, which is a key factor in the input stages of many industrial sectors. The combination of the acquisition of the spectral information across transversal lines while materials are being transported on a conveyor belt, and appropriate image analyses have been successfully validated in the tobacco industry. Lastly, the use of imaging spectroscopy applied to online welding quality monitoring is discussed and compared with traditional spectroscopic approaches in this regard.

Geographic identification of Boletus mushrooms by data fusion of FT-IR and UV spectroscopies combined with multivariate statistical analysis

NASA Astrophysics Data System (ADS)

Yao, Sen; Li, Tao; Li, JieQing; Liu, HongGao; Wang, YuanZhong

2018-06-01

Boletus griseus and Boletus edulis are two well-known wild-grown edible mushrooms which have high nutrition, delicious flavor and high economic value distributing in Yunnan Province. In this study, a rapid method using Fourier transform infrared (FT-IR) and ultraviolet (UV) spectroscopies coupled with data fusion was established for the discrimination of Boletus mushrooms from seven different geographical origins with pattern recognition method. Initially, the spectra of 332 mushroom samples obtained from the two spectroscopic techniques were analyzed individually and then the classification performance based on data fusion strategy was investigated. Meanwhile, the latent variables (LVs) of FT-IR and UV spectra were extracted by partial least square discriminant analysis (PLS-DA) and two datasets were concatenated into a new matrix for data fusion. Then, the fusion matrix was further analyzed by support vector machine (SVM). Compared with single spectroscopic technique, data fusion strategy can improve the classification performance effectively. In particular, the accuracy of correct classification of SVM model in training and test sets were 99.10% and 100.00%, respectively. The results demonstrated that data fusion of FT-IR and UV spectra can provide higher synergic effect for the discrimination of different geographical origins of Boletus mushrooms, which may be benefit for further authentication and quality assessment of edible mushrooms.

Geographic identification of Boletus mushrooms by data fusion of FT-IR and UV spectroscopies combined with multivariate statistical analysis.

PubMed

Yao, Sen; Li, Tao; Li, JieQing; Liu, HongGao; Wang, YuanZhong

2018-06-05

Boletus griseus and Boletus edulis are two well-known wild-grown edible mushrooms which have high nutrition, delicious flavor and high economic value distributing in Yunnan Province. In this study, a rapid method using Fourier transform infrared (FT-IR) and ultraviolet (UV) spectroscopies coupled with data fusion was established for the discrimination of Boletus mushrooms from seven different geographical origins with pattern recognition method. Initially, the spectra of 332 mushroom samples obtained from the two spectroscopic techniques were analyzed individually and then the classification performance based on data fusion strategy was investigated. Meanwhile, the latent variables (LVs) of FT-IR and UV spectra were extracted by partial least square discriminant analysis (PLS-DA) and two datasets were concatenated into a new matrix for data fusion. Then, the fusion matrix was further analyzed by support vector machine (SVM). Compared with single spectroscopic technique, data fusion strategy can improve the classification performance effectively. In particular, the accuracy of correct classification of SVM model in training and test sets were 99.10% and 100.00%, respectively. The results demonstrated that data fusion of FT-IR and UV spectra can provide higher synergic effect for the discrimination of different geographical origins of Boletus mushrooms, which may be benefit for further authentication and quality assessment of edible mushrooms. Copyright © 2018 Elsevier B.V. All rights reserved.

Diagnosis of human malignancies using laser-induced breakdown spectroscopy in combination with chemometric methods

NASA Astrophysics Data System (ADS)

Chen, Xue; Li, Xiaohui; Yu, Xin; Chen, Deying; Liu, Aichun

2018-01-01

Diagnosis of malignancies is a challenging clinical issue. In this work, we present quick and robust diagnosis and discrimination of lymphoma and multiple myeloma (MM) using laser-induced breakdown spectroscopy (LIBS) conducted on human serum samples, in combination with chemometric methods. The serum samples collected from lymphoma and MM cancer patients and healthy controls were deposited on filter papers and ablated with a pulsed 1064 nm Nd:YAG laser. 24 atomic lines of Ca, Na, K, H, O, and N were selected for malignancy diagnosis. Principal component analysis (PCA), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and k nearest neighbors (kNN) classification were applied to build the malignancy diagnosis and discrimination models. The performances of the models were evaluated using 10-fold cross validation. The discrimination accuracy, confusion matrix and receiver operating characteristic (ROC) curves were obtained. The values of area under the ROC curve (AUC), sensitivity and specificity at the cut-points were determined. The kNN model exhibits the best performances with overall discrimination accuracy of 96.0%. Distinct discrimination between malignancies and healthy controls has been achieved with AUC, sensitivity and specificity for healthy controls all approaching 1. For lymphoma, the best discrimination performance values are AUC = 0.990, sensitivity = 0.970 and specificity = 0.956. For MM, the corresponding values are AUC = 0.986, sensitivity = 0.892 and specificity = 0.994. The results show that the serum-LIBS technique can serve as a quick, less invasive and robust method for diagnosis and discrimination of human malignancies.

Multimodal fiber-probe spectroscopy for the diagnostics and classification of bladder tumors

NASA Astrophysics Data System (ADS)

Anand, Suresh; Cicchi, Riccardo; Fantechi, Riccardo; Gacci, Mauro; Nesi, Gabriella; Carini, Marco; Pavone, Francesco S.

2017-02-01

The gold standard for the detection of bladder cancer is white light cystoscopy, followed by an invasive biopsy and pathological examination. Tissue pathology is time consuming and often prone to sampling errors. Recently, optical spectroscopy techniques have evolved as promising techniques for the detection of neoplasia. The specific goal of this study is to evaluate the application of combined auto-fluorescence (excited using 378 nm and 445 nm wavelengths) and diffuse reflectance spectroscopy to discriminate normal bladder tissue from tumor at different grades. The fluorescence spectrum at both excitation wavelengths showed an increased spectral intensity in tumors with respect to normal tissues. Reflectance data indicated an increased reflectance in the wavelength range 610 nm - 700 nm for different grades of tumors, compared to normal tissues. The spectral data were further analyzed using principal component analysis for evaluating the sensitivity and specificity for diagnosing tumor. The spectral differences observed between various grades of tumors provides a strong genesis for the future evaluation on a larger patient population to achieve statistical significance. This study indicates that a combined spectroscopic strategy, incorporating fluorescence and reflectance spectroscopy, could improve the capability for diagnosing bladder tumor as well as for differentiating tumors in different grades.

Spectral discrimination of serum from liver cancer and liver cirrhosis using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Yang, Tianyue; Li, Xiaozhou; Yu, Ting; Sun, Ruomin; Li, Siqi

2011-07-01

In this paper, Raman spectra of human serum were measured using Raman spectroscopy, then the spectra was analyzed by multivariate statistical methods of principal component analysis (PCA). Then linear discriminant analysis (LDA) was utilized to differentiate the loading score of different diseases as the diagnosing algorithm. Artificial neural network (ANN) was used for cross-validation. The diagnosis sensitivity and specificity by PCA-LDA are 88% and 79%, while that of the PCA-ANN are 89% and 95%. It can be seen that modern analyzing method is a useful tool for the analysis of serum spectra for diagnosing diseases.

The effect of bacterial environmental and metabolic stresses on a laser-induced breakdown spectroscopy (LIBS) based identification of Escherichia coli and Streptococcus viridans.

PubMed

Mohaidat, Qassem; Palchaudhuri, Sunil; Rehse, Steven J

2011-04-01

In this paper we investigate the effect that adverse environmental and metabolic stresses have on the laser-induced breakdown spectroscopy (LIBS) identification of bacterial specimens. Single-pulse LIBS spectra were acquired from a non-pathogenic strain of Escherichia coli cultured in two different nutrient media: a trypticase soy agar and a MacConkey agar with a 0.01% concentration of deoxycholate. A chemometric discriminant function analysis showed that the LIBS spectra acquired from bacteria grown in these two media were indistinguishable and easily discriminated from spectra acquired from two other non-pathogenic E. coli strains. LIBS spectra were obtained from specimens of a nonpathogenic E. coli strain and an avirulent derivative of the pathogen Streptococcus viridans in three different metabolic situations: live bacteria reproducing in the log-phase, bacteria inactivated on an abiotic surface by exposure to bactericidal ultraviolet irradiation, and bacteria killed via autoclaving. All bacteria were correctly identified regardless of their metabolic state. This successful identification suggests the possibility of testing specimens that have been rendered safe for handling prior to LIBS identification. This would greatly enhance personnel safety and lower the cost of a LIBS-based diagnostic test. LIBS spectra were obtained from pathogenic and non-pathogenic bacteria that were deprived of nutrition for a period of time ranging from one day to nine days by deposition on an abiotic surface at room temperature. All specimens were successfully classified by species regardless of the duration of nutrient deprivation. © 2011 Society for Applied Spectroscopy

Discrimination of Aspergillus lentulus from Aspergillus fumigatus by Raman spectroscopy and MALDI-TOF MS.

PubMed

Verwer, P E B; van Leeuwen, W B; Girard, V; Monnin, V; van Belkum, A; Staab, J F; Verbrugh, H A; Bakker-Woudenberg, I A J M; van de Sande, W W J

2014-02-01

In 2005, a new sibling species of Aspergillus fumigatus was discovered: Aspergillus lentulus. Both species can cause invasive fungal disease in immune-compromised patients. The species are morphologically very similar. Current techniques for identification are PCR-based or morphology-based. These techniques are labour-intense and not sufficiently discriminatory. Since A. lentulus is less susceptible to several antifungal agents, it is important to correctly identify the causative infectious agent in order to optimize antifungal therapy. In this study we determined whether Raman spectroscopy and/or MALDI-TOF MS were able to differentiate between A. lentulus and A. fumigatus. For 16 isolates of A. lentulus and 16 isolates of A. fumigatus, Raman spectra and peptide profiles were obtained using the Spectracell and MALDI-TOF MS (VITEK MS RUO, bioMérieux) respectively. In order to obtain reliable Raman spectra for A. fumigatus and A. lentulus, the culture medium needed to be adjusted to obtain colourless conidia. Only Raman spectra obtained from colourless conidia were reproducible and correctly identified 25 out of 32 (78 %) of the Aspergillus strains. For VITEK MS RUO, no medium adjustments were necessary. Pigmented conidia resulted in reproducible peptide profiles as well in this case. VITEK MS RUO correctly identified 100 % of the Aspergillus isolates, within a timeframe of approximately 54 h including culture. Of the two techniques studied here, VITEK MS RUO was superior to Raman spectroscopy in the discrimination of A. lentulus from A. fumigatus. VITEK MS RUO seems to be a successful technique in the daily identification of Aspergillus spp. within a limited timeframe.

Raman Spectroscopy and Chemometrics for Identification and Strain Discrimination of the Wine Spoilage Yeasts Saccharomyces cerevisiae, Zygosaccharomyces bailii, and Brettanomyces bruxellensis

PubMed Central

Thornton, Mark A.; Thornton, Roy J.

2013-01-01

The yeasts Zygosaccharomyces bailii, Dekkera bruxellensis (anamorph, Brettanomyces bruxellensis), and Saccharomyces cerevisiae are the major spoilage agents of finished wine. A novel method using Raman spectroscopy in combination with a chemometric classification tool has been developed for the identification of these yeast species and for strain discrimination of these yeasts. Raman spectra were collected for six strains of each of the yeasts Z. bailii, B. bruxellensis, and S. cerevisiae. The yeasts were classified with high sensitivity at the species level: 93.8% for Z. bailii, 92.3% for B. bruxellensis, and 98.6% for S. cerevisiae. Furthermore, we have demonstrated that it is possible to discriminate between strains of these species. These yeasts were classified at the strain level with an overall accuracy of 81.8%. PMID:23913433

Raman spectroscopy and chemometrics for identification and strain discrimination of the wine spoilage yeasts Saccharomyces cerevisiae, Zygosaccharomyces bailii, and Brettanomyces bruxellensis.

PubMed

Rodriguez, Susan B; Thornton, Mark A; Thornton, Roy J

2013-10-01

The yeasts Zygosaccharomyces bailii, Dekkera bruxellensis (anamorph, Brettanomyces bruxellensis), and Saccharomyces cerevisiae are the major spoilage agents of finished wine. A novel method using Raman spectroscopy in combination with a chemometric classification tool has been developed for the identification of these yeast species and for strain discrimination of these yeasts. Raman spectra were collected for six strains of each of the yeasts Z. bailii, B. bruxellensis, and S. cerevisiae. The yeasts were classified with high sensitivity at the species level: 93.8% for Z. bailii, 92.3% for B. bruxellensis, and 98.6% for S. cerevisiae. Furthermore, we have demonstrated that it is possible to discriminate between strains of these species. These yeasts were classified at the strain level with an overall accuracy of 81.8%.

DBSCAN-based ROI extracted from SAR images and the discrimination of multi-feature ROI

NASA Astrophysics Data System (ADS)

He, Xin Yi; Zhao, Bo; Tan, Shu Run; Zhou, Xiao Yang; Jiang, Zhong Jin; Cui, Tie Jun

2009-10-01

The purpose of the paper is to extract the region of interest (ROI) from the coarse detected synthetic aperture radar (SAR) images and discriminate if the ROI contains a target or not, so as to eliminate the false alarm, and prepare for the target recognition. The automatic target clustering is one of the most difficult tasks in the SAR-image automatic target recognition system. The density-based spatial clustering of applications with noise (DBSCAN) relies on a density-based notion of clusters which is designed to discover clusters of arbitrary shape. DBSCAN was first used in the SAR image processing, which has many excellent features: only two insensitivity parameters (radius of neighborhood and minimum number of points) are needed; clusters of arbitrary shapes which fit in with the coarse detected SAR images can be discovered; and the calculation time and memory can be reduced. In the multi-feature ROI discrimination scheme, we extract several target features which contain the geometry features such as the area discriminator and Radon-transform based target profile discriminator, the distribution characteristics such as the EFF discriminator, and the EM scattering property such as the PPR discriminator. The synthesized judgment effectively eliminates the false alarms.

47 CFR 22.321 - Equal employment opportunities.

Code of Federal Regulations, 2013 CFR

2013-10-01

... persons, and personnel must not be discriminated against in employment because of sex, race, color... qualified applicants without regard to sex, race, color, religion or national origin, and solicit their... prejudice or discrimination based upon sex, race, color, religion, or national origin, from the licensee's...

47 CFR 90.168 - Equal employment opportunities.

Code of Federal Regulations, 2012 CFR

2012-10-01

... persons, and personnel must not be discriminated against in employment because of sex, race, color... qualified applicants without regard to sex, race, color, religion or national origin, and solicit their... prejudice or discrimination based upon sex, race, color, religion, or national origin, from the licensee's...

47 CFR 22.321 - Equal employment opportunities.

Code of Federal Regulations, 2012 CFR

2012-10-01

... persons, and personnel must not be discriminated against in employment because of sex, race, color... qualified applicants without regard to sex, race, color, religion or national origin, and solicit their... prejudice or discrimination based upon sex, race, color, religion, or national origin, from the licensee's...

47 CFR 90.168 - Equal employment opportunities.

Code of Federal Regulations, 2013 CFR

2013-10-01

... persons, and personnel must not be discriminated against in employment because of sex, race, color... qualified applicants without regard to sex, race, color, religion or national origin, and solicit their... prejudice or discrimination based upon sex, race, color, religion, or national origin, from the licensee's...

47 CFR 22.321 - Equal employment opportunities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... persons, and personnel must not be discriminated against in employment because of sex, race, color... qualified applicants without regard to sex, race, color, religion or national origin, and solicit their... prejudice or discrimination based upon sex, race, color, religion, or national origin, from the licensee's...

47 CFR 22.321 - Equal employment opportunities.

Code of Federal Regulations, 2014 CFR

2014-10-01

... persons, and personnel must not be discriminated against in employment because of sex, race, color... qualified applicants without regard to sex, race, color, religion or national origin, and solicit their... prejudice or discrimination based upon sex, race, color, religion, or national origin, from the licensee's...

47 CFR 90.168 - Equal employment opportunities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... persons, and personnel must not be discriminated against in employment because of sex, race, color... qualified applicants without regard to sex, race, color, religion or national origin, and solicit their... prejudice or discrimination based upon sex, race, color, religion, or national origin, from the licensee's...

47 CFR 90.168 - Equal employment opportunities.

Code of Federal Regulations, 2014 CFR

2014-10-01

... persons, and personnel must not be discriminated against in employment because of sex, race, color... qualified applicants without regard to sex, race, color, religion or national origin, and solicit their... prejudice or discrimination based upon sex, race, color, religion, or national origin, from the licensee's...

Laser-induced breakdown spectroscopy in industrial and security applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bol'shakov, Alexander A.; Yoo, Jong H.; Liu Chunyi

2010-05-01

Laser-induced breakdown spectroscopy (LIBS) offers rapid, localized chemical analysis of solid or liquid materials with high spatial resolution in lateral and depth profiling, without the need for sample preparation. Principal component analysis and partial least squares algorithms were applied to identify a variety of complex organic and inorganic samples. This work illustrates how LIBS analyzers can answer a multitude of real-world needs for rapid analysis, such as determination of lead in paint and children's toys, analysis of electronic and solder materials, quality control of fiberglass panels, discrimination of coffee beans from different vendors, and identification of generic versus brand-name drugs.more » Lateral and depth profiling was performed on children's toys and paint layers. Traditional one-element calibration or multivariate chemometric procedures were applied for elemental quantification, from single laser shot determination of metal traces at {approx}10 {mu}g/g to determination of halogens at 90 {mu}g/g using 50-shot spectral accumulation. The effectiveness of LIBS for security applications was demonstrated in the field by testing the 50-m standoff LIBS rasterizing detector.« less

HR-MAS MR Spectroscopy of Breast Cancer Tissue Obtained with Core Needle Biopsy: Correlation with Prognostic Factors

PubMed Central

Choi, Ji Soo; Baek, Hyeon-Man; Kim, Suhkmann; Kim, Min Jung; Youk, Ji Hyun; Moon, Hee Jung; Kim, Eun-Kyung; Han, Kyung Hwa; Kim, Dong-hyun; Kim, Seung Il; Koo, Ja Seung

2012-01-01

The purpose of this study was to examine the correlation between high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopy using core needle biopsy (CNB) specimens and histologic prognostic factors currently used in breast cancer patients. After institutional review board approval and informed consent were obtained for this study, CNB specimens were collected from 36 malignant lesions in 34 patients. Concentrations and metabolic ratios of various choline metabolites were estimated by HR-MAS MR spectroscopy using CNB specimens. HR-MAS spectroscopic values were compared according to histopathologic variables [tumor size, lymph node metastasis, histologic grade, status of estrogens receptor (ER), progesterone receptor (PR), HER2 (a receptor for human epidermal growth factor), and Ki-67, and triple negativity]. Multivariate analysis was performed with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA). HR-MAS MR spectroscopy quantified and discriminated choline metabolites in all CNB specimens of the 36 breast cancers. Several metabolite markers [free choline (Cho), phosphocholine (PC), creatine (Cr), taurine, myo-inositol, scyllo-inositol, total choline (tCho), glycine, Cho/Cr, tCho/Cr, PC/Cr] on HR-MAS MR spectroscopy were found to correlate with histologic prognostic factors [ER, PR, HER2, histologic grade, triple negativity, Ki-67, poor prognosis]. OPLS-DA multivariate models were generally able to discriminate the status of histologic prognostic factors (ER, PR, HER2, Ki-67) and prognosis groups. Our study suggests that HR-MAS MR spectroscopy using CNB specimens can predict tumor aggressiveness prior to surgery in breast cancer patients. In addition, it may be helpful in the detection of reliable markers for breast cancer characterization. PMID:23272149

Study of n- γ discrimination by zero-crossing method with SiPM based scintillation detectors

NASA Astrophysics Data System (ADS)

Grodzicka-Kobylka, M.; Szczesniak, T.; Moszyński, M.; Swiderski, L.; Wolski, D.; Baszak, J.; Korolczuk, S.; Schotanus, P.

2018-03-01

The paper presents a study of n / γ discrimination with 4x4 ch and 8x8 ch Multi Pixel Photon Counter (MPPC) arrays in neutron detectors based on Stilbene and EJ299-33 plastic scintillators. The n / γ discrimination showed an excellent capability of the MPPC arrays, comparable to that observed earlier with the classical PMTs. Particularly, an application of a zero-crossing method of n - γ discrimination prevented deterioration of the discrimination by the slow response of the Silicon Photomultiplier (SiPM, or MPPC interchangeably) array related to its large capacitance. It was confirmed by a good agreement of the Figure of Merit normalized to the number of photoelectrons determined for the MPPC arrays and XP5500 PMT.

Spectral features of biogenic calcium carbonates and implications for astrobiology

NASA Astrophysics Data System (ADS)

Berg, B. L.; Ronholm, J.; Applin, D. M.; Mann, P.; Izawa, M.; Cloutis, E. A.; Whyte, L. G.

2014-09-01

The ability to discriminate biogenic from abiogenic calcium carbonate (CaCO3) would be useful in the search for extant or extinct life, since CaCO3 can be produced by both biotic and abiotic processes on Earth. Bioprecipitated CaCO3 material was produced during the growth of heterotrophic microbial isolates on medium enriched with calcium acetate or calcium citrate. These biologically produced CaCO3, along with natural and synthetic non-biologically produced CaCO3 samples, were analysed by reflectance spectroscopy (0.35-2.5 μm), Raman spectroscopy (532 and 785 nm), and laser-induced fluorescence spectroscopy (365 and 405 nm excitation). Optimal instruments for the discrimination of biogenic from abiogenic CaCO3 were determined to be reflectance spectroscopy, and laser-induced fluorescence spectroscopy. Multiple absorption features in the visible light region occurred in reflectance spectra for most biogenic CaCO3 samples, which are likely due to organic pigments. Multiple fluorescence peaks occurred in emission spectra (405 nm excitation) of biogenic CaCO3 samples, which also are best attributed to the presence of organic compounds; however, further analyses must be performed in order to better determine the cause of these features to establish criteria for confirming the origin of a given CaCO3 sample. Raman spectroscopy was not useful for discrimination since any potential Raman peaks in spectra of biogenic carbonates collected by both the 532 and 785 nm lasers were overwhelmed by fluorescence. However, this also suggests that biogenic carbonates may be identified by the presence of this organic-associated fluorescence. No reliable spectroscopic differences in terms of parameters such as positions or widths of carbonate-associated absorption bands were found between the biogenic and abiogenic carbonate samples. These results indicate that the presence or absence of organic matter intimately associated with carbonate minerals is the only potentially useful spectral discriminator for the techniques that were examined, and that multiple spectroscopic techniques are capable of detecting the presence of associated organic materials. However, the presence or absence of intimately associated organic matter is not, in itself, an indicator of biogenicity.

Vibrational structure of the polyunsaturated fatty acids eicosapentaenoic acid and arachidonic acid studied by infrared spectroscopy

NASA Astrophysics Data System (ADS)

Kiefer, Johannes; Noack, Kristina; Bartelmess, Juergen; Walter, Christian; Dörnenburg, Heike; Leipertz, Alfred

2010-02-01

The spectroscopic discrimination of the two structurally similar polyunsaturated C 20 fatty acids (PUFAs) 5,8,11,14,17-eicosapentaenoic acid and 5,8,11,14-eicosatetraenoic acid (arachidonic acid) is shown. For this purpose their vibrational structures are studied by means of attenuated total reflection (ATR) Fourier-transform infrared (FT-IR) spectroscopy. The fingerprint regions of the recorded spectra are found to be almost identical, while the C-H stretching mode regions around 3000 cm -1 show such significant differences as results of electronic and molecular structure alterations based on the different degree of saturation that both fatty acids can be clearly distinguished from each other.

Polarimetric SAR image classification based on discriminative dictionary learning model

NASA Astrophysics Data System (ADS)

Sang, Cheng Wei; Sun, Hong

2018-03-01

Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

Surface Optical Rectification from Layered MoS2 Crystal by THz Time-Domain Surface Emission Spectroscopy.

PubMed

Huang, Yuanyuan; Zhu, Lipeng; Zhao, Qiyi; Guo, Yaohui; Ren, Zhaoyu; Bai, Jintao; Xu, Xinlong

2017-02-08

Surface optical rectification was observed from the layered semiconductor molybdenum disulfide (MoS 2 ) crystal via terahertz (THz) time-domain surface emission spectroscopy under linearly polarized femtosecond laser excitation. The radiated THz amplitude of MoS 2 has a linear dependence on ever-increasing pump fluence and thus quadratic with the pump electric field, which discriminates from the surface Dember field induced THz radiation in InAs and the transient photocurrent-induced THz generation in graphite. Theoretical analysis based on space symmetry of MoS 2 crystal suggests that the underlying mechanism of THz radiation is surface optical rectification under the reflection configuration. This is consistent with the experimental results according to the radiated THz amplitude dependences on azimuthal and incident polarization angles. We also demonstrated the damage threshold of MoS 2 due to microscopic bond breaking under the femtosecond laser irradiation, which can be monitored via THz time-domain emission spectroscopy and Raman spectroscopy.

Applications of synchrotron-based spectroscopic techniques in studying nucleic acids and nucleic acid-functionalized nanomaterials

PubMed Central

Wu, Peiwen; Yu, Yang; McGhee, Claire E.; Tan, Li Huey

2014-01-01

In this review, we summarize recent progresses in the application of synchrotron-based spectroscopic techniques for nucleic acid research that takes advantage of high-flux and high-brilliance electromagnetic radiation from synchrotron sources. The first section of the review focuses on the characterization of the structure and folding processes of nucleic acids using different types of synchrotron-based spectroscopies, such as X-ray absorption spectroscopy, X-ray emission spectroscopy, X-ray photoelectron spectroscopy, synchrotron radiation circular dichroism, X-ray footprinting and small-angle X-ray scattering. In the second section, the characterization of nucleic acid-based nanostructures, nucleic acid-functionalized nanomaterials and nucleic acid-lipid interactions using these spectroscopic techniques is summarized. Insights gained from these studies are described and future directions of this field are also discussed. PMID:25205057

Applications of synchrotron-based spectroscopic techniques in studying nucleic acids and nucleic acid-functionalized nanomaterials

DOE PAGES

Wu, Peiwen; Yu, Yang; McGhee, Claire E.; ...

2014-09-10

In this paper, we summarize recent progress in the application of synchrotron-based spectroscopic techniques for nucleic acid research that takes advantage of high-flux and high-brilliance electromagnetic radiation from synchrotron sources. The first section of the review focuses on the characterization of the structure and folding processes of nucleic acids using different types of synchrotron-based spectroscopies, such as X-ray absorption spectroscopy, X-ray emission spectroscopy, X-ray photoelectron spectroscopy, synchrotron radiation circular dichroism, X-ray footprinting and small-angle X-ray scattering. In the second section, the characterization of nucleic acid-based nanostructures, nucleic acid-functionalized nanomaterials and nucleic acid-lipid interactions using these spectroscopic techniques is summarized. Insightsmore » gained from these studies are described and future directions of this field are also discussed.« less

Detection and identification of multiple adulterants in plant food supplements using attenuated total reflectance-Infrared spectroscopy.

PubMed

Deconinck, E; Aouadi, C; Bothy, J L; Courselle, P

2018-04-15

Due to the rising popularity of dietary supplements, especially plant food supplements, and alternative herbal medicines, a whole market developed and these products became freely available through internet. Though several searches revealed that at least a part of these products, especially the ones obtained from websites disclosing their physical identity, are aldulterated with pharmaceutical compounds. This causes a threat for public health, since these compounds are not declared and therefore adverse effects will not immediately be related to the product. The more the adulterants can interfere with other medicinal treatments. Since the present active pharmaceutical ingredients are not declared on the package and the products are sold as 100% natural or herbal in nature, it is very difficult for custom personnel to discriminate between products to be confiscated or not. Therefore easy to apply analytical approaches to discriminate between adulterated and non-adulterated products are necessary. This paper presents an approach based on infrared spectroscopy combined with attenuated total reflectance (ATR) and partial least squares- discriminant analysis (PLS-DA) to easily differentiate between adulterated and non- adulterated plant food supplements and to get a first idea of the nature of the adulterant present. The performance of PLS-DA models based on Mid-IR and NIR data were compared as well as models based on the combined data. Further three preprocessing strategies were compared. The best performance was obtained for a PLS-DA model using Mid-IR data with the second derivative as preprocessing method. This model showed a correct classification rate of 98.3% for an external test set. Also eight real samples were screened using the model and for seven of these samples a correct classification was obtained. Generally it could be concluded that the obtained model and the presented approach could be used at customs to discriminate between adulterated and non-adulterated herbal food supplements and even get a first idea of the nature of the adulterant present. The more the presented approach hardly needs sample preparation. Copyright © 2018 Elsevier B.V. All rights reserved.

Detection of Leukemia with Blood Samples Using Raman Spectroscopy and Multivariate Analysis

NASA Astrophysics Data System (ADS)

Martínez-Espinosa, J. C.; González-Solís, J. L.; Frausto-Reyes, C.; Miranda-Beltrán, M. L.; Soria-Fregoso, C.; Medina-Valtierra, J.

2009-06-01

The use of Raman spectroscopy to analyze blood biochemistry and hence distinguish between normal and abnormal blood was investigated. Blood samples were obtained from 6 patients who were clinically diagnosed with leukemia and 6 healthy volunteers. The imprint was put under the microscope and several points were chosen for Raman measurement. All the spectra were collected by a confocal Raman micro-spectroscopy (Renishaw) with a NIR 830 nm laser. It is shown that the serum samples from patients with leukemia and from the control group can be discriminated when the multivariate statistical methods of principal component analysis (PCA) and linear discriminated analysis (LDA) are applied to their Raman spectra. The ratios of some band intensities were analyzed and some band ratios were significant and corresponded to proteins, phospholipids, and polysaccharides. The preliminary results suggest that Raman Spectroscopy could be a new technique to study the degree of damage to the bone marrow using just blood samples instead of biopsies, treatment very painful for patients.

New approaches to the analysis of complex samples using fluorescence lifetime techniques and organized media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hertz, P.R.

Fluorescence spectroscopy is a highly sensitive and selective tool for the analysis of complex systems. In order to investigate the efficacy of several steady state and dynamic techniques for the analysis of complex systems, this work focuses on two types of complex, multicomponent samples: petrolatums and coal liquids. It is shown in these studies dynamic, fluorescence lifetime-based measurements provide enhanced discrimination between complex petrolatum samples. Additionally, improved quantitative analysis of multicomponent systems is demonstrated via incorporation of organized media in coal liquid samples. This research provides the first systematic studies of (1) multifrequency phase-resolved fluorescence spectroscopy for dynamic fluorescence spectralmore » fingerprinting of complex samples, and (2) the incorporation of bile salt micellar media to improve accuracy and sensitivity for characterization of complex systems. In the petroleum studies, phase-resolved fluorescence spectroscopy is used to combine spectral and lifetime information through the measurement of phase-resolved fluorescence intensity. The intensity is collected as a function of excitation and emission wavelengths, angular modulation frequency, and detector phase angle. This multidimensional information enhances the ability to distinguish between complex samples with similar spectral characteristics. Examination of the eigenvalues and eigenvectors from factor analysis of phase-resolved and steady state excitation-emission matrices, using chemometric methods of data analysis, confirms that phase-resolved fluorescence techniques offer improved discrimination between complex samples as compared with conventional steady state methods.« less

High-Throughput Metabolic Fingerprinting of Legume Silage Fermentations via Fourier Transform Infrared Spectroscopy and Chemometrics

PubMed Central

Johnson, Helen E.; Broadhurst, David; Kell, Douglas B.; Theodorou, Michael K.; Merry, Roger J.; Griffith, Gareth W.

2004-01-01

Silage quality is typically assessed by the measurement of several individual parameters, including pH, lactic acid, acetic acid, bacterial numbers, and protein content. The objective of this study was to use a holistic metabolic fingerprinting approach, combining a high-throughput microtiter plate-based fermentation system with Fourier transform infrared (FT-IR) spectroscopy, to obtain a snapshot of the sample metabolome (typically low-molecular-weight compounds) at a given time. The aim was to study the dynamics of red clover or grass silage fermentations in response to various inoculants incorporating lactic acid bacteria (LAB). The hyperspectral multivariate datasets generated by FT-IR spectroscopy are difficult to interpret visually, so chemometrics methods were used to deconvolute the data. Two-phase principal component-discriminant function analysis allowed discrimination between herbage types and different LAB inoculants and modeling of fermentation dynamics over time. Further analysis of FT-IR spectra by the use of genetic algorithms to identify the underlying biochemical differences between treatments revealed that the amide I and amide II regions (wavenumbers of 1,550 to 1,750 cm−1) of the spectra were most frequently selected (reflecting changes in proteins and free amino acids) in comparisons between control and inoculant-treated fermentations. This corresponds to the known importance of rapid fermentation for the efficient conservation of forage proteins. PMID:15006782

Rapid discrimination of cultivated Codonopsis lanceolata in different ages by FT-IR and 2DCOS-IR

NASA Astrophysics Data System (ADS)

Zhu, Yun; Xu, Chang-hua; Huang, Jian; Li, Guo-yu; Liu, Xin-Hu; Sun, Su-qin; Wang, Jin-hui

2014-07-01

Deodeok (Codonopsis lanceolata) root, a traditional Chinese herbal medicine, has been used to treat lung ailments, rheumatism, menstrual disturbance and bruises with a long history in China and some other Asian countries. In this study, four types of Deodeok with different growth years were discriminated and identified by a Tri-step infrared spectroscopy method (Fourier transform-infrared spectroscopy (conventional FT-IR) coupled with second derivative infrared spectroscopy (SD-IR) and two dimensional correlation infrared spectroscopy(2DCOS-IR) under thermal perturbation. Although only small differences were found in the FT-IR spectra of the samples, the positions and intensities of peaks around 1736, 1634, 1246, 1055, 1033, 818, 779 cm-1 could be considered as the key factors for discriminating them. The differences among them were amplified by their SD-IR spectra. The 2DCOS-IR spectra provided obvious dynamic chemical structure information of Deodeok samples, which present different particular auto peak clusters in the range of 875-1130 cm-1 and 1170-1630 cm-1, respectively. It was demonstrated that the content of triterpene were decreasing when C. lanceolata were growing older, but the relative content of saccharides initially increased and decreased significantly afterwards. It indicated a general trend that the content of polysaccharides accumulated with increasing years. Specifically, the content of polysaccharides accumulated in the root of 2-year-old plant was the lowest, 4-years-old was the highest, and then the content decreased gradually. Furthermore, according to the differences of locations and intensities of auto-peaks in 2D-IR spectra, the integral changes of components were revealed. This study offers a promising method inherent with cost-effective and time-saving to characterize and discriminate the complicated system like Deodeok.

Biochemical and molecular characterization of thyroid tissue by micro-Raman spectroscopy and gene expression analysis

NASA Astrophysics Data System (ADS)

Neto, Lázaro P. M.; Martin, Aírton A.; Soto, Claudio A. T.; Santos, André B. O.; Mello, Evandro S.; Pereira, Marina A.; Cernea, Cláudio R.; Brandão, Lenine G.; Canevari, Renata A.

2016-02-01

Thyroid carcinomas represent the main endocrine malignancy and their diagnosis may produce inconclusive results. Raman spectroscopy and gene expression analysis have shown excellent results on the differentiation of carcinomas. This study aimed to improve the discrimination between different thyroid pathologies combining of both analyses. A total of 35 thyroid tissues samples including normal tissue (n=10), goiter (n=10), papillary (n=10) and follicular carcinomas (n=5) were analyzed. Confocal Raman spectra was obtain by using a Rivers Diagnostic System, 785 nm laser excitation and CCD detector. The data was processed by the software Labspec5 and Origin 8.5 and analyzed by Minitab® program. The gene expression analysis was performed by qRT-PCR technique for TG, TPO, PDGFB, SERPINA1, LGALS3 and TFF3 genes and statistically analyzed by Mann-Whitney test. The confocal Raman spectroscopy allowed a maximum discrimination of 91.1% between normal and tumor tissues, 84.8% between benign and malignant pathologies and 84.6% among carcinomas analyzed. Significant differences was observed for TG, LGALS3, SERPINA1 and TFF3 genes between benign lesions and carcinomas, and SERPINA1 and TFF3 genes between papillary and follicular carcinomas. Principal component analysis was performed using PC1 and PC2 in the papillary carcinoma samples that showed over gene expression when compared with normal sample, where 90% of discrimination was observed at the Amide 1 (1655 cm-1), and at the tyrosine spectra region (856 cm-1). The discrimination of tissues thyroid carried out by confocal Raman spectroscopy and gene expression analysis indicate that these techniques are promising tools to be used in the diagnosis of thyroid lesions.

Combined elemental and microstructural analysis of genuine and fake copper-alloy coins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bartoli, L; Agresti, J; Mascalchi, M

2011-07-31

Innovative noninvasive material analysis techniques are applied to determine archaeometallurgical characteristics of copper-alloy coins from Florence's National Museum of Archaeology. Three supposedly authentic Roman coins and three hypothetically fraudolent imitations are thoroughly investigated using laser-induced plasma spectroscopy and time of flight neutron diffraction along with 3D videomicroscopy and electron microscopy. Material analyses are aimed at collecting data allowing for objective discrimination between genuine Roman productions and late fakes. The results show the mentioned techniques provide quantitative compositional and textural data, which are strictly related to the manufacturing processes and aging of copper alloys. (laser applications)

Fluorescence lifetime in cardiovascular diagnostics

PubMed Central

Marcu, Laura

2010-01-01

We review fluorescence lifetime techniques including time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) and fluorescence lifetime imaging microscopy (FLIM) instrumentation and associated methodologies that allow for characterization and diagnosis of atherosclerotic plaques. Emphasis is placed on the translational research potential of TR-LIFS and FLIM and on determining whether intrinsic fluorescence signals can be used to provide useful contrast for the diagnosis of high-risk atherosclerotic plaque. Our results demonstrate that these techniques allow for the discrimination of important biochemical features involved in atherosclerotic plaque instability and rupture and show their potential for future intravascular applications. PMID:20210432

Analysis of LIF-Raman spectroscopy for the diagnosis of normal and liver diseases

NASA Astrophysics Data System (ADS)

Li, Xiaozhou; Yang, Tianyue; Yu, Ting; Sun, Ruomin; Li, Siqi

2011-07-01

In this paper, 514.5nm argon ion laser induced human serum Raman and auto-fluorescence spectra of normal, liver cirrhosis and liver cancer were measured and analyzed. The spectral differences between these three types of serums were observed and given brief explanations. Three parameters α, φ and Δλ were introduced to describe characteristics of each type of spectrum. Experimental results showed that these parameters might be applicable for discrimination of normal, liver cirrhosis and liver cancer, which will provide some reference values to explore the method of laser spectral diagnosis of cancer.

Investigation of a fiber optic surface plasmon spectroscopy in conjunction with conductivity as an in situ method for simultaneously monitoring changes in dissolved organic carbon and salinity in coastal waters.

PubMed

Kim, Yoon-Chang; Cramer, Jeffrey A; Booksh, Karl S

2011-10-21

A combination surface plasmon resonance (SPR) and conductivity sensor array was developed and implemented to demonstrate the ability to differentiate among changes in dissolved organic carbon (DOC) and salinity in coastal water. The array is capable of achieving sufficient spatial and temporal data density to better understand the cycling and fate of terrestrial DOC in coastal areas. DOC is the second largest source of bioreactive carbon in the environment and plays a key role in mediating microbial activity and generation of atmospheric CO(2). In the coastal areas, the salinity is also an important property in many applications, such as leak detection for landfill liners, saltwater intrusion to drinking water, marine environment monitoring, and seasonal climate prediction. Conductivity sensors are the industry standard for determining salinity in ocean systems. However, both conductivity and refractive index sensors, such as SPR spectroscopy based sensors, respond to salinity and DOC levels. To demonstrate the capability of the SPR sensor and a conductivity sensor to collect complimentary data useful in discrimination of salinity and DOC in coastal zone water, conductivity, SPR, and temperature data were collected during passage from the Juan de Fuca ridge area returning to the University of Washington docks.

Detection and Classification of Live and Dead Escherichia coli by Laser-Induced Breakdown Spectroscopy

PubMed Central

Sivakumar, P.; Fernández-Bravo, A.; Taleh, L.; Biddle, J.F.

2015-01-01

Abstract A common goal for astrobiology is to detect organic materials that may indicate the presence of life. However, organic materials alone may not be representative of currently living systems. Thus, it would be valuable to have a method with which to determine the health of living materials. Here, we present progress toward this goal by reporting on the application of laser-induced breakdown spectroscopy (LIBS) to study characteristics of live and dead cells using Escherichia coli (E. coli) strain K12 cells as a model organism since its growth and death in the laboratory are well understood. Our goal is to determine whether LIBS, in its femto- and/or nanosecond forms, could ascertain the state of a living organism. E. coli strain K12 cells were grown, collected, and exposed to one of two types of inactivation treatments: autoclaving and sonication. Cells were also kept alive as a control. We found that LIBS yields key information that allows for the discrimination of live and dead E. coli bacteria based on ionic shifts reflective of cell membrane integrity. Key Words: E. coli—Trace elements—Live and dead cells—Laser-induced breakdown spectroscopy—Atomic force microscopy. Astrobiology 15, 144–153. PMID:25683088

Insights on diagnosis of oral cavity pathologies by infrared spectroscopy: A review

NASA Astrophysics Data System (ADS)

Giorgini, Elisabetta; Balercia, Paolo; Conti, Carla; Ferraris, Paolo; Sabbatini, Simona; Rubini, Corrado; Tosi, Giorgio

2013-11-01

Fourier-Transform Infrared microspectroscopy, a largely used spectroscopic technique in basic and industrial researches, offers the possibility to analyze the vibrational features of molecular groups within a variety of environments. In the bioclinical field, and, in particular, in the study of cells, tissues and biofluids, it could be considered a supporting objective technique able to characterize the biochemical processes involved in relevant pathologies, such as tumoral diseases, highlighting specific spectral markers associable with the principal biocomponents (proteins, lipids and carbohydrates). In this article, we review the applications of infrared spectroscopy to the study of tumoral diseases of oral cavity compartments with the aim to improve understanding of biological processes involved during the onset of these lesions and to afford to an early diagnosis. Spectral studies on mouth, salivary glands and oral cystic lesions, objectively discriminate normal from dysplastic and cancer states characterizing also the grading.

Rapid evaluation and quantitative analysis of thyme, origano and chamomile essential oils by ATR-IR and NIR spectroscopy

NASA Astrophysics Data System (ADS)

Schulz, Hartwig; Quilitzsch, Rolf; Krüger, Hans

2003-12-01

The essential oils obtained from various chemotypes of thyme, origano and chamomile species were studied by ATR/FT-IR as well as NIR spectroscopy. Application of multivariate statistics (PCA, PLS) in conjunction with analytical reference data leads to very good IR and NIR calibration results. For the main essential oil components (e.g. carvacrol, thymol, γ-terpinene, α-bisabolol and β-farnesene) standard errors are in the range of the applied GC reference method. In most cases the multiple coefficients of determination ( R2) are >0.97. Using the IR fingerprint region (900-1400 cm -1) a qualitative discrimination of the individual chemotypes is possible already by visual judgement without to apply any chemometric algorithms.The described rapid and non-destructive methods can be applied in industry to control very easily purifying, blending and redistillation processes of the mentioned essential oils.

Micro-Raman spectroscopy of natural and synthetic indigo samples.

PubMed

Vandenabeele, Peter; Moens, Luc

2003-02-01

In this work indigo samples from three different sources are studied by using Raman spectroscopy: the synthetic pigment and pigments from the woad (Isatis tinctoria) and the indigo plant (Indigofera tinctoria). 21 samples were obtained from 8 suppliers; for each sample 5 Raman spectra were recorded and used for further chemometrical analysis. Principal components analysis (PCA) was performed as data reduction method before applying hierarchical cluster analysis. Linear discriminant analysis (LDA) was implemented as a non-hierarchical supervised pattern recognition method to build a classification model. In order to avoid broad-shaped interferences from the fluorescence background, the influence of 1st and 2nd derivatives on the classification was studied by using cross-validation. Although chemically identical, it is shown that Raman spectroscopy in combination with suitable chemometric methods has the potential to discriminate between synthetic and natural indigo samples.

Authentication of the botanical origin of honey by near-infrared spectroscopy.

PubMed

Ruoff, Kaspar; Luginbühl, Werner; Bogdanov, Stefan; Bosset, Jacques Olivier; Estermann, Barbara; Ziolko, Thomas; Amado, Renato

2006-09-06

Fourier transform near-infrared spectroscopy (FT-NIR) was evaluated for the authentication of eight unifloral and polyfloral honey types (n = 364 samples) previously classified using traditional methods such as chemical, pollen, and sensory analysis. Chemometric evaluation of the spectra was carried out by applying principal component analysis and linear discriminant analysis. The corresponding error rates were calculated according to Bayes' theorem. NIR spectroscopy enabled a reliable discrimination of acacia, chestnut, and fir honeydew honey from the other unifloral and polyfloral honey types studied. The error rates ranged from <0.1 to 6.3% depending on the honey type. NIR proved also to be useful for the classification of blossom and honeydew honeys. The results demonstrate that near-infrared spectrometry is a valuable, rapid, and nondestructive tool for the authentication of the above-mentioned honeys, but not for all varieties studied.

Surface enhanced Raman spectroscopy as a point-of-care diagnostic for infection in wound effluent

NASA Astrophysics Data System (ADS)

Ghebremedhin, Meron; Yesupriya, Shubha; Crane, Nicole J.

2016-03-01

In military medicine, one of the challenges in dealing with large combat-related injuries is the prevalence of bacterial infection, including multidrug resistant organisms. This can prolong the wound healing process and lead to wound dehiscence. Current methods of identifying bacterial infection rely on culturing microbes from patient material and performing biochemical tests, which together can take 2-3 days to complete. Surface Enhanced Raman Spectroscopy (SERS) is a powerful vibrational spectroscopy technique that allows for highly sensitive structural detection of analytes adsorbed onto specially prepared metal surfaces. In the past, we have been able to discriminate between bacterial isolates grown on solid culture media using standard Raman spectroscopic methods. Here, SERS is utilized to assess the presence of bacteria in wound effluent samples taken directly from patients. To our knowledge, this is the first attempt for the application of SERS directly to wound effluent. The utilization of SERS as a point-of-care diagnostic tool would enable physicians to determine course of treatment and drug administration in a matter of hours.

In vivo tumor identification of colorectal liver metastases with diffuse reflectance and fluorescence spectroscopy.

PubMed

Tanis, Erik; Evers, Danny J; Spliethoff, Jarich W; Pully, Vishnu V; Kuhlmann, Koert; van Coevorden, Frits; Hendriks, Benno H W; Sanders, Joyce; Prevoo, Warner; Ruers, Theo J M

2016-11-01

Over the last decade, an increasing effort has been put towards the implementation of optical guidance techniques to aid surgeons during cancer surgery. Diffuse reflectance spectroscopy (DRS) and fluorescence spectroscopy (FS) are two of these new techniques. The objective of this study is to investigate whether in vivo optical spectroscopy is able to accurately discriminate colorectal liver metastases (CRLM) from normal liver tissue in vivo. DRS and FS were incorporated at the tip of a needle and were used for in vivo tissue differentiation during resection of CRLM. Measurements were taken in and around the tumor lesions and measurement sites were marked and correlated to histology (i.e., normal liver tissue or tumor tissue). Patients with and without neoadjuvant systemic chemotherapy were included into the study. Four hundred and eighty-four measurements were taken in and near 19 liver lesions prior to resection. Overall sensitivity and specificity for DRS was 95% and 92%, respectively. Bile was the most discriminative parameter. The addition of FS did not improve the overall accuracy. Sensitivity and specificity was not hampered by neo-adjuvant chemotherapy; sensitivity and specificity after neo-adjuvant chemotherapy were 92% and 100%, respectively. We have successfully integrated spectroscopy technology into a disposable 15 Gauge optical needle and we have shown that DRS and FS can accurately discriminate CRLM from normal liver tissue in the in vivo setting regardless of whether the patient was pre-treated with systemic therapy. This technique makes in vivo guidance accessible for common surgical practice. Lasers Surg. Med. 48:820-827, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Discrimination of Apple Liqueurs (Nalewka) Using a Voltammetric Electronic Tongue, UV-Vis and Raman Spectroscopy

PubMed Central

Śliwińska, Magdalena; Garcia-Hernandez, Celia; Kościński, Mikołaj; Dymerski, Tomasz; Wardencki, Waldemar; Namieśnik, Jacek; Śliwińska-Bartkowiak, Małgorzata; Jurga, Stefan; Garcia-Cabezon, Cristina; Rodriguez-Mendez, Maria Luz

2016-01-01

The capability of a phthalocyanine-based voltammetric electronic tongue to analyze strong alcoholic beverages has been evaluated and compared with the performance of spectroscopic techniques coupled to chemometrics. Nalewka Polish liqueurs prepared from five apple varieties have been used as a model of strong liqueurs. Principal Component Analysis has demonstrated that the best discrimination between liqueurs prepared from different apple varieties is achieved using the e-tongue and UV-Vis spectroscopy. Raman spectra coupled to chemometrics have not been efficient in discriminating liqueurs. The calculated Euclidean distances and the k-Nearest Neighbors algorithm (kNN) confirmed these results. The main advantage of the e-tongue is that, using PLS-1, good correlations have been found simultaneously with the phenolic content measured by the Folin–Ciocalteu method (R2 of 0.97 in calibration and R2 of 0.93 in validation) and also with the density, a marker of the alcoholic content method (R2 of 0.93 in calibration and R2 of 0.88 in validation). UV-Vis coupled with chemometrics has shown good correlations only with the phenolic content (R2 of 0.99 in calibration and R2 of 0.99 in validation) but correlations with the alcoholic content were low. Raman coupled with chemometrics has shown good correlations only with density (R2 of 0.96 in calibration and R2 of 0.85 in validation). In summary, from the three holistic methods evaluated to analyze strong alcoholic liqueurs, the voltammetric electronic tongue using phthalocyanines as sensing elements is superior to Raman or UV-Vis techniques because it shows an excellent discrimination capability and remarkable correlations with both antioxidant capacity and alcoholic content—the most important parameters to be measured in this type of liqueurs.  PMID:27735832

Discrimination of Apple Liqueurs (Nalewka) Using a Voltammetric Electronic Tongue, UV-Vis and Raman Spectroscopy.

PubMed

Śliwińska, Magdalena; Garcia-Hernandez, Celia; Kościński, Mikołaj; Dymerski, Tomasz; Wardencki, Waldemar; Namieśnik, Jacek; Śliwińska-Bartkowiak, Małgorzata; Jurga, Stefan; Garcia-Cabezon, Cristina; Rodriguez-Mendez, Maria Luz

2016-10-09

The capability of a phthalocyanine-based voltammetric electronic tongue to analyze strong alcoholic beverages has been evaluated and compared with the performance of spectroscopic techniques coupled to chemometrics. Nalewka Polish liqueurs prepared from five apple varieties have been used as a model of strong liqueurs. Principal Component Analysis has demonstrated that the best discrimination between liqueurs prepared from different apple varieties is achieved using the e-tongue and UV-Vis spectroscopy. Raman spectra coupled to chemometrics have not been efficient in discriminating liqueurs. The calculated Euclidean distances and the k-Nearest Neighbors algorithm (kNN) confirmed these results. The main advantage of the e-tongue is that, using PLS-1, good correlations have been found simultaneously with the phenolic content measured by the Folin-Ciocalteu method (R² of 0.97 in calibration and R² of 0.93 in validation) and also with the density, a marker of the alcoholic content method (R² of 0.93 in calibration and R² of 0.88 in validation). UV-Vis coupled with chemometrics has shown good correlations only with the phenolic content (R² of 0.99 in calibration and R² of 0.99 in validation) but correlations with the alcoholic content were low. Raman coupled with chemometrics has shown good correlations only with density (R² of 0.96 in calibration and R² of 0.85 in validation). In summary, from the three holistic methods evaluated to analyze strong alcoholic liqueurs, the voltammetric electronic tongue using phthalocyanines as sensing elements is superior to Raman or UV-Vis techniques because it shows an excellent discrimination capability and remarkable correlations with both antioxidant capacity and alcoholic content-the most important parameters to be measured in this type of liqueurs.

Discrimination of bladder cancer cells from normal urothelial cells with high specificity and sensitivity: combined application of atomic force microscopy and modulated Raman spectroscopy.

PubMed

Canetta, Elisabetta; Riches, Andrew; Borger, Eva; Herrington, Simon; Dholakia, Kishan; Adya, Ashok K

2014-05-01

Atomic force microscopy (AFM) and modulated Raman spectroscopy (MRS) were used to discriminate between living normal human urothelial cells (SV-HUC-1) and bladder tumour cells (MGH-U1) with high specificity and sensitivity. MGH-U1 cells were 1.5-fold smaller, 1.7-fold thicker and 1.4-fold rougher than normal SV-HUC-1 cells. The adhesion energy was 2.6-fold higher in the MGH-U1 cells compared to normal SV-HUC-1 cells, which possibly indicates that bladder tumour cells are more deformable than normal cells. The elastic modulus of MGH-U1 cells was 12-fold lower than SV-HUC-1 cells, suggesting a higher elasticity of the bladder cancer cell membranes. The biochemical fingerprints of cancer cells displayed a higher DNA and lipid content, probably due to an increase in the nuclear to cytoplasm ratio. Normal cells were characterized by higher protein contents. AFM studies revealed a decrease in the lateral dimensions and an increase in thickness of cancer cells compared to normal cells; these studies authenticate the observations from MRS. Nanostructural, nanomechanical and biochemical profiles of bladder cells provide qualitative and quantitative markers to differentiate between normal and cancerous cells at the single cellular level. AFM and MRS allow discrimination between adhesion energy, elasticity and Raman spectra of SV-HUC-1 and MGH-U1 cells with high specificity (83, 98 and 95%) and sensitivity (97, 93 and 98%). Such single-cell-level studies could have a pivotal impact on the development of AFM-Raman combined methodologies for cancer profiling and screening with translational significance. Copyright © 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Linear high-boost fusion of Stokes vector imagery for effective discrimination and recognition of real targets in the presence of multiple identical decoys

NASA Astrophysics Data System (ADS)

El-Saba, Aed; Sakla, Wesam A.

2010-04-01

Recently, the use of imaging polarimetry has received considerable attention for use in automatic target recognition (ATR) applications. In military remote sensing applications, there is a great demand for sensors that are capable of discriminating between real targets and decoys. Accurate discrimination of decoys from real targets is a challenging task and often requires the fusion of various sensor modalities that operate simultaneously. In this paper, we use a simple linear fusion technique known as the high-boost fusion method for effective discrimination of real targets in the presence of multiple decoys. The HBF assigns more weight to the polarization-based imagery in forming the final fused image that is used for detection. We have captured both intensity and polarization-based imagery from an experimental laboratory arrangement containing a mixture of sand/dirt, rocks, vegetation, and other objects for the purpose of simulating scenery that would be acquired in a remote sensing military application. A target object and three decoys that are identical in physical appearance (shape, surface structure and color) and different in material composition have also been placed in the scene. We use the wavelet-filter joint transform correlation (WFJTC) technique to perform detection between input scenery and the target object. Our results show that use of the HBF method increases the correlation performance metrics associated with the WFJTC-based detection process when compared to using either the traditional intensity or polarization-based images.

Detection of colon and rectum cancers by terahertz techniques

NASA Astrophysics Data System (ADS)

Wahaia, Faustino; Valusis, Gintaras; Bernardo, Luis M.; Oliveira, Albino; Macutkevic, Jan; Kasalynas, Irmantas; Seliuta, Dalius

2010-04-01

Based on experimental analyses of colon and rectal tissues by THz spectroscopy and THz imaging, we show it is possible to distinguish between healthy and cancerous zones. Plots of the absorption coefficient and the index of refraction of the healthy and cancer affected tissues as well as 2-D transmission THz images will be presented. The experimental results will be discussed and the conditions for the tissues discrimination will be established.

24 CFR 982.202 - How applicants are selected: General requirements.

Code of Federal Regulations, 2011 CFR

2011-04-01

... residency preference (see § 982.207). (2) Where family will live. Admission to the program may not be based... preference system may provide a preference for admission of families with certain characteristics from the...) Discrimination because of age, race, color, religion, sex, or national origin; (iv) Discrimination because of...

Seismic Discrimination of Earthquakes and Explosions, with Application to the Southwestern United States

DTIC Science & Technology

1979-03-22

multi-station discriminants than by those based on network averages. In spite of this situ - ation, average a posteriori probabilities were sometimes...Technology, Pasadena, California. Allen, C. R., L. T. Silver, and F. G. Stehi (1960). Agua Blanca fault - a major transverse structure of northern Baja

78 FR 59338 - Notice of Funds Availability Under the Rural Microentrepreneur Assistance Program

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-26

.... Department of Agriculture (USDA) prohibits discrimination against its customers, employees, and applicants for employment on the bases of race, color, national origin, age, disability, sex, gender identity....) If you wish to file a Civil Rights program complaint of discrimination, complete the USDA Program...

Evaluation of FTIR spectroscopy as diagnostic tool for colorectal cancer using spectral analysis

NASA Astrophysics Data System (ADS)

Dong, Liu; Sun, Xuejun; Chao, Zhang; Zhang, Shiyun; Zheng, Jianbao; Gurung, Rajendra; Du, Junkai; Shi, Jingsen; Xu, Yizhuang; Zhang, Yuanfu; Wu, Jinguang

2014-03-01

The aim of this study is to confirm FTIR spectroscopy as a diagnostic tool for colorectal cancer. 180 freshly removed colorectal samples were collected from 90 patients for spectrum analysis. The ratios of spectral intensity and relative intensity (/I1460) were calculated. Principal component analysis (PCA) and Fisher's discriminant analysis (FDA) were applied to distinguish the malignant from normal. The FTIR parameters of colorectal cancer and normal tissues were distinguished due to the contents or configurations of nucleic acids, proteins, lipids and carbohydrates. Related to nitrogen containing, water, protein and nucleic acid were increased significantly in the malignant group. Six parameters were selected as independent factors to perform discriminant functions. The sensitivity for FTIR in diagnosing colorectal cancer was 96.6% by discriminant analysis. Our study demonstrates that FTIR can be a useful technique for detection of colorectal cancer and may be applied in clinical colorectal cancer diagnosis.

Classification of narcotics in solid mixtures using principal component analysis and Raman spectroscopy.

PubMed

Ryder, Alan G

2002-03-01

Eighty-five solid samples consisting of illegal narcotics diluted with several different materials were analyzed by near-infrared (785 nm excitation) Raman spectroscopy. Principal Component Analysis (PCA) was employed to classify the samples according to narcotic type. The best sample discrimination was obtained by using the first derivative of the Raman spectra. Furthermore, restricting the spectral variables for PCA to 2 or 3% of the original spectral data according to the most intense peaks in the Raman spectrum of the pure narcotic resulted in a rapid discrimination method for classifying samples according to narcotic type. This method allows for the easy discrimination between cocaine, heroin, and MDMA mixtures even when the Raman spectra are complex or very similar. This approach of restricting the spectral variables also decreases the computational time by a factor of 30 (compared to the complete spectrum), making the methodology attractive for rapid automatic classification and identification of suspect materials.

Drop coating deposition Raman spectroscopy of blood plasma for the detection of colorectal cancer

NASA Astrophysics Data System (ADS)

Li, Pengpeng; Chen, Changshui; Deng, Xiaoyuan; Mao, Hua; Jin, Shaoqin

2015-03-01

We have recently applied the technique of drop coating deposition Raman (DCDR) spectroscopy for colorectal cancer (CRC) detection using blood plasma. The aim of this study was to develop a more convenient and stable method based on blood plasma for noninvasive CRC detection. Significant differences are observed in DCDR spectra between healthy (n=105) and cancer (n=75) plasma from 15 CRC patients and 21 volunteers, particularly in the spectra that are related to proteins, nucleic acids, and β-carotene. The multivariate analysis principal components analysis and the linear discriminate analysis, together with leave-one-out, cross validation were used on DCDR spectra and yielded a sensitivity of 100% (75/75) and specificity of 98.1% (103/105) for detection of CRC. This study demonstrates that DCDR spectroscopy of blood plasma associated with multivariate statistical algorithms has the potential for the noninvasive detection of CRC.

Discrimination of microbiological samples using femtosecond laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Baudelet, Matthieu; Yu, Jin; Bossu, Myriam; Jovelet, Julien; Wolf, Jean-Pierre; Amodeo, Tanguy; Fréjafon, Emeric; Laloi, Patrick

2006-10-01

Using femtosecond laser-induced breakdown spectroscopy, the authors have analyzed five different species of bacterium. Line emissions from six trace mineral elements, Na, Mg, P, K, Ca, and Fe, have been clearly detected. Their intensities correspond to relative concentrations of these elements contained in the analyzed samples. The authors demonstrate that the concentration profile of trace elements allows unambiguous discrimination of different bacteria. Quantitative differentiation has been made by representing bacteria in a six-dimension hyperspace with each of its axis representing a detected trace element. In such hyperspace, representative points of different species of bacterium are gathered in different and distinct volumes.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars.

PubMed

Hu, Boran; Yue, Yaqing; Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W

2015-01-01

Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.

Evaluation of factors in development of Vis/NIR spectroscopy models for discriminating PSE, DFD and normal broiler breast meat

USDA-ARS?s Scientific Manuscript database

1. To evaluate the performance of visible and near-infrared (Vis/NIR) spectroscopic models for discriminating true pale, soft and exudative (PSE), normal and dark, firm and dry (DFD) broiler breast meat in different conditions of preprocessing methods, spectral ranges, characteristic wavelength sele...

Effect of selective growth media on the differentiation of Salmonella enterica serovars by Fourier-Transform Mid-Infrared Spectroscopy.

PubMed

Baldauf, Nathan A; Rodriguez-Romo, Luis A; Männig, Annegret; Yousef, Ahmed E; Rodriguez-Saona, Luis E

2007-01-01

Salmonella enterica serovars are prevalent foodborne pathogens responsible for high numbers of salmonellosis each year. Complex Fourier-transform infrared (FTIR) spectra offer unique biochemical fingerprints of bacteria with bands due to major cellular components. Growth media effects on discrimination of Salmonella serovars by FTIR spectroscopy were investigated and a novel sample preparation technique was developed. S. enterica strains from six serovars were grown on xylose lysine desoxycholate (XLD), Miller-Mallinson (MM), and plate count (PCA) agar as a control (37 degrees C, 24 h). Isolated colonies were suspended in 50% acetonitrile and centrifuged; the remaining pellet was placed on an AMTIR (attenuated total reflectance) crystal and dried under vacuum. Classification models (Soft Independent Modeling of Class Analogy, SIMCA), generated from derivatized infrared spectra (1300-900 cm-1 or 1200-900 cm-1), successfully discriminated among Salmonella strains with major discrimination from 1000-970 cm-1 associated to stretching modes of O-specific polysaccharide chains of lipopolysaccharides. Sample treatment with acetonitrile enhanced safe handling of the bacteria, removed interfering signals and improved the discriminating ability of SIMCA. All media were able to discriminate the S. enterica strains studied, varying in discriminating peaks and class distances in SIMCA classification. This methodology, with the production of large libraries of pathogenic bacteria, could be applied for the rapid monitoring of bacterial contamination in food with minimal sample manipulation.

[Identification of Dendrobium varieties by infrared spectroscopy].

PubMed

Liu, Fei; Wang, Yuan-Zhong; Yang, Chun-Yan; Jin, Hang

2014-11-01

The difference of Dendrobium varieties were analyzed by Fourier transform infrared (FTIR) spectroscopy. The infrared spectra of 206 stems from 30 Dendrobium varieties were obtained, and showed that polysaccharides, especially fiber, were the main components in Dendrobium plants. FTIR combined with Wilks' Lambda stepwise discriminative analysis was used to identify Dendrobium varieties. The effects of spectral range and number of training samples on the discrimination results were also analysed. Two hundred eighty seven variables in the spectral range of 1 800-1 250 cm(-1) were studied, and showed that the return discrimination is 100% correct when the training samples number of each species was 2, 3, 4, 5, and 6, respectively, whereas for the remaining samples the correct rates of identification were equal to 79.4%, 91.3%, 93.0%, 98.2%, and 100%, respectively. The same discriminative analyses on five different training samples in the spectral range of 1 800-1 500, 1 500-1 250, 1 250-600, 1 250-950 and 950-650 cm(-1) were compared, which showed that the variables in the range of 1 800-1 250, 1 800-1 500 and 950-600 cm(-1) were more suitable for variety identification, and one can obtain the satisfactory result for discriminative analysis when the training sample is more than 3. Our results indicate that FTIR combined with stepwise discriminative analysis is an effective way to distinguish different Dendrobium varieties.

¹H NMR spectroscopy reveals the effect of genotype and growth conditions on composition of sea buckthorn (Hippophaë rhamnoides L.) berries.

PubMed

Kortesniemi, Maaria; Sinkkonen, Jari; Yang, Baoru; Kallio, Heikki

2014-03-15

¹H NMR spectroscopy and multivariate data analysis were applied to the metabolic profiling and discrimination of wild sea buckthorn (Hippophaë rhamnoides L.) berries from different locations in Finland (subspecies (ssp.) rhamnoides) and China (ssp. sinensis). Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) showed discrimination of the two subspecies and different growth sites. The discrimination of ssp. rhamnoides was mainly associated with typically higher temperature, radiation and humidity and lower precipitation in the south, yielding higher levels of O-ethyl β-d-glucopyranoside and d-glucose, and lower levels of malic, quinic and ascorbic acids. Significant metabolic differences (p<0.05) in genetically identical berries were observed between latitudes 60° and 67° north in Finland. High altitudes (> 2,000 m) correlated with greater levels of malic and ascorbic acids in ssp. sinensis. The NMR metabolomics approach applied here is effective for identification of metabolites, geographical origin and subspecies of sea buckthorn berries. Copyright © 2013 Elsevier Ltd. All rights reserved.

1H nuclear magnetic resonance-based metabolomic characterization of wines by grape varieties and production areas.

PubMed

Son, Hong-Seok; Kim, Ki Myong; van den Berg, Frans; Hwang, Geum-Sook; Park, Won-Mok; Lee, Cherl-Ho; Hong, Young-Shick

2008-09-10

(1)H NMR spectroscopy was used to investigate the metabolic differences in wines produced from different grape varieties and different regions. A significant separation among wines from Campbell Early, Cabernet Sauvignon, and Shiraz grapes was observed using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The metabolites contributing to the separation were assigned to be 2,3-butanediol, lactate, acetate, proline, succinate, malate, glycerol, tartarate, glucose, and phenolic compounds by PCA and PLS-DA loading plots. Wines produced from Cabernet Sauvignon grapes harvested in the continental areas of Australia, France, and California were also separated. PLS-DA loading plots revealed that the level of proline in Californian Cabernet Sauvignon wines was higher than that in Australian and French Cabernet Sauvignon, Australian Shiraz, and Korean Campbell Early wines, showing that the chemical composition of the grape berries varies with the variety and growing area. This study highlights the applicability of NMR-based metabolomics with multivariate statistical data sets in determining wine quality and product origin.

Recent applications of multivariate data analysis methods in the authentication of rice and the most analyzed parameters: A review.

PubMed

Maione, Camila; Barbosa, Rommel Melgaço

2018-01-24

Rice is one of the most important staple foods around the world. Authentication of rice is one of the most addressed concerns in the present literature, which includes recognition of its geographical origin and variety, certification of organic rice and many other issues. Good results have been achieved by multivariate data analysis and data mining techniques when combined with specific parameters for ascertaining authenticity and many other useful characteristics of rice, such as quality, yield and others. This paper brings a review of the recent research projects on discrimination and authentication of rice using multivariate data analysis and data mining techniques. We found that data obtained from image processing, molecular and atomic spectroscopy, elemental fingerprinting, genetic markers, molecular content and others are promising sources of information regarding geographical origin, variety and other aspects of rice, being widely used combined with multivariate data analysis techniques. Principal component analysis and linear discriminant analysis are the preferred methods, but several other data classification techniques such as support vector machines, artificial neural networks and others are also frequently present in some studies and show high performance for discrimination of rice.

Application of visible and near-infrared spectroscopy to classification of Miscanthus species

DOE PAGES

Jin, Xiaoli; Chen, Xiaoling; Xiao, Liang; ...

2017-04-03

Here, the feasibility of visible and near infrared (NIR) spectroscopy as tool to classify Miscanthus samples was explored in this study. Three types of Miscanthus plants, namely, M. sinensis, M. sacchariflorus and M. fIoridulus, were analyzed using a NIR spectrophotometer. Several classification models based on the NIR spectra data were developed using line discriminated analysis (LDA), partial least squares (PLS), least squares support vector machine regression (LSSVR), radial basis function (RBF) and neural network (NN). The principal component analysis (PCA) presented rough classification with overlapping samples, while the models of Line_LSSVR, RBF_LSSVR and RBF_NN presented almost same calibration and validationmore » results. Due to the higher speed of Line_LSSVR than RBF_LSSVR and RBF_NN, we selected the line_LSSVR model as a representative. In our study, the model based on line_LSSVR showed higher accuracy than LDA and PLS models. The total correct classification rates of 87.79 and 96.51% were observed based on LDA and PLS model in the testing set, respectively, while the line_LSSVR showed 99.42% of total correct classification rate. Meanwhile, the lin_LSSVR model in the testing set showed correct classification rate of 100, 100 and 96.77% for M. sinensis, M. sacchariflorus and M. fIoridulus, respectively. The lin_LSSVR model assigned 99.42% of samples to the right groups, except one M. fIoridulus sample. The results demonstrated that NIR spectra combined with a preliminary morphological classification could be an effective and reliable procedure for the classification of Miscanthus species.« less

Portable, real-time alloy identification of metallic wear debris from machinery lubrication systems: laser-induced breakdown spectroscopy versus x-ray fluorescence

NASA Astrophysics Data System (ADS)

Suresh, Pooja

2014-05-01

Alloy identification of oil-borne wear debris captured on chip detectors, filters and magnetic plugs allows the machinery maintainer to assess the health of the engine or gearbox and identify specific component damage. Today, such identification can be achieved in real time using portable, at-line laser-induced breakdown spectroscopy (LIBS) and Xray fluorescence (XRF) instruments. Both techniques can be utilized in various industries including aviation, marine, railways, heavy diesel and other industrial machinery with, however, some substantial differences in application and instrument performance. In this work, the performances of a LIBS and an XRF instrument are compared based on measurements of a wide range of typical aerospace alloys including steels, titanium, aluminum and nickel alloys. Measurement results were analyzed with a staged correlation technique specifically developed for the purposes of this study - identifying the particle alloy composition using a pre-recorded library of spectral signatures. The analysis is performed in two stages: first, the base element of the alloy is determined by correlation with the stored elemental spectra and then, the alloy is identified by matching the particle's spectral signature using parametric correlation against the stored spectra of all alloys that have the same base element. The correlation analysis has achieved highly repeatable discrimination between alloys of similar composition. Portable LIBS demonstrates higher detection accuracy and better identification of alloys comprising lighter elements as compared to that of the portable XRF system, and reveals a significant reduction in the analysis time over XRF.

Application of visible and near-infrared spectroscopy to classification of Miscanthus species

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Xiaoli; Chen, Xiaoling; Xiao, Liang

Here, the feasibility of visible and near infrared (NIR) spectroscopy as tool to classify Miscanthus samples was explored in this study. Three types of Miscanthus plants, namely, M. sinensis, M. sacchariflorus and M. fIoridulus, were analyzed using a NIR spectrophotometer. Several classification models based on the NIR spectra data were developed using line discriminated analysis (LDA), partial least squares (PLS), least squares support vector machine regression (LSSVR), radial basis function (RBF) and neural network (NN). The principal component analysis (PCA) presented rough classification with overlapping samples, while the models of Line_LSSVR, RBF_LSSVR and RBF_NN presented almost same calibration and validationmore » results. Due to the higher speed of Line_LSSVR than RBF_LSSVR and RBF_NN, we selected the line_LSSVR model as a representative. In our study, the model based on line_LSSVR showed higher accuracy than LDA and PLS models. The total correct classification rates of 87.79 and 96.51% were observed based on LDA and PLS model in the testing set, respectively, while the line_LSSVR showed 99.42% of total correct classification rate. Meanwhile, the lin_LSSVR model in the testing set showed correct classification rate of 100, 100 and 96.77% for M. sinensis, M. sacchariflorus and M. fIoridulus, respectively. The lin_LSSVR model assigned 99.42% of samples to the right groups, except one M. fIoridulus sample. The results demonstrated that NIR spectra combined with a preliminary morphological classification could be an effective and reliable procedure for the classification of Miscanthus species.« less

Application of visible and near-infrared spectroscopy to classification of Miscanthus species.

PubMed

Jin, Xiaoli; Chen, Xiaoling; Xiao, Liang; Shi, Chunhai; Chen, Liang; Yu, Bin; Yi, Zili; Yoo, Ji Hye; Heo, Kweon; Yu, Chang Yeon; Yamada, Toshihiko; Sacks, Erik J; Peng, Junhua

2017-01-01

The feasibility of visible and near infrared (NIR) spectroscopy as tool to classify Miscanthus samples was explored in this study. Three types of Miscanthus plants, namely, M. sinensis, M. sacchariflorus and M. fIoridulus, were analyzed using a NIR spectrophotometer. Several classification models based on the NIR spectra data were developed using line discriminated analysis (LDA), partial least squares (PLS), least squares support vector machine regression (LSSVR), radial basis function (RBF) and neural network (NN). The principal component analysis (PCA) presented rough classification with overlapping samples, while the models of Line_LSSVR, RBF_LSSVR and RBF_NN presented almost same calibration and validation results. Due to the higher speed of Line_LSSVR than RBF_LSSVR and RBF_NN, we selected the line_LSSVR model as a representative. In our study, the model based on line_LSSVR showed higher accuracy than LDA and PLS models. The total correct classification rates of 87.79 and 96.51% were observed based on LDA and PLS model in the testing set, respectively, while the line_LSSVR showed 99.42% of total correct classification rate. Meanwhile, the lin_LSSVR model in the testing set showed correct classification rate of 100, 100 and 96.77% for M. sinensis, M. sacchariflorus and M. fIoridulus, respectively. The lin_LSSVR model assigned 99.42% of samples to the right groups, except one M. fIoridulus sample. The results demonstrated that NIR spectra combined with a preliminary morphological classification could be an effective and reliable procedure for the classification of Miscanthus species.

Application of visible and near-infrared spectroscopy to classification of Miscanthus species

PubMed Central

Shi, Chunhai; Chen, Liang; Yu, Bin; Yi, Zili; Yoo, Ji Hye; Heo, Kweon; Yu, Chang Yeon; Yamada, Toshihiko; Sacks, Erik J.; Peng, Junhua

2017-01-01

The feasibility of visible and near infrared (NIR) spectroscopy as tool to classify Miscanthus samples was explored in this study. Three types of Miscanthus plants, namely, M. sinensis, M. sacchariflorus and M. fIoridulus, were analyzed using a NIR spectrophotometer. Several classification models based on the NIR spectra data were developed using line discriminated analysis (LDA), partial least squares (PLS), least squares support vector machine regression (LSSVR), radial basis function (RBF) and neural network (NN). The principal component analysis (PCA) presented rough classification with overlapping samples, while the models of Line_LSSVR, RBF_LSSVR and RBF_NN presented almost same calibration and validation results. Due to the higher speed of Line_LSSVR than RBF_LSSVR and RBF_NN, we selected the line_LSSVR model as a representative. In our study, the model based on line_LSSVR showed higher accuracy than LDA and PLS models. The total correct classification rates of 87.79 and 96.51% were observed based on LDA and PLS model in the testing set, respectively, while the line_LSSVR showed 99.42% of total correct classification rate. Meanwhile, the lin_LSSVR model in the testing set showed correct classification rate of 100, 100 and 96.77% for M. sinensis, M. sacchariflorus and M. fIoridulus, respectively. The lin_LSSVR model assigned 99.42% of samples to the right groups, except one M. fIoridulus sample. The results demonstrated that NIR spectra combined with a preliminary morphological classification could be an effective and reliable procedure for the classification of Miscanthus species. PMID:28369059

Authentication of organic feed by near-infrared spectroscopy combined with chemometrics: a feasibility study.

PubMed

Tres, A; van der Veer, G; Perez-Marin, M D; van Ruth, S M; Garrido-Varo, A

2012-08-22

Organic products tend to retail at a higher price than their conventional counterparts, which makes them susceptible to fraud. In this study we evaluate the application of near-infrared spectroscopy (NIRS) as a rapid, cost-effective method to verify the organic identity of feed for laying hens. For this purpose a total of 36 organic and 60 conventional feed samples from The Netherlands were measured by NIRS. A binary classification model (organic vs conventional feed) was developed using partial least squares discriminant analysis. Models were developed using five different data preprocessing techniques, which were externally validated by a stratified random resampling strategy using 1000 realizations. Spectral regions related to the protein and fat content were among the most important ones for the classification model. The models based on data preprocessed using direct orthogonal signal correction (DOSC), standard normal variate (SNV), and first and second derivatives provided the most successful results in terms of median sensitivity (0.91 in external validation) and median specificity (1.00 for external validation of SNV models and 0.94 for DOSC and first and second derivative models). A previously developed model, which was based on fatty acid fingerprinting of the same set of feed samples, provided a higher sensitivity (1.00). This shows that the NIRS-based approach provides a rapid and low-cost screening tool, whereas the fatty acid fingerprinting model can be used for further confirmation of the organic identity of feed samples for laying hens. These methods provide additional assurance to the administrative controls currently conducted in the organic feed sector.

Molecular origins of scintillation in organic scintillators (Conference Presentation)

NASA Astrophysics Data System (ADS)

Feng, Patrick; Mengesha, Wondwosen; Myllenbeck, Nicholas

2016-09-01

Organic-based scintillators are indispensable materials for radiation detection owing to their high sensitivity to fast neutrons, low cost, and tailorable properties. There has been a recent resurgence of interest in organic scintillators due to exciting discoveries related to neutron discrimination and gamma-ray spectroscopy, which represent capabilities previously thought not possible in these materials. I will discuss our development of crystalline and polymer-based scintillators for these applications. Structure-property relationships related to intermolecular interactions and host-guest electronic exchange will be discussed in the context of energy-transfer pathways relevant to scintillation. An emphasis will be placed on the rational design of these materials, as guided by first principles and DFT calculations. Two related topics will be discussed: 1) Incorporation of organometallic triplet-harvesting additives to plastic scintillator matrices to confer a 'two-state' (singlet and triplet) luminescence signature to different types of ionizing radiation. This approach relies upon energetic and spatial overlap between the donor and acceptor excited states for efficient electronic exchange. Key considerations also include synthetic modification of the luminescence spectra and kinetics, as well as the addition of secondary additives to increase the recombination efficiency. 2) Design of organotin-containing plastic scintillators as a route towards gamma-ray spectroscopy. Organometallic compounds were selected on the basis of distance-dependent quenching relationships, phase compatibility with the polymer matrix, and the gamma-ray cross sections. This approach is guided by molecular modeling and radiation transport modeling to achieve the highest possible detection sensitivity luminescence intensity.

Classification of Ilex species based on metabolomic fingerprinting using nuclear magnetic resonance and multivariate data analysis.

PubMed

Choi, Young Hae; Sertic, Sarah; Kim, Hye Kyong; Wilson, Erica G; Michopoulos, Filippos; Lefeber, Alfons W M; Erkelens, Cornelis; Prat Kricun, Sergio D; Verpoorte, Robert

2005-02-23

The metabolomic analysis of 11 Ilex species, I. argentina, I. brasiliensis, I. brevicuspis, I. dumosavar. dumosa, I. dumosa var. guaranina, I. integerrima, I. microdonta, I. paraguariensis var. paraguariensis, I. pseudobuxus, I. taubertiana, and I. theezans, was carried out by NMR spectroscopy and multivariate data analysis. The analysis using principal component analysis and classification of the (1)H NMR spectra showed a clear discrimination of those samples based on the metabolites present in the organic and aqueous fractions. The major metabolites that contribute to the discrimination are arbutin, caffeine, phenylpropanoids, and theobromine. Among those metabolites, arbutin, which has not been reported yet as a constituent of Ilex species, was found to be a biomarker for I. argentina,I. brasiliensis, I. brevicuspis, I. integerrima, I. microdonta, I. pseudobuxus, I. taubertiana, and I. theezans. This reliable method based on the determination of a large number of metabolites makes the chemotaxonomical analysis of Ilex species possible.

Visible/near-infrared spectroscopy for discrimination of HLB-infected citrus leaves from healthy leaves

USDA-ARS?s Scientific Manuscript database

Researchers have used various hyperspectral systems, covering several areas of the electromagnetic spectrum to investigate all types of disease/plant interactions. The purpose of this research was to investigate using visible and near-infrared (400-1100nm) spectroscopy to differentiate HLB infected...

A near-infrared spectroscopy routine for unambiguous identification of cryptic ant species

USDA-ARS?s Scientific Manuscript database

The identification of species – of importance for most biological disciplines – is not always straightforward as cryptic species present a hurdle for traditional species discrimination. Fibre-optic near-infrared spectroscopy (NIRS) is a rapid and cheap method for a wide range of different applicatio...

A chemiluminescence sensor array for discriminating natural sugars and artificial sweeteners.

PubMed

Niu, Weifen; Kong, Hao; Wang, He; Zhang, Yantu; Zhang, Sichun; Zhang, Xinrong

2012-01-01

In this paper, we report a chemiluminescence (CL) sensor array based on catalytic nanomaterials for the discrimination of ten sweeteners, including five natural sugars and five artificial sweeteners. The CL response patterns ("fingerprints") can be obtained for a given compound on the nanomaterial array and then identified through linear discriminant analysis (LDA). Moreover, each pure sweetener was quantified based on the emission intensities of selected sensor elements. The linear ranges for these sweeteners lie within 0.05-100 mM, but vary with the type of sweetener. The applicability of this array to real-life samples was demonstrated by applying it to various beverages, and the results showed that the sensor array possesses excellent discrimination power and reversibility.

Comparative evaluation of spectroscopic models using different multivariate statistical tools in a multicancer scenario

NASA Astrophysics Data System (ADS)

Ghanate, A. D.; Kothiwale, S.; Singh, S. P.; Bertrand, Dominique; Krishna, C. Murali

2011-02-01

Cancer is now recognized as one of the major causes of morbidity and mortality. Histopathological diagnosis, the gold standard, is shown to be subjective, time consuming, prone to interobserver disagreement, and often fails to predict prognosis. Optical spectroscopic methods are being contemplated as adjuncts or alternatives to conventional cancer diagnostics. The most important aspect of these approaches is their objectivity, and multivariate statistical tools play a major role in realizing it. However, rigorous evaluation of the robustness of spectral models is a prerequisite. The utility of Raman spectroscopy in the diagnosis of cancers has been well established. Until now, the specificity and applicability of spectral models have been evaluated for specific cancer types. In this study, we have evaluated the utility of spectroscopic models representing normal and malignant tissues of the breast, cervix, colon, larynx, and oral cavity in a broader perspective, using different multivariate tests. The limit test, which was used in our earlier study, gave high sensitivity but suffered from poor specificity. The performance of other methods such as factorial discriminant analysis and partial least square discriminant analysis are at par with more complex nonlinear methods such as decision trees, but they provide very little information about the classification model. This comparative study thus demonstrates not just the efficacy of Raman spectroscopic models but also the applicability and limitations of different multivariate tools for discrimination under complex conditions such as the multicancer scenario.

Application of Atomic Dielectric Resonance Spectroscopy for the screening of blood samples from patients with clinical variant and sporadic CJD

PubMed Central

Fagge, Timothy J; Barclay, G Robin; Stove, G Colin; Stove, Gordon; Robinson, Michael J; Head, Mark W; Ironside, James W; Turner, Marc L

2007-01-01

Background Sub-clinical variant Creutzfeldt-Jakob disease (vCJD) infection and reports of vCJD transmission through blood transfusion emphasise the need for blood screening assays to ensure the safety of blood and transplanted tissues. Most assays aim to detect abnormal prion protein (PrPSc), although achieving required sensitivity is a challenge. Methods We have used innovative Atomic Dielectric Resonance Spectroscopy (ADRS), which determines dielectric properties of materials which are established by reflectivity and penetration of radio/micro waves, to analyse blood samples from patients and controls to identify characteristic ADR signatures unique to blood from vCJD and to sCJD patients. Initial sets of blood samples from vCJD, sCJD, non-CJD neurological diseases and normal healthy adults (blood donors) were screened as training samples to determine group-specific ADR characteristics, and provided a basis for classification of blinded sets of samples. Results Blood sample groups from vCJD, sCJD, non-CJD neurological diseases and normal healthy adults (blood donors) screened by ADRS were classified with 100% specificity and sensitivity, discriminating these by a co-variance expert analysis system. Conclusion ADRS appears capable of recognising and discriminating serum samples from vCJD, sCJD, non-CJD neurological diseases, and normal healthy adults, and might be developed to provide a system for primary screening or confirmatory assay complementary to other screening systems. PMID:17760958

Application of passive imaging polarimetry in the discrimination and detection of different color targets of identical shapes using color-blind imaging sensors

NASA Astrophysics Data System (ADS)

El-Saba, A. M.; Alam, M. S.; Surpanani, A.

2006-05-01

Important aspects of automatic pattern recognition systems are their ability to efficiently discriminate and detect proper targets with low false alarms. In this paper we extend the applications of passive imaging polarimetry to effectively discriminate and detect different color targets of identical shapes using color-blind imaging sensor. For this case of study we demonstrate that traditional color-blind polarization-insensitive imaging sensors that rely only on the spatial distribution of targets suffer from high false detection rates, especially in scenarios where multiple identical shape targets are present. On the other hand we show that color-blind polarization-sensitive imaging sensors can successfully and efficiently discriminate and detect true targets based on their color only. We highlight the main advantages of using our proposed polarization-encoded imaging sensor.

Evaluation on the concentration change of paeoniflorin and glycyrrhizic acid in different formulations of Shaoyao-Gancao-Tang by the tri-level infrared macro-fingerprint spectroscopy and the whole analysis method

NASA Astrophysics Data System (ADS)

Liu, Aoxue; Wang, Jingjuan; Guo, Yizhen; Xiao, Yao; Wang, Yue; Sun, Suqin; Chen, Jianbo

2018-03-01

As a kind of common prescriptions, Shaoyao-Gancao-Tang (SGT) contains two Chinese herbs with four different proportions which have different clinical efficacy because of their various components. In order to investigate the herb-herb interaction mechanisms, we used the method of tri-level infrared macro-fingerprint spectroscopy to evaluate the concentration change of active components of four SGTs in this research. Fourier transform infrared spectroscopy (FT-IR) and Second derivative infrared spectroscopy (SD-IR) can recognize the multiple prescriptions directly and simultaneously. 2D-IR spectra enhance the spectral resolution and obtain much new information for discriminating the similar complicated samples of SGT. Furthermore, the whole analysis method from the analysis of the main components to the specific components and the relative content of the components may evaluate the quality of TCM better. Then we concluded that paeoniflorin and glycyrrhizic acid were the highest proportion in active ingredients in SGT-12:1 and the lowest one in SGT-12:12, which matched the HPLC-DAD results. It is demonstrated that the method composed by the tri-level infrared macro-fingerprint spectroscopy and the whole analysis can be applicable for effective, visual and accurate analysis and identification of very complicated and similar mixture systems of traditional Chinese medicine.

Independent components analysis to increase efficiency of discriminant analysis methods (FDA and LDA): Application to NMR fingerprinting of wine.

PubMed

Monakhova, Yulia B; Godelmann, Rolf; Kuballa, Thomas; Mushtakova, Svetlana P; Rutledge, Douglas N

2015-08-15

Discriminant analysis (DA) methods, such as linear discriminant analysis (LDA) or factorial discriminant analysis (FDA), are well-known chemometric approaches for solving classification problems in chemistry. In most applications, principle components analysis (PCA) is used as the first step to generate orthogonal eigenvectors and the corresponding sample scores are utilized to generate discriminant features for the discrimination. Independent components analysis (ICA) based on the minimization of mutual information can be used as an alternative to PCA as a preprocessing tool for LDA and FDA classification. To illustrate the performance of this ICA/DA methodology, four representative nuclear magnetic resonance (NMR) data sets of wine samples were used. The classification was performed regarding grape variety, year of vintage and geographical origin. The average increase for ICA/DA in comparison with PCA/DA in the percentage of correct classification varied between 6±1% and 8±2%. The maximum increase in classification efficiency of 11±2% was observed for discrimination of the year of vintage (ICA/FDA) and geographical origin (ICA/LDA). The procedure to determine the number of extracted features (PCs, ICs) for the optimum DA models was discussed. The use of independent components (ICs) instead of principle components (PCs) resulted in improved classification performance of DA methods. The ICA/LDA method is preferable to ICA/FDA for recognition tasks based on NMR spectroscopic measurements. Copyright © 2015 Elsevier B.V. All rights reserved.

Fast label-free detection of Legionella spp. in biofilms by applying immunomagnetic beads and Raman spectroscopy.

PubMed

Kusić, Dragana; Rösch, Petra; Popp, Jürgen

2016-03-01

Legionellae colonize biofilms, can form a biofilm by itself and multiply intracellularly within the protozoa commonly found in water distribution systems. Approximately half of the known species are pathogenic and have been connected to severe multisystem Legionnaires' disease. The detection methods for Legionella spp. in water samples are still based on cultivation, which is time consuming due to the slow growth of this bacterium. Here, we developed a cultivation-independent, label-free and fast detection method for legionellae in a biofilm matrix based on the Raman spectroscopic analysis of isolated single cells via immunomagnetic separation (IMS). A database comprising the Raman spectra of single bacterial cells captured and separated from the biofilms formed by each species was used to build the identification method based on a support vector machine (SVM) discriminative classifier. The complete method allows the detection of Legionella spp. in 100 min. Cross-reactivity of Legionella spp. specific immunomagnetic beads to the other studied genera was tested, where only small cell amounts of Pseudomonas aeruginosa, Klebsiella pneumoniae and Escherichia coli compared to the initial number of cells were isolated by the immunobeads. Nevertheless, the Raman spectra collected from isolated non-targeted bacteria were well-discriminated from the Raman spectra collected from isolated Legionella cells, whereby the Raman spectra of the independent dataset of Legionella strains were assigned with an accuracy of 98.6%. In addition, Raman spectroscopy was also used to differentiate between isolated Legionella species. Copyright © 2016 Elsevier GmbH. All rights reserved.

Near-infrared-excited confocal Raman spectroscopy advances in vivo diagnosis of cervical precancer.

PubMed

Duraipandian, Shiyamala; Zheng, Wei; Ng, Joseph; Low, Jeffrey J H; Ilancheran, Arunachalam; Huang, Zhiwei

2013-06-01

Raman spectroscopy is a unique optical technique that can probe the changes of vibrational modes of biomolecules associated with tissue premalignant transformation. This study evaluates the clinical utility of confocal Raman spectroscopy over near-infrared (NIR) autofluorescence (AF) spectroscopy and composite NIR AF/Raman spectroscopy for improving early diagnosis of cervical precancer in vivo at colposcopy. A rapid NIR Raman system coupled with a ball-lens fiber-optic confocal Raman probe was utilized for in vivo NIR AF/Raman spectral measurements of the cervix. A total of 1240 in vivo Raman spectra [normal (n=993), dysplasia (n=247)] were acquired from 84 cervical patients. Principal components analysis (PCA) and linear discriminant analysis (LDA) together with a leave-one-patient-out, cross-validation method were used to extract the diagnostic information associated with distinctive spectroscopic modalities. The diagnostic ability of confocal Raman spectroscopy was evaluated using the PCA-LDA model developed from the significant principal components (PCs) [i.e., PC4, 0.0023%; PC5, 0.00095%; PC8, 0.00022%, (p<0.05)], representing the primary tissue Raman features (e.g., 854, 937, 1095, 1253, 1311, 1445, and 1654 cm(-1)). Confocal Raman spectroscopy coupled with PCA-LDA modeling yielded the diagnostic accuracy of 84.1% (a sensitivity of 81.0% and a specificity of 87.1%) for in vivo discrimination of dysplastic cervix. The receiver operating characteristic curves further confirmed that the best classification was achieved using confocal Raman spectroscopy compared to the composite NIR AF/Raman spectroscopy or NIR AF spectroscopy alone. This study illustrates that confocal Raman spectroscopy has great potential to improve early diagnosis of cervical precancer in vivo during clinical colposcopy.

Kennard-Stone combined with least square support vector machine method for noncontact discriminating human blood species

NASA Astrophysics Data System (ADS)

Zhang, Linna; Li, Gang; Sun, Meixiu; Li, Hongxiao; Wang, Zhennan; Li, Yingxin; Lin, Ling

2017-11-01

Identifying whole bloods to be either human or nonhuman is an important responsibility for import-export ports and inspection and quarantine departments. Analytical methods and DNA testing methods are usually destructive. Previous studies demonstrated that visible diffuse reflectance spectroscopy method can realize noncontact human and nonhuman blood discrimination. An appropriate method for calibration set selection was very important for a robust quantitative model. In this paper, Random Selection (RS) method and Kennard-Stone (KS) method was applied in selecting samples for calibration set. Moreover, proper stoichiometry method can be greatly beneficial for improving the performance of classification model or quantification model. Partial Least Square Discrimination Analysis (PLSDA) method was commonly used in identification of blood species with spectroscopy methods. Least Square Support Vector Machine (LSSVM) was proved to be perfect for discrimination analysis. In this research, PLSDA method and LSSVM method was used for human blood discrimination. Compared with the results of PLSDA method, this method could enhance the performance of identified models. The overall results convinced that LSSVM method was more feasible for identifying human and animal blood species, and sufficiently demonstrated LSSVM method was a reliable and robust method for human blood identification, and can be more effective and accurate.

7 CFR 3560.154 - Tenant selection.

Code of Federal Regulations, 2011 CFR

2011-01-01

... discrimination against tenant applications on the basis of race, color, national origin, religion, sex, familial... (iii) Moderate-income applicants. (g) Priorities and preferences for admission. (1) Eligible applicants...) Borrowers receiving Section 8 project-based assistance may establish preferences in accordance with U.S...

Discriminating two nonorthogonal states against a noise channel by feed-forward control

NASA Astrophysics Data System (ADS)

Guo, Li-Sha; Xu, Bao-Ming; Zou, Jian; Wang, Chao-Quan; Li, Hai; Li, Jun-Gang; Shao, Bin

2015-02-01

We propose a scheme by using the feed-forward control (FFC) to realize a better effect of discrimination of two nonorthogonal states after passing a noise channel based on the minimum-error (ME) discrimination. We show that the application of our scheme can highly improve the effect of discrimination compared with the ME discrimination without the FFC for any pair of nonorthogonal states and any degree of amplitude damping. Especially, the effect of our optimal discrimination can reach that of the two initial nonorthogonal pure states in the presence of the noise channel in a deterministic way for equal a priori probabilities or even be better than that in a probabilistic way for unequal a priori probabilities.

Fluorescence spectroscopy applied to orange trees

NASA Astrophysics Data System (ADS)

Marcassa, L. G.; Gasparoto, M. C. G.; Belasque, J., Jr.; Lins, E. C.; Dias Nunes, F.; Bagnato, V. S.

2006-05-01

In this work, we have applied laser-induced fluorescence spectroscopy to investigate biological processes in orange trees (Citrus aurantium L.). We have chosen to investigate water stress and Citrus Canker, which is a disease caused by the Xanthomonas axonopodis pv. citri bacteria. The fluorescence spectroscopy was investigated by using as an excitation source a 442-nm 15-mW HeCd gas multimode discharge laser and a 532-nm 10-mW Nd3+:YAG laser. The stress manifestation was detected by the variation of fluorescence ratios of the leaves at different wavelengths. The fluorescence ratios present a significant variation, showing the possibility to observe water stress by fluorescence spectrum. The Citrus Canker’s contaminated leaves were discriminated from the healthy leaves using a more complex analysis of the fluorescence spectra. However, we were unable to discriminate it from another disease, and new fluorescence experiments are planned for the future.

Characterization of a fluorescent hydrogel synthesized using chitosan, polyvinyl alcohol and 9-anthraldehyde for the selective detection and discrimination of trace Fe3+ and Fe2+ in water for live-cell imaging.

PubMed

Maity, Santu; Parshi, Nira; Prodhan, Chandraday; Chaudhuri, Keya; Ganguly, Jhuma

2018-08-01

A three-dimensional fluorescent hydrogel based on chitosan, polyvinyl alcohol and 9-anthraldehyde (ChPA) has been successfully designed and synthesized for the selective detection and discrimination of Fe 3+ and Fe 2+ in aqueous environment. The unique characteristics of ChPA has been confirmed by the Fourier-transform infrared spectroscopy (FTIR), rheological measurement, scanning electron microscopy (SEM), thermogravimetry and differential thermogravimetry (TG-DTG), ultraviolet-visible spectroscopy (UV-vis), fluorescence studies, transmission electron microscopy (TEM), energy dispersive x-ray spectroscopy (EDX), x-ray diffraction (XRD) and dynamic light scattering (DLS). The emission intensity at 516 nm of the hydrogel has been enhanced remarkably with the addition of Fe 3+ due to the inhibition of the photoinduced electron transfer (PET) process. However, it gets strongly quenched in the case of Fe 2+ owing to chelation enhanced quenching (CHEQ). The probe (ChPA) causes no significant change in the fluorescence and becomes highly specific and sensitive towards Fe 3+ and Fe 2+ compared to other interfering heavy and transition metal ions (HTM). The detection limits of the sensor for the Fe 3+ and Fe 2+ are 0.124 nM and 0.138 nM, respectively. The probe is also promising as a selective sensor for the Fe 3+ and Fe 2+ in the fluorescence imaging of living cells. Thus, such a probe opens up new opportunities to improve the chitosan based fluorescent chemosensor having biocompatibility, biodegradability, sufficient thermal stability and stability in a wide pH range. Copyright © 2018 Elsevier Ltd. All rights reserved.

Requirements for Calibration in Noninvasive Glucose Monitoring by Raman Spectroscopy

PubMed Central

Lipson, Jan; Bernhardt, Jeff; Block, Ueyn; Freeman, William R.; Hofmeister, Rudy; Hristakeva, Maya; Lenosky, Thomas; McNamara, Robert; Petrasek, Danny; Veltkamp, David; Waydo, Stephen

2009-01-01

Background In the development of noninvasive glucose monitoring technology, it is highly desirable to derive a calibration that relies on neither person-dependent calibration information nor supplementary calibration points furnished by an existing invasive measurement technique (universal calibration). Method By appropriate experimental design and associated analytical methods, we establish the sufficiency of multiple factors required to permit such a calibration. Factors considered are the discrimination of the measurement technique, stabilization of the experimental apparatus, physics–physiology-based measurement techniques for normalization, the sufficiency of the size of the data set, and appropriate exit criteria to establish the predictive value of the algorithm. Results For noninvasive glucose measurements, using Raman spectroscopy, the sufficiency of the scale of data was demonstrated by adding new data into an existing calibration algorithm and requiring that (a) the prediction error should be preserved or improved without significant re-optimization, (b) the complexity of the model for optimum estimation not rise with the addition of subjects, and (c) the estimation for persons whose data were removed entirely from the training set should be no worse than the estimates on the remainder of the population. Using these criteria, we established guidelines empirically for the number of subjects (30) and skin sites (387) for a preliminary universal calibration. We obtained a median absolute relative difference for our entire data set of 30 mg/dl, with 92% of the data in the Clarke A and B ranges. Conclusions Because Raman spectroscopy has high discrimination for glucose, a data set of practical dimensions appears to be sufficient for universal calibration. Improvements based on reducing the variance of blood perfusion are expected to reduce the prediction errors substantially, and the inclusion of supplementary calibration points for the wearable device under development will be permissible and beneficial. PMID:20144354

Classification and quantitation of milk powder by near-infrared spectroscopy and mutual information-based variable selection and partial least squares

NASA Astrophysics Data System (ADS)

Chen, Hui; Tan, Chao; Lin, Zan; Wu, Tong

2018-01-01

Milk is among the most popular nutrient source worldwide, which is of great interest due to its beneficial medicinal properties. The feasibility of the classification of milk powder samples with respect to their brands and the determination of protein concentration is investigated by NIR spectroscopy along with chemometrics. Two datasets were prepared for experiment. One contains 179 samples of four brands for classification and the other contains 30 samples for quantitative analysis. Principal component analysis (PCA) was used for exploratory analysis. Based on an effective model-independent variable selection method, i.e., minimal-redundancy maximal-relevance (MRMR), only 18 variables were selected to construct a partial least-square discriminant analysis (PLS-DA) model. On the test set, the PLS-DA model based on the selected variable set was compared with the full-spectrum PLS-DA model, both of which achieved 100% accuracy. In quantitative analysis, the partial least-square regression (PLSR) model constructed by the selected subset of 260 variables outperforms significantly the full-spectrum model. It seems that the combination of NIR spectroscopy, MRMR and PLS-DA or PLSR is a powerful tool for classifying different brands of milk and determining the protein content.

Increasing selectivity for TNT-based explosive detection by synchronous luminescence and derivative spectroscopy with quantum yields of selected aromatic amines.

PubMed

Sheaff, Chrystal N; Eastwood, Delyle; Wai, Chien M

2007-01-01

The detection of explosive material is at the forefront of current analytical problems. A detection method is desired that is not restricted to detecting only explosive materials, but is also capable of identifying the origin and type of explosive. It is essential that a detection method have the selectivity to distinguish among compounds in a mixture of explosives. The nitro compounds found in explosives have low fluorescent yields or are considered to be non-fluorescent; however, after reduction, the amino compounds exhibit relatively high fluorescence. We discuss how to increase selectivity of explosive detection using fluorescence; this includes synchronous luminescence and derivative spectroscopy with appropriate smoothing. By implementing synchronous luminescence and derivative spectroscopy, we were able to resolve the reduction products of one major TNT-based explosive compound, 2,4-diaminotoluene, and the reduction products of other minor TNT-based explosives in a mixture. We also report for the first time the quantum yields of these important compounds. Relative quantum yields are useful in establishing relative fluorescence intensities and are an important spectroscopic measurement of molecules. Our approach allows for rapid, sensitive, and selective detection with the discrimination necessary to distinguish among various explosives.

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs.

PubMed

Ganga, G M D; Esposto, K F; Braatz, D

2012-01-01

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Document Examination: Applications of Image Processing Systems.

PubMed

Kopainsky, B

1989-12-01

Dealing with images is a familiar business for an expert in questioned documents: microscopic, photographic, infrared, and other optical techniques generate images containing the information he or she is looking for. A recent method for extracting most of this information is digital image processing, ranging from the simple contrast and contour enhancement to the advanced restoration of blurred texts. When combined with a sophisticated physical imaging system, an image pricessing system has proven to be a powerful and fast tool for routine non-destructive scanning of suspect documents. This article reviews frequent applications, comprising techniques to increase legibility, two-dimensional spectroscopy (ink discrimination, alterations, erased entries, etc.), comparison techniques (stamps, typescript letters, photo substitution), and densitometry. Computerized comparison of handwriting is not included. Copyright © 1989 Central Police University.

Development and Validation of Discriminant Analysis Models for Student Loan Defaultees and Non-Defaultees.

ERIC Educational Resources Information Center

Myers, Greeley; Siera, Steven

1980-01-01

Default on guaranteed student loans has been increasing. The use of discriminant analysis as a technique to identify "good" v "bad" student loans based on information available from the loan application is discussed. Research to test the ability of models to such predictions is reported. (Author/MLW)

Metabolite profiling of Clinacanthus nutans leaves extracts obtained from different drying methods by 1H NMR-based metabolomics

NASA Astrophysics Data System (ADS)

Hashim, Noor Haslinda Noor; Latip, Jalifah; Khatib, Alfi

2016-11-01

The metabolites of Clinacanthus nutans leaves extracts and their dependence on drying process were systematically characterized using 1H nuclear magnetic resonance spectroscopy (NMR) multivariate data analysis. Principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were able to distinguish the leaves extracts obtained from different drying methods. The identified metabolites were carbohydrates, amino acid, flavonoids and sulfur glucoside compounds. The major metabolites responsible for the separation in PLS-DA loading plots were lupeol, cycloclinacosides, betulin, cerebrosides and choline. The results showed that the combination of 1H NMR spectroscopy and multivariate data analyses could act as an efficient technique to understand the C. nutans composition and its variation.

Rapid on-line detection and grading of wooden breast myopathy in chicken fillets by near-infrared spectroscopy

PubMed Central

Veiseth-Kent, Eva; Høst, Vibeke; Løvland, Atle

2017-01-01

The main objective of this work was to develop a method for rapid and non-destructive detection and grading of wooden breast (WB) syndrome in chicken breast fillets. Near-infrared (NIR) spectroscopy was chosen as detection method, and an industrial NIR scanner was applied and tested for large scale on-line detection of the syndrome. Two approaches were evaluated for discrimination of WB fillets: 1) Linear discriminant analysis based on NIR spectra only, and 2) a regression model for protein was made based on NIR spectra and the estimated concentrations of protein were used for discrimination. A sample set of 197 fillets was used for training and calibration. A test set was recorded under industrial conditions and contained spectra from 79 fillets. The classification methods obtained 99.5–100% correct classification of the calibration set and 100% correct classification of the test set. The NIR scanner was then installed in a commercial chicken processing plant and could detect incidence rates of WB in large batches of fillets. Examples of incidence are shown for three broiler flocks where a high number of fillets (9063, 6330 and 10483) were effectively measured. Prevalence of WB of 0.1%, 6.6% and 8.5% were estimated for these flocks based on the complete sample volumes. Such an on-line system can be used to alleviate the challenges WB represents to the poultry meat industry. It enables automatic quality sorting of chicken fillets to different product categories. Manual laborious grading can be avoided. Incidences of WB from different farms and flocks can be tracked and information can be used to understand and point out main causes for WB in the chicken production. This knowledge can be used to improve the production procedures and reduce today’s extensive occurrence of WB. PMID:28278170

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Objective. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. Approach. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. Main results. The results showed that 86.0% (p<0.001 ) of participants can be correctly classified in leave-one-out cross-validation. The most discriminative brain regions included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex. Significance. This study demonstrated that, in a small sample, multivariate pattern analysis can effectively identify ADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

Discriminating Intercalative Effects of Threading Intercalator Nogalamycin, from Classical Intercalator Daunomycin, Using Single Molecule Atomic Force Spectroscopy.

PubMed

Banerjee, T; Banerjee, S; Sett, S; Ghosh, S; Rakshit, T; Mukhopadhyay, R

2016-01-01

DNA threading intercalators are a unique class of intercalating agents, albeit little biophysical information is available on their intercalative actions. Herein, the intercalative effects of nogalamycin, which is a naturally-occurring DNA threading intercalator, have been investigated by high-resolution atomic force microscopy (AFM) and spectroscopy (AFS). The results have been compared with those of the well-known chemotherapeutic drug daunomycin, which is a non-threading classical intercalator bearing structural similarity to nogalamycin. A comparative AFM assessment revealed a greater increase in DNA contour length over the entire incubation period of 48 h for nogalamycin treatment, whereas the contour length increase manifested faster in case of daunomycin. The elastic response of single DNA molecules to an externally applied force was investigated by the single molecule AFS approach. Characteristic mechanical fingerprints in the overstretching behaviour clearly distinguished the nogalamycin/daunomycin-treated dsDNA from untreated dsDNA-the former appearing less elastic than the latter, and the nogalamycin-treated DNA distinguished from the daunomycin-treated DNA-the classically intercalated dsDNA appearing the least elastic. A single molecule AFS-based discrimination of threading intercalation from the classical type is being reported for the first time.

Discriminating Intercalative Effects of Threading Intercalator Nogalamycin, from Classical Intercalator Daunomycin, Using Single Molecule Atomic Force Spectroscopy

PubMed Central

Sett, S.; Ghosh, S.; Rakshit, T.; Mukhopadhyay, R.

2016-01-01

DNA threading intercalators are a unique class of intercalating agents, albeit little biophysical information is available on their intercalative actions. Herein, the intercalative effects of nogalamycin, which is a naturally-occurring DNA threading intercalator, have been investigated by high-resolution atomic force microscopy (AFM) and spectroscopy (AFS). The results have been compared with those of the well-known chemotherapeutic drug daunomycin, which is a non-threading classical intercalator bearing structural similarity to nogalamycin. A comparative AFM assessment revealed a greater increase in DNA contour length over the entire incubation period of 48 h for nogalamycin treatment, whereas the contour length increase manifested faster in case of daunomycin. The elastic response of single DNA molecules to an externally applied force was investigated by the single molecule AFS approach. Characteristic mechanical fingerprints in the overstretching behaviour clearly distinguished the nogalamycin/daunomycin-treated dsDNA from untreated dsDNA—the former appearing less elastic than the latter, and the nogalamycin-treated DNA distinguished from the daunomycin-treated DNA—the classically intercalated dsDNA appearing the least elastic. A single molecule AFS-based discrimination of threading intercalation from the classical type is being reported for the first time. PMID:27183010

Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors

PubMed Central

Feng, Shangyuan; Huang, Shaohua; Lin, Duo; Chen, Guannan; Xu, Yuanji; Li, Yongzeng; Huang, Zufang; Pan, Jianji; Chen, Rong; Zeng, Haishan

2015-01-01

The capability of saliva protein analysis, based on membrane protein purification and surface-enhanced Raman spectroscopy (SERS), for detecting benign and malignant breast tumors is presented in this paper. A total of 97 SERS spectra from purified saliva proteins were acquired from samples obtained from three groups: 33 healthy subjects; 33 patients with benign breast tumors; and 31 patients with malignant breast tumors. Subtle but discernible changes in the mean SERS spectra of the three groups were observed. Tentative assignments of the saliva protein SERS spectra demonstrated that benign and malignant breast tumors led to several specific biomolecular changes of the saliva proteins. Multiclass partial least squares–discriminant analysis was utilized to analyze and classify the saliva protein SERS spectra from healthy subjects, benign breast tumor patients, and malignant breast tumor patients, yielding diagnostic sensitivities of 75.75%, 72.73%, and 74.19%, as well as specificities of 93.75%, 81.25%, and 86.36%, respectively. The results from this exploratory work demonstrate that saliva protein SERS analysis combined with partial least squares–discriminant analysis diagnostic algorithms has great potential for the noninvasive and label-free detection of breast cancer. PMID:25609959

A study of association between fingernail elements and osteoporosis by laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Bahreini, Maryam; Hosseinimakarem, Zahra; Hassan Tavassoli, Seyed

2012-09-01

Laser induced breakdown spectroscopy (LIBS) is used to investigate the possible effect of osteoporosis on the elemental composition of fingernails. Also, the ability to classify healthy, osteopenic, and osteoporotic subjects based on their fingernail spectra has been examined. 46 atomic and ionic emission lines belonging to 13 elements, which are dominated by calcium and magnesium, have been identified. Measurements are carried out on fingernail clippings of 99 subjects including 27 healthy, 47 osteopenic, and 25 osteoporotic subjects. The Pearson correlations between spectral intensities of different elements of fingernail and age and bone mineral densities (BMDs) in nail samples are calculated. Correlations between line intensities of some elements such as sodium and potassium, calcium and iron, magnesium and silicon and also between some fingernail elements, BMD, and age are observed. Although some of these correlations are weak, some information about mineral metabolism can be deduced from them. Discrimination between nail samples of healthy, osteopenic, and osteoporotic subjects is shown to be somehow possible by a discriminant function analysis using 46 atomic emission lines of the LIBS spectra as input variables. The results of this study provide some evidences for association between osteoporosis and elemental composition of fingernails measured by LIBS.

Use of NMR spectroscopy and magnetic resonance imaging for discriminating Juglans nigra L. seeds

Treesearch

John A. Vozzo; J.M. Halloin; T.G. Cooper; E.J. Potechen

1996-01-01

Black walnut (JuglamnigraL.) seeds are large and require stratification for germination. However, many seeds fail to germinate following stratification. Radiography can be used to select empty seeds, but cannot determine which full seeds will germinate. The objective of this study was to determine if any discrimination could bc achieved through use...

Optical tool for salinity detection by remote sensing spectroscopy: application on Oran watershed, Algeria

NASA Astrophysics Data System (ADS)

Abdellatif, Dehni; Mourad, Lounis

2017-07-01

Soil salinity is a complex problem that affects groundwater aquifers and agricultural lands in the semiarid regions. Remote sensing and spectroscopy database systems provide accuracy for salinity autodetection and dynamical delineation. Salinity detection techniques using polychromatic wavebands by field geocomputation and experimental data are time consuming and expensive. This paper presents an automated spectral detection and identification of salt minerals using a monochromatic waveband concept from multispectral bands-Landsat 8 Operational Land Imager (OLI) and Thermal InfraRed Sensor (TIRS) and spectroscopy United States Geological Survey database. For detecting mineral salts related to electrolytes, such as electronical and vibrational transitions, an integrated approach of salinity detection related to the optical monochromatic concept has been addressed. The purpose of this paper is to discriminate waveband intrinsic spectral similarity using the Beer-Lambert and Van 't Hoff laws for spectral curve extraction such as transmittance, reflectance, absorbance, land surface temperature, molar concentration, and osmotic pressure. These parameters are primordial for hydrodynamic salinity modeling and continuity identification using chemical and physical approaches. The established regression fitted models have been addressed for salt spectroscopy validation for suitable calibration and validation. Furthermore, our analytical tool is conducted for better decision interface using spectral salinity detection and identification in the Oran watershed, Algeria.

Shifted excitation Raman difference spectroscopy for authentication of cheese and cheese analogues

NASA Astrophysics Data System (ADS)

Sowoidnich, Kay; Kronfeldt, Heinz-Detlef

2016-04-01

Food authentication and the detection of adulterated products are recent major issues in the food industry as these topics are of global importance for quality control and food safety. To effectively address this challenge requires fast, reliable and non-destructive analytical techniques. Shifted Excitation Raman Difference Spectroscopy (SERDS) is well suited for identification purposes as it combines the chemically specific information obtained by Raman spectroscopy with the ability for efficient fluorescence rejection. The two slightly shifted excitation wavelengths necessary for SERDS are realized by specially designed microsystem diode lasers. At 671 nm the laser (optical power: 50 mW, spectral shift: 0.7 nm) is based on an external cavity configuration whereas an emission at 783 nm (optical power: 110 mW, spectral shift: 0.5 nm) is achieved by a distributed feedback laser. To investigate the feasibility of SERDS for rapid and nondestructive authentication purposes four types of cheese and three different cheese analogues were selected. Each sample was probed at 8 different positions using integration times of 3-10 seconds and 10 spectra were recorded at each spot. Principal components analysis was applied to the SERDS spectra revealing variations in fat and protein signals as primary distinction criterion between cheese and cheese analogues for both excitation wavelengths. Furthermore, to some extent, minor compositional differences could be identified to discriminate between individual species of cheese and cheese analogues. These findings highlight the potential of SERDS for rapid food authentication potentially paving the way for future applications of portable SERDS systems for non-invasive in situ analysis.

Enhanced NMR Discrimination of Pharmaceutically Relevant Molecular Crystal Forms through Fragment-Based Ab Initio Chemical Shift Predictions.

PubMed

Hartman, Joshua D; Day, Graeme M; Beran, Gregory J O

2016-11-02

Chemical shift prediction plays an important role in the determination or validation of crystal structures with solid-state nuclear magnetic resonance (NMR) spectroscopy. One of the fundamental theoretical challenges lies in discriminating variations in chemical shifts resulting from different crystallographic environments. Fragment-based electronic structure methods provide an alternative to the widely used plane wave gauge-including projector augmented wave (GIPAW) density functional technique for chemical shift prediction. Fragment methods allow hybrid density functionals to be employed routinely in chemical shift prediction, and we have recently demonstrated appreciable improvements in the accuracy of the predicted shifts when using the hybrid PBE0 functional instead of generalized gradient approximation (GGA) functionals like PBE. Here, we investigate the solid-state 13 C and 15 N NMR spectra for multiple crystal forms of acetaminophen, phenobarbital, and testosterone. We demonstrate that the use of the hybrid density functional instead of a GGA provides both higher accuracy in the chemical shifts and increased discrimination among the different crystallographic environments. Finally, these results also provide compelling evidence for the transferability of the linear regression parameters mapping predicted chemical shieldings to chemical shifts that were derived in an earlier study.

Enhanced NMR Discrimination of Pharmaceutically Relevant Molecular Crystal Forms through Fragment-Based Ab Initio Chemical Shift Predictions

PubMed Central

2016-01-01

Chemical shift prediction plays an important role in the determination or validation of crystal structures with solid-state nuclear magnetic resonance (NMR) spectroscopy. One of the fundamental theoretical challenges lies in discriminating variations in chemical shifts resulting from different crystallographic environments. Fragment-based electronic structure methods provide an alternative to the widely used plane wave gauge-including projector augmented wave (GIPAW) density functional technique for chemical shift prediction. Fragment methods allow hybrid density functionals to be employed routinely in chemical shift prediction, and we have recently demonstrated appreciable improvements in the accuracy of the predicted shifts when using the hybrid PBE0 functional instead of generalized gradient approximation (GGA) functionals like PBE. Here, we investigate the solid-state 13C and 15N NMR spectra for multiple crystal forms of acetaminophen, phenobarbital, and testosterone. We demonstrate that the use of the hybrid density functional instead of a GGA provides both higher accuracy in the chemical shifts and increased discrimination among the different crystallographic environments. Finally, these results also provide compelling evidence for the transferability of the linear regression parameters mapping predicted chemical shieldings to chemical shifts that were derived in an earlier study. PMID:27829821

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brubaker, Erik; Dibble, Dean C.; Mengesha, Wondwosen

An ideal 3He detector replacement for the near- to medium-term future will use materials that are easy to produce and well understood, while maintaining thermal neutron detection efficiency and gamma rejection close to the 3He standard. Toward this end, we investigated the use of standard alkali halide scintillators interfaced with 6Li and read out with photomultiplier tubes (PMTs). Thermal neutrons are captured on 6Li with high efficiency, emitting high-energy and triton ( 3H) reaction products. These particles deposit energy in the scintillator, providing a thermal neutron signal; discrimination against gamma interactions is possible via pulse shape discrimination (PSD), since heavymore » particles produce faster pulses in alkali halide crystals. We constructed and tested two classes of detectors based on this concept. In one case 6Li is used as a dopant in polycrystalline NaI; in the other case a thin Li foil is used as a conversion layer. In the configurations studied here, these systems are sensitive to both gamma and neutron radiation, with discrimination between the two and good energy resolution for gamma spectroscopy. We present results from our investigations, including measurements of the neutron efficiency and gamma rejection for the two detector types. We also show a comparison with Cs 2LiYCl 6:Ce (CLYC), which is emerging as the standard scintillator for simultaneous gamma and thermal neutron detection, and also allows PSD. We conclude that 6Li foil with CsI scintillating crystals has near-term promise as a thermal neutron detector in applications previously dominated by 3He detectors. The other approach, 6Li-doped alkali halides, has some potential, but require more work to understand material properties and improve fabrication processes.« less

Applications of absorption spectroscopy using quantum cascade lasers.

PubMed

Zhang, Lizhu; Tian, Guang; Li, Jingsong; Yu, Benli

2014-01-01

Infrared laser absorption spectroscopy (LAS) is a promising modern technique for sensing trace gases with high sensitivity, selectivity, and high time resolution. Mid-infrared quantum cascade lasers, operating in a pulsed or continuous wave mode, have potential as spectroscopic sources because of their narrow linewidths, single mode operation, tunability, high output power, reliability, low power consumption, and compactness. This paper reviews some important developments in modern laser absorption spectroscopy based on the use of quantum cascade laser (QCL) sources. Among the various laser spectroscopic methods, this review is focused on selected absorption spectroscopy applications of QCLs, with particular emphasis on molecular spectroscopy, industrial process control, combustion diagnostics, and medical breath analysis.

Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity at high sensitivity levels (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhao, Jianhua; Zeng, Haishan; Kalia, Sunil; Lui, Harvey

2017-02-01

Background: Raman spectroscopy is a non-invasive optical technique which can measure molecular vibrational modes within tissue. A large-scale clinical study (n = 518) has demonstrated that real-time Raman spectroscopy could distinguish malignant from benign skin lesions with good diagnostic accuracy; this was validated by a follow-up independent study (n = 127). Objective: Most of the previous diagnostic algorithms have typically been based on analyzing the full band of the Raman spectra, either in the fingerprint or high wavenumber regions. Our objective in this presentation is to explore wavenumber selection based analysis in Raman spectroscopy for skin cancer diagnosis. Methods: A wavenumber selection algorithm was implemented using variably-sized wavenumber windows, which were determined by the correlation coefficient between wavenumbers. Wavenumber windows were chosen based on accumulated frequency from leave-one-out cross-validated stepwise regression or least and shrinkage selection operator (LASSO). The diagnostic algorithms were then generated from the selected wavenumber windows using multivariate statistical analyses, including principal component and general discriminant analysis (PC-GDA) and partial least squares (PLS). A total cohort of 645 confirmed lesions from 573 patients encompassing skin cancers, precancers and benign skin lesions were included. Lesion measurements were divided into training cohort (n = 518) and testing cohort (n = 127) according to the measurement time. Result: The area under the receiver operating characteristic curve (ROC) improved from 0.861-0.891 to 0.891-0.911 and the diagnostic specificity for sensitivity levels of 0.99-0.90 increased respectively from 0.17-0.65 to 0.20-0.75 by selecting specific wavenumber windows for analysis. Conclusion: Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity at high sensitivity levels.

Analysis of surgical margins in oral cancer using in situ fluorescence spectroscopy.

PubMed

Francisco, Ana Lucia Noronha; Correr, Wagner Rafael; Pinto, Clóvis Antônio Lopes; Gonçalves Filho, João; Chulam, Thiago Celestino; Kurachi, Cristina; Kowalski, Luiz Paulo

2014-06-01

Oral cancer is a public health problem with high prevalence in the population. Local tumor control is best achieved by complete surgical resection with adequate margins. A disease-free surgical margin correlates with a lower rate of local recurrence and a higher rate of disease-free survival. Fluorescence spectroscopy is a noninvasive diagnostic tool that can aid in real-time cancer detection. The technique, which evaluates the biochemical composition and structure of tissue fluorescence, is relatively simple, fast and, accurate. This study aimed to compare oral squamous cell carcinoma lesions to surgical margins and the mucosa of healthy volunteers by fluorescence spectroscopy. The sample consisted of 56 individuals, 28 with oral squamous cell carcinoma and 28 healthy volunteers with normal oral mucosa. Thirty six cases (64.3%) were male and the mean age was 60.9 years old. The spectra were classified and compared to histopathology to determine fluorescence efficiency for diagnostic discrimination of tumors. In the analysis of the other cases we observed discrimination between normal mucosa, injury and margins. At two-year follow up, three individuals had local recurrence, and in two cases investigation fluorescence in the corresponding area showed qualitative differences in spectra between the recurrence area and the area without recurrence at the same anatomical site in the same patient. In situ analysis of oral mucosa showed the potential of fluorescence spectroscopy as a diagnostic tool that can aid in discrimination of altered mucosa and normal mucosa. Copyright © 2014 Elsevier Ltd. All rights reserved.

Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods.

PubMed

Durakli Velioglu, Serap; Ercioglu, Elif; Boyaci, Ismail Hakki

2017-05-01

This research paper describes the potential of synchronous fluorescence (SF) spectroscopy for authentication of buffalo milk, a favourable raw material in the production of some premium dairy products. Buffalo milk is subjected to fraudulent activities like many other high priced foodstuffs. The current methods widely used for the detection of adulteration of buffalo milk have various disadvantages making them unattractive for routine analysis. Thus, the aim of the present study was to assess the potential of SF spectroscopy in combination with multivariate methods for rapid discrimination between buffalo and cow milk and detection of the adulteration of buffalo milk with cow milk. SF spectra of cow and buffalo milk samples were recorded between 400-550 nm excitation range with Δλ of 10-100 nm, in steps of 10 nm. The data obtained for ∆λ = 10 nm were utilised to classify the samples using principal component analysis (PCA), and detect the adulteration level of buffalo milk with cow milk using partial least square (PLS) methods. Successful discrimination of samples and detection of adulteration of buffalo milk with limit of detection value (LOD) of 6% are achieved with the models having root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) values of 2, 7, and 4%, respectively. The results reveal the potential of SF spectroscopy for rapid authentication of buffalo milk.

The relationship between cross-sectional shapes and FTIR profiles in synthetic wig fibers and their discriminating abilities - An evidential value perspective.

PubMed

Joslin Yogi, Theresa A; Penrod, Michael; Holt, Melinda; Buzzini, Patrick

2018-02-01

Wig fragments or fibers may occasionally be recognized as potential physical evidence during criminal investigations. While analytical methods traditionally adopted for the examination of textile fibers are utilized for the characterizations and comparisons of wig specimens, it is essential to understand in deeper detail the valuable contribution of features of these non-routine evidentiary materials as well as the relationship of the gathered analytical data. This study explores the dependence between the microscopic features of cross-sectional shapes and the polymer type gathered by Fourier transform infrared (FTIR) spectroscopy. The discriminating power of the two methods of cross-sectioning and FTIR spectroscopy was also investigated. Forty-one synthetic wigs varying in both quality and price were collected: twenty-three brown, twelve blondes and six black samples. The collected samples were observed using light microscopy methods (bright field illumination and polarized light), before obtaining cross-sections using the Joliff method and analyze them using FTIR spectroscopy. The forty-one samples were divided into ten groups based on one or more of the ten types of cross-sectional shapes that were observed. The majority of encountered cross-sectional shapes were defined as horseshoe, dog bone and lobular. Infrared spectroscopy confirmed modacrylic to be the most prevalent fiber type. Blends of modacrylic and polyvinyl chloride fibers were also observed as well as polypropylene wig samples. The Goodman and Kruskal lambda statistical test was used and showed that the cross-sectional shape and infrared profile were related. From an evidentiary value perspective, this finding has implications when addressing questions about a common source between questioned wig specimens and a wig reference sample. Copyright © 2017 Elsevier B.V. All rights reserved.

Non-invasive analysis of hormonal variations and effect of postmenopausal Vagifem treatment on women using in vivo high wavenumber confocal Raman spectroscopy.

PubMed

Duraipandian, Shiyamala; Zheng, Wei; Ng, Joseph; Low, Jeffrey J H; Ilancheran, A; Huang, Zhiwei

2013-07-21

This study aims to evaluate the feasibility of applying high wavenumber (HW) confocal Raman spectroscopy for non-invasive assessment of menopause-related hormonal changes in the cervix as well as for determining the effect of Vagifem(®) treatment on postmenopausal women with atrophic cervix. A rapid HW confocal Raman spectroscopy system coupled with a ball lens fiber-optic Raman probe was utilized for in vivo cervical tissue Raman measurements at 785 nm excitation. A total of 164 in vivo HW Raman spectra (premenopausal (n = 104), postmenopausal-prevagifem (n = 34), postmenopausal-postvagifem (n = 26)) were measured from the normal cervix of 26 patients undergoing colposcopy. We established the biochemical basis of premenopausal, postmenopausal-prevagifem and postmenopausal-postvagifem cervix using semiquantitative biomolecular modeling derived from Raman-active biochemicals (i.e., lipids, proteins and water) that play a critical role in HW Raman spectral changes associated with the menopausal process. The diagnostic algorithms developed based on partial least squares-discriminant analysis (PLS-DA) together with leave-one patient-out, cross-validation yielded the diagnostic sensitivities of 88.5%, 91.2% and 88.5%, and specificities of 91.7%, 90.8% and 99.3%, respectively, for non-invasive in vivo discrimination among premenopausal, postmenopausal-prevagifem and postmenopausal-postvagifem cervix. This work demonstrates for the first time that HW confocal Raman spectroscopy in conjunction with biomolecular modeling can be a powerful diagnostic tool for identifying hormone/menopause-related variations in the native squamous epithelium of normal cervix, as well as for assessing the effect of Vagifem treatment on postmenopausal atrophic cervix in vivo during clinical colposcopic inspections.

Development of a novel combined fluorescence and reflectance spectroscopy system for guiding high-grade glioma resections: confirmation of capability in lab experiments

NASA Astrophysics Data System (ADS)

Mousavi, Monirehalsadat; Xie, Haiyan; Xie, Zhiyuan; Brydegaard, Mikkel; Axelsson, Johan; Andersson-Engels, Stefan

2013-11-01

Total resection of glioblastoma multiform (GBM), the most common and aggressive malignant brain tumor, is challenging among other things due to difficulty in intraoperative discrimination between normal and residual tumor cells. This project demonstrates the potential of a system based on a combination of autofluorescence and diffuse reflectance spectroscopy to be useful as an intraoperative guiding tool. In this context, a system based on 5 LEDs coupled to optical fibers was employed to deliver UV/visible light to the sample sequentially. Remitted light from the tissue; including diffuse reflected and fluorescence of endogenous and exogenous fluorophores, as well as its photobleaching product, is transmitted to one photodiode and four avalanche photodiodes. This instrument has been evaluated with very promising results by performing various tissue-equivalent phantom laboratory and clinical studies on skin lesions.

Distinction Between Recurrent Glioma and Radiation Injury Using Magnetic Resonance Spectroscopy in Combination With Diffusion-Weighted Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeng, Q.-S.; Li, C.-F.; Liu Hong

2007-05-01

Purpose: The aim of this study was to explore the diagnostic effectiveness of magnetic resonance (MR) spectroscopy with diffusion-weighted imaging on the evaluation of the recurrent contrast-enhancing areas at the site of treated gliomas. Methods and Materials: In 55 patients who had new contrast-enhancing lesions in the vicinity of the previously resected and irradiated high-grade gliomas, two-dimensional MR spectroscopy and diffusion-weighted imaging were performed. Spectral data for N-acetylaspartate (NAA), choline (Cho), creatine (Cr), lipid (Lip), and lactate (Lac) were analyzed in conjunction with the apparent diffusion coefficient (ADC) in all patients. Diagnosis of these lesions was assigned by means ofmore » follow-up or histopathology. Results: The Cho/NAA and Cho/Cr ratios were significantly higher in recurrent tumor than in regions of radiation injury (p < 0.01). The ADC value and ADC ratios (ADC of contrast-enhancing lesion to matching structure in the contralateral hemisphere) were significantly higher in radiation injury regions than in recurrent tumor (p < 0.01). With MR spectroscopic data, two variables (Cho/NAA and Cho/Cr ratios) were shown to differentiate recurrent glioma from radiation injury, and 85.5% of total subjects were correctly classified into groups. However, with discriminant analysis of MR spectroscopy imaging plus diffusion-weighted imaging, three variables (Cho/NAA, Cho/Cr, and ADC ratio) were identified and 96.4% of total subjects were correctly classified. There was a significant difference between the diagnostic accuracy of the two discriminant analyses (Chi-square = 3.96, p = 0.046). Conclusion: Using discriminant analysis, this study found that MR spectroscopy in combination with ADC ratio, rather than ADC value, can improve the ability to differentiate recurrent glioma and radiation injury.« less

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

DOE PAGES

Belianinov, Alex; Panchapakesan, G.; Lin, Wenzhi; ...

2014-12-02

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1 x Sex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signaturemore » and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.« less

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belianinov, Alex, E-mail: belianinova@ornl.gov; Ganesh, Panchapakesan; Lin, Wenzhi

2014-12-01

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe{sub 0.55}Se{sub 0.45} (T{sub c} = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe{sub 1−x}Se{sub x} structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified bymore » their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.« less

One-laser-based generation/detection of Brillouin dynamic grating and its application to distributed discrimination of strain and temperature.

PubMed

Zou, Weiwen; He, Zuyuan; Hotate, Kazuo

2011-01-31

This paper presents a novel scheme to generate and detect Brillouin dynamic grating in a polarization-maintaining optical fiber based on one laser source. Precise measurement of Brillouin dynamic grating spectrum is achieved benefiting from that the pump, probe and readout waves are coherently originated from the same laser source. Distributed discrimination of strain and temperature is also achieved with high accuracy.

Raman imaging at biological interfaces: applications in breast cancer diagnosis

PubMed Central

2013-01-01

Background One of the most important areas of Raman medical diagnostics is identification and characterization of cancerous and noncancerous tissues. The methods based on Raman scattering has shown significant potential for probing human breast tissue to provide valuable information for early diagnosis of breast cancer. A vibrational fingerprint from the biological tissue provides information which can be used to identify, characterize and discriminate structures in breast tissue, both in the normal and cancerous environment. Results The paper reviews recent progress in understanding structure and interactions at biological interfaces of the human tissue by using confocal Raman imaging and IR spectroscopy. The important differences between the noncancerous and cancerous human breast tissues were found in regions characteristic for vibrations of carotenoids, fatty acids, proteins, and interfacial water. Particular attention was paid to the role played by unsaturated fatty acids and their derivatives as well as carotenoids and interfacial water. Conclusions We demonstrate that Raman imaging has reached a clinically relevant level in regard to breast cancer diagnosis applications. The results presented in the paper may have serious implications on understanding mechanisms of interactions in living cells under realistically crowded conditions of biological tissue. PMID:23705882

Pseudorandom Noise Code-Based Technique for Cloud and Aerosol Discrimination Applications

NASA Technical Reports Server (NTRS)

Campbell, Joel F.; Prasad, Narasimha S.; Flood, Michael A.; Harrison, Fenton Wallace

2011-01-01

NASA Langley Research Center is working on a continuous wave (CW) laser based remote sensing scheme for the detection of CO2 and O2 from space based platforms suitable for ACTIVE SENSING OF CO2 EMISSIONS OVER NIGHTS, DAYS, AND SEASONS (ASCENDS) mission. ASCENDS is a future space-based mission to determine the global distribution of sources and sinks of atmospheric carbon dioxide (CO2). A unique, multi-frequency, intensity modulated CW (IMCW) laser absorption spectrometer (LAS) operating at 1.57 micron for CO2 sensing has been developed. Effective aerosol and cloud discrimination techniques are being investigated in order to determine concentration values with accuracies less than 0.3%. In this paper, we discuss the demonstration of a PN code based technique for cloud and aerosol discrimination applications. The possibility of using maximum length (ML)-sequences for range and absorption measurements is investigated. A simple model for accomplishing this objective is formulated, Proof-of-concept experiments carried out using SONAR based LIDAR simulator that was built using simple audio hardware provided promising results for extension into optical wavelengths. Keywords: ASCENDS, CO2 sensing, O2 sensing, PN codes, CW lidar

Detection of pit fragments in fresh cherries using near infrared spectroscopy

USDA-ARS?s Scientific Manuscript database

NIR spectroscopy in the wavelength region from 900nm to 2600nm was evaluated as the basis for a rapid, non-destructive method for the detection of pits and pit fragments in fresh cherries. Partial Least Squares discriminant analysis (PLS-DA) following various spectral pretreatments was applied to sp...

Raman Spectroscopy: A New Proposal for the Detection of Leukemia Using Blood Samples

NASA Astrophysics Data System (ADS)

Martínez-Espinosa, J. C.; González-Solís, J. L.; Frausto-Reyes, C.; Miranda-Beltrán, M. L.; Soria-Fregoso, C.; Medina-Valtierra, J.; Sánchez-Gómez, R.

2008-08-01

The use of Raman spectroscopy to analyze blood biochemistry and hence distinguish between normal and abnormal blood was investigated. The blood samples were obtained from 6 patients who were clinically diagnosed with leukemia and 6 healthy volunteer. The imprint was put under the microscope and several points were chosen for Raman measurement. All spectra were collected at confocal Raman micro-spectroscopy (Renishaw) with NIR 830 nm laser. It is shown that the serum samples from patients with leukemia and from the control group can be discriminated when the multivariate statistical methods of principal component analysis (PCA) and linear discriminated analysis (LDA) is applied to their Raman spectra. The ratios of some band intensities were analyzed and some band ratios were significant and corresponded to proteins, phospholipids, and polysaccharides. In addition, currently the degree of damage to the bone marrow is estimated through biopsies and therefore it is a very procedure painful. The preliminary results suggest that Raman spectroscopy could be a new technique to study the bone marrow using just blood samples.

[Determination of wine original regions using information fusion of NIR and MIR spectroscopy].

PubMed

Xiang, Ling-Li; Li, Meng-Hua; Li, Jing-Mingz; Li, Jun-Hui; Zhang, Lu-Da; Zhao, Long-Lian

2014-10-01

Geographical origins of wine grapes are significant factors affecting wine quality and wine prices. Tasters' evaluation is a good method but has some limitations. It is important to discriminate different wine original regions quickly and accurately. The present paper proposed a method to determine wine original regions based on Bayesian information fusion that fused near-infrared (NIR) transmission spectra information and mid-infrared (MIR) ATR spectra information of wines. This method improved the determination results by expanding the sources of analysis information. NIR spectra and MIR spectra of 153 wine samples from four different regions of grape growing were collected by near-infrared and mid-infrared Fourier transform spe trometer separately. These four different regions are Huailai, Yantai, Gansu and Changli, which areall typical geographical originals for Chinese wines. NIR and MIR discriminant models for wine regions were established using partial least squares discriminant analysis (PLS-DA) based on NIR spectra and MIR spectra separately. In PLS-DA, the regions of wine samples are presented in group of binary code. There are four wine regions in this paper, thereby using four nodes standing for categorical variables. The output nodes values for each sample in NIR and MIR models were normalized first. These values stand for the probabilities of each sample belonging to each category. They seemed as the input to the Bayesian discriminant formula as a priori probability value. The probabilities were substituteed into the Bayesian formula to get posterior probabilities, by which we can judge the new class characteristics of these samples. Considering the stability of PLS-DA models, all the wine samples were divided into calibration sets and validation sets randomly for ten times. The results of NIR and MIR discriminant models of four wine regions were as follows: the average accuracy rates of calibration sets were 78.21% (NIR) and 82.57% (MIR), and the average accuracy rates of validation sets were 82.50% (NIR) and 81.98% (MIR). After using the method proposed in this paper, the accuracy rates of calibration and validation changed to 87.11% and 90.87% separately, which all achieved better results of determination than individual spectroscopy. These results suggest that Bayesian information fusion of NIR and MIR spectra is feasible for fast identification of wine original regions.

Concept and setup for intraoperative imaging of tumorous tissue via Attenuated Total Reflection spectrosocopy with Quantum Cascade Lasers

NASA Astrophysics Data System (ADS)

Geiger, Florian B.; Koerdel, Martin; Schick, Anton; Heimann, Axel; Matiasek, Kaspar; Herkommer, Alois M.

2015-03-01

A major challenge in tumor surgery is the differentiation between normal and malignant tissue. Since an incompletely resected tumor easily leads to recidivism, the gold standard is to remove malignant tissue with a sufficient safety margin and send it to pathology for examination with patho-histological techniques (rapid section diagnosis). This approach, however, exhibits several disadvantages: The removal of additional tissue (safety margin) means additional stress to the patient; the correct interpretation of proper tumor excision relies on the pathologist's experience and the waiting time between resection and pathological result can be more than 45 minutes. This last aspect implies unnecessary occupation of cost-intensive operating room staff as well as longer anesthesia for the patient. Various research groups state that hyperspectral imaging in the mid-infrared, especially in the so called "fingerprint region", allows spatially resolved discrimination between normal and malignant tissue. All these experiments, though, took place in a laboratory environment and were conducted on dried, ex vivo tissue and on a microscopic scale. It is therefore our aim to develop a system incorporating the following properties: Intraoperatively and in vivo applicable, measurement time shorter than one minute, based on mid infrared spectroscopy, providing both spectral and spatial information and no use of external fluorescence markers. Theoretical assessment of different concepts and experimental studies show that a setup based on a tunable Quantum Cascade Laser and Attenuated Total Reflection seems feasible for in vivo tissue discrimination via imaging. This is confirmed by experiments with a first demonstrator.

[Discrimination among different brands of coffee by using vis-near infrared spectra].

PubMed

Wang, Yan-Yan; He, Yong; Shao, Yong-Ni; Zhang, Zhi-Fei

2007-04-01

Near infrared spectroscopy technology was used to distinguish three different brands of coffee bought from the supermarket. Two models, PCA-BP and WT-BP, were employed for the analysis and prediction of the samples. The discrimination among the different brands of coffee was based on the combination of the function of data compression in the PCA and WT technology and the ability of learning and prediction of the artificial neural network. In the experiment, 60 samples were used for model calibration and 30 for brand prediction. The result showed that both the PCA-BP and WT-BP models achieved 100% discrimination rate, and the wavelet transforms technology is superior to the principal component analysis both in time-consuming and the capability of data compression. It is indicated that the model set up by the combination of WT technology and BP neural network in the present study is rapid in analysis and precise in pattern discrimination. It can be concluded that a new approach to distinguishing pure coffee was of fered and the result of this experiment established the foundation for the determination of the raw material (coffee bean) of different brands of coffee in the market.

[Traceability of Wine Varieties Using Near Infrared Spectroscopy Combined with Cyclic Voltammetry].

PubMed

Li, Meng-hua; Li, Jing-ming; Li, Jun-hui; Zhang, Lu-da; Zhao, Long-lian

2015-06-01

To achieve the traceability of wine varieties, a method was proposed to fuse Near-infrared (NIR) spectra and cyclic voltammograms (CV) which contain different information using D-S evidence theory. NIR spectra and CV curves of three different varieties of wines (cabernet sauvignon, merlot, cabernet gernischt) which come from seven different geographical origins were collected separately. The discriminant models were built using PLS-DA method. Based on this, D-S evidence theory was then applied to achieve the integration of the two kinds of discrimination results. After integrated by D-S evidence theory, the accuracy rate of cross-validation is 95.69% and validation set is 94.12% for wine variety identification. When only considering the wine that come from Yantai, the accuracy rate of cross-validation is 99.46% and validation set is 100%. All the traceability models after fusion achieved better results on classification than individual method. These results suggest that the proposed method combining electrochemical information with spectral information using the D-S evidence combination formula is benefit to the improvement of model discrimination effect, and is a promising tool for discriminating different kinds of wines.

Near-infrared Raman spectroscopy for assessing biochemical changes of cervical tissue associated with precarcinogenic transformation.

PubMed

Duraipandian, Shiyamala; Mo, Jianhua; Zheng, Wei; Huang, Zhiwei

2014-11-07

Raman spectroscopy measures the inelastically scattered light from tissue that is capable of identifying native tissue biochemical constituents and their changes associated with disease transformation. This study aims to characterize the Raman spectroscopic properties of cervical tissue associated with the multi-stage progression of cervical precarcinogenic sequence. A rapid-acquisition fiber-optic near-infrared (NIR) Raman diagnostic system was employed for tissue Raman spectral measurements at 785 nm excitation. A total of 68 Raman spectra (23 benign, 29 low-grade squamous intraepithelial lesions (LSIL) and 16 high grade squamous intraepithelial lesions (HSIL)) were measured from 25 cervical tissue biopsy specimens, as confirmed by colposcopy-histopathology. The semi-quantitative biochemical modeling based on the major biochemicals (i.e., DNA, proteins (histone, collagen), lipid (triolein) and carbohydrates (glycogen)) in cervical tissue uncovers the stepwise accumulation of biomolecular changes associated with progressive cervical precarcinogenesis. Multi-class partial least squares-discriminant analysis (PLS-DA) together with leave-one tissue site-out, cross-validation yielded the diagnostic sensitivities of 95.7%, 82.8% and 81.3%; specificities of 100.0%, 92.3% and 88.5%,for discrimination among benign, LSIL and HSIL cervical tissues, respectively. This work suggests that the Raman spectral biomarkers have identified the potential to be used for monitoring the multi-stage cervical precarcinogenesis, forming the foundation of applying NIR Raman spectroscopy for the early diagnosis of cervical precancer in vivo at the molecular level.

Neutron/Gamma-ray discrimination through measures of fit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amiri, Moslem; Prenosil, Vaclav; Cvachovec, Frantisek

2015-07-01

Statistical tests and their underlying measures of fit can be utilized to separate neutron/gamma-ray pulses in a mixed radiation field. In this article, first the application of a sample statistical test is explained. Fit measurement-based methods require true pulse shapes to be used as reference for discrimination. This requirement makes practical implementation of these methods difficult; typically another discrimination approach should be employed to capture samples of neutrons and gamma-rays before running the fit-based technique. In this article, we also propose a technique to eliminate this requirement. These approaches are applied to several sets of mixed neutron and gamma-ray pulsesmore » obtained through different digitizers using stilbene scintillator in order to analyze them and measure their discrimination quality. (authors)« less

Identifying Plant Part Composition of Forest Logging Residue Using Infrared Spectral Data and Linear Discriminant Analysis

PubMed Central

Acquah, Gifty E.; Via, Brian K.; Billor, Nedret; Fasina, Oladiran O.; Eckhardt, Lori G.

2016-01-01

As new markets, technologies and economies evolve in the low carbon bioeconomy, forest logging residue, a largely untapped renewable resource will play a vital role. The feedstock can however be variable depending on plant species and plant part component. This heterogeneity can influence the physical, chemical and thermochemical properties of the material, and thus the final yield and quality of products. Although it is challenging to control compositional variability of a batch of feedstock, it is feasible to monitor this heterogeneity and make the necessary changes in process parameters. Such a system will be a first step towards optimization, quality assurance and cost-effectiveness of processes in the emerging biofuel/chemical industry. The objective of this study was therefore to qualitatively classify forest logging residue made up of different plant parts using both near infrared spectroscopy (NIRS) and Fourier transform infrared spectroscopy (FTIRS) together with linear discriminant analysis (LDA). Forest logging residue harvested from several Pinus taeda (loblolly pine) plantations in Alabama, USA, were classified into three plant part components: clean wood, wood and bark and slash (i.e., limbs and foliage). Five-fold cross-validated linear discriminant functions had classification accuracies of over 96% for both NIRS and FTIRS based models. An extra factor/principal component (PC) was however needed to achieve this in FTIRS modeling. Analysis of factor loadings of both NIR and FTIR spectra showed that, the statistically different amount of cellulose in the three plant part components of logging residue contributed to their initial separation. This study demonstrated that NIR or FTIR spectroscopy coupled with PCA and LDA has the potential to be used as a high throughput tool in classifying the plant part makeup of a batch of forest logging residue feedstock. Thus, NIR/FTIR could be employed as a tool to rapidly probe/monitor the variability of forest biomass so that the appropriate online adjustments to parameters can be made in time to ensure process optimization and product quality. PMID:27618901

Near-infrared Raman spectroscopy to detect anti-Toxoplasma gondii antibody in blood sera of domestic cats: quantitative analysis based on partial least-squares multivariate statistics

NASA Astrophysics Data System (ADS)

Duarte, Janaína; Pacheco, Marcos T. T.; Villaverde, Antonio Balbin; Machado, Rosangela Z.; Zângaro, Renato A.; Silveira, Landulfo

2010-07-01

Toxoplasmosis is an important zoonosis in public health because domestic cats are the main agents responsible for the transmission of this disease in Brazil. We investigate a method for diagnosing toxoplasmosis based on Raman spectroscopy. Dispersive near-infrared Raman spectra are used to quantify anti-Toxoplasma gondii (IgG) antibodies in blood sera from domestic cats. An 830-nm laser is used for sample excitation, and a dispersive spectrometer is used to detect the Raman scattering. A serological test is performed in all serum samples by the enzyme-linked immunosorbent assay (ELISA) for validation. Raman spectra are taken from 59 blood serum samples and a quantification model is implemented based on partial least squares (PLS) to quantify the sample's serology by Raman spectra compared to the results provided by the ELISA test. Based on the serological values provided by the Raman/PLS model, diagnostic parameters such as sensitivity, specificity, accuracy, positive prediction values, and negative prediction values are calculated to discriminate negative from positive samples, obtaining 100, 80, 90, 83.3, and 100%, respectively. Raman spectroscopy, associated with the PLS, is promising as a serological assay for toxoplasmosis, enabling fast and sensitive diagnosis.

Discrimination and prediction of the origin of Chinese and Korean soybeans using Fourier transform infrared spectrometry (FT-IR) with multivariate statistical analysis

PubMed Central

Lee, Byeong-Ju; Zhou, Yaoyao; Lee, Jae Soung; Shin, Byeung Kon; Seo, Jeong-Ah; Lee, Doyup; Kim, Young-Suk

2018-01-01

The ability to determine the origin of soybeans is an important issue following the inclusion of this information in the labeling of agricultural food products becoming mandatory in South Korea in 2017. This study was carried out to construct a prediction model for discriminating Chinese and Korean soybeans using Fourier-transform infrared (FT-IR) spectroscopy and multivariate statistical analysis. The optimal prediction models for discriminating soybean samples were obtained by selecting appropriate scaling methods, normalization methods, variable influence on projection (VIP) cutoff values, and wave-number regions. The factors for constructing the optimal partial-least-squares regression (PLSR) prediction model were using second derivatives, vector normalization, unit variance scaling, and the 4000–400 cm–1 region (excluding water vapor and carbon dioxide). The PLSR model for discriminating Chinese and Korean soybean samples had the best predictability when a VIP cutoff value was not applied. When Chinese soybean samples were identified, a PLSR model that has the lowest root-mean-square error of the prediction value was obtained using a VIP cutoff value of 1.5. The optimal PLSR prediction model for discriminating Korean soybean samples was also obtained using a VIP cutoff value of 1.5. This is the first study that has combined FT-IR spectroscopy with normalization methods, VIP cutoff values, and selected wave-number regions for discriminating Chinese and Korean soybeans. PMID:29689113

Thermal oxidation process accelerates degradation of the olive oil mixed with sunflower oil and enables its discrimination using synchronous fluorescence spectroscopy and chemometric analysis

NASA Astrophysics Data System (ADS)

Mabood, Fazal; Boqué, Ricard; Folcarelli, Rita; Busto, Olga; Al-Harrasi, Ahmed; Hussain, Javid

2015-05-01

We have investigated the effect of thermal treatment on the discrimination of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with sunflower oil. Two groups of samples were used. One group was analyzed at room temperature (25 °C) and the other group was thermally treated in a thermostatic water bath at 75 °C for 8 h, in contact with air and with light exposure, to favor oxidation. All samples were then measured with synchronous fluorescence spectroscopy. Fluorescence spectra were acquired by varying the excitation wavelength in the region from 250 to 720 nm. In order to optimize the differences between excitation and emission wavelengths, four constant differential wavelengths, i.e., 20 nm, 40 nm, 60 nm and 80 nm, were tried. Partial least-squares discriminant analysis (PLS-DA) was used to discriminate between pure and adulterated oils. It was found that the 20 nm difference was the optimal, at which the discrimination models showed the best results. The best PLS-DA models were those built with the difference spectra (75-25 °C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration. Furthermore, PLS regression models were built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 1.75% of adulteration.

Differentiation of Candida albicans, Candida glabrata, and Candida krusei by FT-IR and chemometrics by CHROMagar™ Candida.

PubMed

Wohlmeister, Denise; Vianna, Débora Renz Barreto; Helfer, Virginia Etges; Calil, Luciane Noal; Buffon, Andréia; Fuentefria, Alexandre Meneghello; Corbellini, Valeriano Antonio; Pilger, Diogo André

2017-10-01

Pathogenic Candida species are detected in clinical infections. CHROMagar™ is a phenotypical method used to identify Candida species, although it has limitations, which indicates the need for more sensitive and specific techniques. Infrared Spectroscopy (FT-IR) is an analytical vibrational technique used to identify patterns of metabolic fingerprint of biological matrixes, particularly whole microbial cell systems as Candida sp. in association of classificatory chemometrics algorithms. On the other hand, Soft Independent Modeling by Class Analogy (SIMCA) is one of the typical algorithms still little employed in microbiological classification. This study demonstrates the applicability of the FT-IR-technique by specular reflectance associated with SIMCA to discriminate Candida species isolated from vaginal discharges and grown on CHROMagar™. The differences in spectra of C. albicans, C. glabrata and C. krusei were suitable for use in the discrimination of these species, which was observed by PCA. Then, a SIMCA model was constructed with standard samples of three species and using the spectral region of 1792-1561cm -1 . All samples (n=48) were properly classified based on the chromogenic method using CHROMagar™ Candida. In total, 93.4% (n=45) of the samples were correctly and unambiguously classified (Class I). Two samples of C. albicans were classified correctly, though these could have been C. glabrata (Class II). Also, one C. glabrata sample could have been classified as C. krusei (Class II). Concerning these three samples, one triplicate of each was included in Class II and two in Class I. Therefore, FT-IR associated with SIMCA can be used to identify samples of C. albicans, C. glabrata, and C. krusei grown in CHROMagar™ Candida aiming to improve clinical applications of this technique. Copyright © 2017 Elsevier B.V. All rights reserved.

Potential of non-invasive esophagus cancer detection based on urine surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Huang, Shaohua; Wang, Lan; Chen, Weisheng; Feng, Shangyuan; Lin, Juqiang; Huang, Zufang; Chen, Guannan; Li, Buhong; Chen, Rong

2014-11-01

Non-invasive esophagus cancer detection based on urine surface-enhanced Raman spectroscopy (SERS) analysis was presented. Urine SERS spectra were measured on esophagus cancer patients (n = 56) and healthy volunteers (n = 36) for control analysis. Tentative assignments of the urine SERS spectra indicated some interesting esophagus cancer-specific biomolecular changes, including a decrease in the relative content of urea and an increase in the percentage of uric acid in the urine of esophagus cancer patients compared to that of healthy subjects. Principal component analysis (PCA) combined with linear discriminant analysis (LDA) was employed to analyze and differentiate the SERS spectra between normal and esophagus cancer urine. The diagnostic algorithms utilizing a multivariate analysis method achieved a diagnostic sensitivity of 89.3% and specificity of 83.3% for separating esophagus cancer samples from normal urine samples. These results from the explorative work suggested that silver nano particle-based urine SERS analysis coupled with PCA-LDA multivariate analysis has potential for non-invasive detection of esophagus cancer.

Noninvasive detection of nasopharyngeal carcinoma based on saliva proteins using surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Lin, Xueliang; Lin, Duo; Ge, Xiaosong; Qiu, Sufang; Feng, Shangyuan; Chen, Rong

2017-10-01

The present study evaluated the capability of saliva analysis combining membrane protein purification with surface-enhanced Raman spectroscopy (SERS) for noninvasive detection of nasopharyngeal carcinoma (NPC). A rapid and convenient protein purification method based on cellulose acetate membrane was developed. A total of 659 high-quality SERS spectra were acquired from purified proteins extracted from the saliva samples of 170 patients with pathologically confirmed NPC and 71 healthy volunteers. Spectral analysis of those saliva protein SERS spectra revealed specific changes in some biochemical compositions, which were possibly associated with NPC transformation. Furthermore, principal component analysis combined with linear discriminant analysis (PCA-LDA) was utilized to analyze and classify the saliva protein SERS spectra from NPC and healthy subjects. Diagnostic sensitivity of 70.7%, specificity of 70.3%, and diagnostic accuracy of 70.5% could be achieved by PCA-LDA for NPC identification. These results show that this assay based on saliva protein SERS analysis holds promising potential for developing a rapid, noninvasive, and convenient clinical tool for NPC screening.

Comparative evaluation of differential laser-induced perturbation spectroscopy as a technique to discriminate emerging skin pathology

NASA Astrophysics Data System (ADS)

Kozikowski, Raymond T.; Smith, Sarah E.; Lee, Jennifer A.; Castleman, William L.; Sorg, Brian S.; Hahn, David W.

2012-06-01

Fluorescence spectroscopy has been widely investigated as a technique for identifying pathological tissue; however, unrelated subject-to-subject variations in spectra complicate data analysis and interpretation. We describe and evaluate a new biosensing technique, differential laser-induced perturbation spectroscopy (DLIPS), based on deep ultraviolet (UV) photochemical perturbation in combination with difference spectroscopy. This technique combines sequential fluorescence probing (pre- and post-perturbation) with sub-ablative UV perturbation and difference spectroscopy to provide a new spectral dimension, facilitating two improvements over fluorescence spectroscopy. First, the differential technique eliminates significant variations in absolute fluorescence response within subject populations. Second, UV perturbations alter the extracellular matrix (ECM), directly coupling the DLIPS response to the biological structure. Improved biosensing with DLIPS is demonstrated in vivo in a murine model of chemically induced skin lesion development. Component loading analysis of the data indicates that the DLIPS technique couples to structural proteins in the ECM. Analysis of variance shows that DLIPS has a significant response to emerging pathology as opposed to other population differences. An optimal likelihood ratio classifier for the DLIPS dataset shows that this technique holds promise for improved diagnosis of epithelial pathology. Results further indicate that DLIPS may improve diagnosis of tissue by augmenting fluorescence spectra (i.e. orthogonal sensing).

[Rapid discriminating hogwash oil and edible vegetable oil using near infrared optical fiber spectrometer technique].

PubMed

Zhang, Bing-Fang; Yuan, Li-Bo; Kong, Qing-Ming; Shen, Wei-Zheng; Zhang, Bing-Xiu; Liu, Cheng-Hai

2014-10-01

In the present study, a new method using near infrared spectroscopy combined with optical fiber sensing technology was applied to the analysis of hogwash oil in blended oil. The 50 samples were a blend of frying oil and "nine three" soybean oil according to a certain volume ratio. The near infrared transmission spectroscopies were collected and the quantitative analysis model of frying oil was established by partial least squares (PLS) and BP artificial neural network The coefficients of determina- tion of calibration sets were 0.908 and 0.934 respectively. The coefficients of determination of validation sets were 0.961 and 0.952, the root mean square error of calibrations (RMSEC) was 0.184 and 0.136, and the root mean square error of predictions (RMSEP) was all 0.111 6. They conform to the model application requirement. At the same time, frying oil and qualified edible oil were identified with the principal component analysis (PCA), and the accurate rate was 100%. The experiment proved that near infrared spectral technology not only can quickly and accurately identify hogwash oil, but also can quantitatively detect hog- wash oil. This method has a wide application prospect in the detection of oil.

Investigating Antibacterial Effects of Garlic (Allium sativum) Concentrate and Garlic-Derived Organosulfur Compounds on Campylobacter jejuni by Using Fourier Transform Infrared Spectroscopy, Raman Spectroscopy, and Electron Microscopy ▿ †

PubMed Central

Lu, Xiaonan; Rasco, Barbara A.; Jabal, Jamie M. F.; Aston, D. Eric; Lin, Mengshi; Konkel, Michael E.

2011-01-01

Fourier transform infrared (FT-IR) spectroscopy and Raman spectroscopy were used to study the cell injury and inactivation of Campylobacter jejuni from exposure to antioxidants from garlic. C. jejuni was treated with various concentrations of garlic concentrate and garlic-derived organosulfur compounds in growth media and saline at 4, 22, and 35°C. The antimicrobial activities of the diallyl sulfides increased with the number of sulfur atoms (diallyl sulfide < diallyl disulfide < diallyl trisulfide). FT-IR spectroscopy confirmed that organosulfur compounds are responsible for the substantial antimicrobial activity of garlic, much greater than those of garlic phenolic compounds, as indicated by changes in the spectral features of proteins, lipids, and polysaccharides in the bacterial cell membranes. Confocal Raman microscopy (532-nm-gold-particle substrate) and Raman mapping of a single bacterium confirmed the intracellular uptake of sulfur and phenolic components. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were employed to verify cell damage. Principal-component analysis (PCA), discriminant function analysis (DFA), and soft independent modeling of class analogs (SIMCA) were performed, and results were cross validated to differentiate bacteria based upon the degree of cell injury. Partial least-squares regression (PLSR) was employed to quantify and predict actual numbers of healthy and injured bacterial cells remaining following treatment. PLSR-based loading plots were investigated to further verify the changes in the cell membrane of C. jejuni treated with organosulfur compounds. We demonstrated that bacterial injury and inactivation could be accurately investigated by complementary infrared and Raman spectroscopies using a chemical-based, “whole-organism fingerprint” with the aid of chemometrics and electron microscopy. PMID:21642409

Classification of edible oils by employing 31P and 1H NMR spectroscopy in combination with multivariate statistical analysis. A proposal for the detection of seed oil adulteration in virgin olive oils.

PubMed

Vigli, Georgia; Philippidis, Angelos; Spyros, Apostolos; Dais, Photis

2003-09-10

A combination of (1)H NMR and (31)P NMR spectroscopy and multivariate statistical analysis was used to classify 192 samples from 13 types of vegetable oils, namely, hazelnut, sunflower, corn, soybean, sesame, walnut, rapeseed, almond, palm, groundnut, safflower, coconut, and virgin olive oils from various regions of Greece. 1,2-Diglycerides, 1,3-diglycerides, the ratio of 1,2-diglycerides to total diglycerides, acidity, iodine value, and fatty acid composition determined upon analysis of the respective (1)H NMR and (31)P NMR spectra were selected as variables to establish a classification/prediction model by employing discriminant analysis. This model, obtained from the training set of 128 samples, resulted in a significant discrimination among the different classes of oils, whereas 100% of correct validated assignments for 64 samples were obtained. Different artificial mixtures of olive-hazelnut, olive-corn, olive-sunflower, and olive-soybean oils were prepared and analyzed by (1)H NMR and (31)P NMR spectroscopy. Subsequent discriminant analysis of the data allowed detection of adulteration as low as 5% w/w, provided that fresh virgin olive oil samples were used, as reflected by their high 1,2-diglycerides to total diglycerides ratio (D > or = 0.90).

Rapid discrimination of sea buckthorn berries from different H. rhamnoides subspecies by multi-step IR spectroscopy coupled with multivariate data analysis

NASA Astrophysics Data System (ADS)

Liu, Yue; Zhang, Ying; Zhang, Jing; Fan, Gang; Tu, Ya; Sun, Suqin; Shen, Xudong; Li, Qingzhu; Zhang, Yi

2018-03-01

As an important ethnic medicine, sea buckthorn was widely used to prevent and treat various diseases due to its nutritional and medicinal properties. According to the Chinese Pharmacopoeia, sea buckthorn was originated from H. rhamnoides, which includes five subspecies distributed in China. Confusion and misidentification usually occurred due to their similar morphology, especially in dried and powdered forms. Additionally, these five subspecies have vital differences in quality and physiological efficacy. This paper focused on the quick classification and identification method of sea buckthorn berry powders from five H. rhamnoides subspecies using multi-step IR spectroscopy coupled with multivariate data analysis. The holistic chemical compositions revealed by the FT-IR spectra demonstrated that flavonoids, fatty acids and sugars were the main chemical components. Further, the differences in FT-IR spectra regarding their peaks, positions and intensities were used to identify H. rhamnoides subspecies samples. The discrimination was achieved using principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). The results showed that the combination of multi-step IR spectroscopy and chemometric analysis offered a simple, fast and reliable method for the classification and identification of the sea buckthorn berry powders from different H. rhamnoides subspecies.

[Application of Raman Spectroscopy Technique to Agricultural Products Quality and Safety Determination].

PubMed

Liu, Yan-de; Jin, Tan-tan

2015-09-01

The quality and safety of agricultural products and people health are inseparable. Using the conventional chemical methods which have so many defects, such as sample pretreatment, complicated operation process and destroying the samples. Raman spectroscopy as a powerful tool of analysing and testing molecular structure, can implement samples quickly without damage, qualitative and quantitative detection analysis. With the continuous improvement and the scope of the application of Raman spectroscopy technology gradually widen, Raman spectroscopy technique plays an important role in agricultural products quality and safety determination, and has wide application prospects. There have been a lot of related research reports based on Raman spectroscopy detection on agricultural product quality safety at present. For the understanding of the principle of detection and the current development situation of Raman spectroscopy, as well as tracking the latest research progress both at home and abroad, the basic principles and the development of Raman spectroscopy as well as the detection device were introduced briefly. The latest research progress of quality and safety determination in fruits and vegetables, livestock and grain by Raman spectroscopy technique were reviewed deeply. Its technical problems for agricultural products quality and safety determination were pointed out. In addition, the text also briefly introduces some information of Raman spectrometer and the application for patent of the portable Raman spectrometer, prospects the future research and application.

Analysis of human nails by laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Hosseinimakarem, Zahra; Tavassoli, Seyed Hassan

2011-05-01

Laser-induced breakdown spectroscopy (LIBS) is applied to analyze human fingernails using nanosecond laser pulses. Measurements on 45 nail samples are carried out and 14 key species are identified. The elements detected with the present system are: Al, C, Ca, Fe, H, K, Mg, N, Na, O, Si, Sr, Ti as well as CN molecule. Sixty three emission lines have been identified in the spectrum that are dominated by calcium lines. A discriminant function analysis is used to discriminate among different genders and age groups. This analysis demonstrates efficient discrimination among these groups. The mean concentration of each element is compared between different groups. Correlation between concentrations of elements in fingernails is calculated. A strong correlation is found between sodium and potassium while calcium and magnesium levels are inversely correlated. A case report on high levels of sodium and potassium in patients with hyperthyroidism is presented. It is shown that LIBS could be a promising technique for the analysis of nails and therefore identification of health problems.

Chinese vinegar classification via volatiles using long-optical-path infrared spectroscopy and chemometrics.

PubMed

Dong, D; Zheng, W; Jiao, L; Lang, Y; Zhao, X

2016-03-01

Different brands of Chinese vinegar are similar in appearance, color and aroma, making their discrimination difficult. The compositions and concentrations of the volatiles released from different vinegars vary by raw material and brewing process and thus offer a means to discriminate vinegars. In this study, we enhanced the detection sensitivity of the infrared spectrometer by extending its optical path. We measured the infrared spectra of the volatiles from 5 brands of Chinese vinegar and observed the spectral characteristics corresponding to alcohols, esters, acids, furfural, etc. Different brands of Chinese vinegar had obviously different infrared spectra and could be classified through chemometrics analysis. Furthermore, we established classification models and demonstrated their effectiveness for classifying different brands of vinegar. This study demonstrates that long-optical-path infrared spectroscopy has the ability to discriminate Chinese vinegars with the advantages that it is fast and non-destructive and eliminates the need for sampling. Copyright © 2015 Elsevier Ltd. All rights reserved.

Differentiation of fresh and frozen-thawed fish samples using Raman spectroscopy coupled with chemometric analysis.

PubMed

Velioğlu, Hasan Murat; Temiz, Havva Tümay; Boyaci, Ismail Hakki

2015-04-01

The potential of Raman spectroscopy was investigated in terms of its capability to discriminate the species of the fish samples and determine their freshness according to the number of freezing/thawing cycles they exposed. Species discrimination analysis was carried out on sixty-four fish samples from six different species, namely horse mackerel (Trachurus trachurus), European anchovy (Engraulis encrasicolus), red mullet (Mullus surmuletus), Bluefish (Pomatamus saltatrix), Atlantic salmon (Salmo salar) and flying gurnard (Trigla lucerna). Afterwards, fish samples were exposed to different numbers of freezing/thawing cycles and separated into three batches, namely (i) fresh, (ii) once frozen-thawed (OF) and (iii) twice frozen-thawed (TF) samples, in order to perform the freshness analysis. Raman data collected were used as inputs for chemometric analysis, which enabled us to develop two main PCA models to successfully terminate the studies for both species discrimination and freshness determination analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Determination of Chinese rice wine from different wineries by near-infrared spectroscopy combined with chemometrics methods

NASA Astrophysics Data System (ADS)

Niu, Xiaoying; Ying, Yibin; Yu, Haiyan; Xie, Lijuan; Fu, Xiaping; Zhou, Ying; Jiang, Xuesong

2007-09-01

In this paper, 104 samples of Chinese rice wines of the same variety (Shaoxing rice wine), collected in three winery ("guyuelongshan", "pagoda" brand, "kuaijishan"), three brewed years (2002, 2004, 2004-2006) were analyzed by near-infrared transmission spectroscopy between 800 and 2500 nm. The spectral differences were studied by principal components analysis (PCA), and Classifications, according the brand, were carried out by discriminant analysis (DA) and partial least squares discriminant analysis (PLSDA). The DA model gained a total accuracy of 94.23% and when used to predict the brand of the validation set samples, a better result, correctly classified all of the three kinds of Chinese rice wine up to 100%, are obtained by PLSDA model. The work reported here is a feasibility study and requires further development with considerable samples of more different brands. Further studies are needed in order to improve the accuracy and robustness, and to extend the discrimination to other Chinese rice wine varieties or brands.

Identification of offal adulteration in beef by laser induced breakdown spectroscopy (LIBS).

PubMed

Velioglu, Hasan Murat; Sezer, Banu; Bilge, Gonca; Baytur, Süleyman Efe; Boyaci, Ismail Hakki

2018-04-01

Minced meat is the major ingredient in sausages, beef burgers, and similar products; and thus it is the main product subjected to adulteration with meat offal. Determination of this kind of meat adulteration is crucial due to religious, economic and ethical concerns. The aim of the present study is to discriminate the beef meat and offal samples by using laser induced breakdown spectroscopy (LIBS). To this end, LIBS and multivariate data analysis were used to discriminate pure beef and offal samples qualitatively and to determine the offal mixture adulteration quantitatively. In this analysis, meat samples were frozen and LIBS analysis were performed. The results indicate that by using principal component analysis (PCA), discrimination of pure offal and offal mixture adulterated beef samples can be achieved successfully. Besides, adulteration ratio can be determined using partial least square analysis method (PLS) with 0.947 coefficient of determination (R 2 ) and 3.8% of limit of detection (LOD) values for offal mixture adulterated beef samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rapid differentiation of Listeria monocytogenes epidemic clones III and IV and their intact compared with heat-killed populations using Fourier transform infrared spectroscopy and chemometrics.

PubMed

Nyarko, Esmond B; Puzey, Kenneth A; Donnelly, Catherine W

2014-06-01

The objectives of this study were to determine if Fourier transform infrared (FT-IR) spectroscopy and multivariate statistical analysis (chemometrics) could be used to rapidly differentiate epidemic clones (ECs) of Listeria monocytogenes, as well as their intact compared with heat-killed populations. FT-IR spectra were collected from dried thin smears on infrared slides prepared from aliquots of 10 μL of each L. monocytogenes ECs (ECIII: J1-101 and R2-499; ECIV: J1-129 and J1-220), and also from intact and heat-killed cell populations of each EC strain using 250 scans at a resolution of 4 cm(-1) in the mid-infrared region in a reflectance mode. Chemometric analysis of spectra involved the application of the multivariate discriminant method for canonical variate analysis (CVA) and linear discriminant analysis (LDA). CVA of the spectra in the wavelength region 4000 to 600 cm(-1) separated the EC strains while LDA resulted in a 100% accurate classification of all spectra in the data set. Further, CVA separated intact and heat-killed cells of each EC strain and there was 100% accuracy in the classification of all spectra when LDA was applied. FT-IR spectral wavenumbers 1650 to 1390 cm(-1) were used to separate heat-killed and intact populations of L. monocytogenes. The FT-IR spectroscopy method allowed discrimination between strains that belong to the same EC. FT-IR is a highly discriminatory and reproducible method that can be used for the rapid subtyping of L. monocytogenes, as well as for the detection of live compared with dead populations of the organism. Fourier transform infrared (FT-IR) spectroscopy and multivariate statistical analysis can be used for L. monocytogenes source tracking and for clinical case isolate comparison during epidemiological investigations since the method is capable of differentiating epidemic clones and it uses a library of well-characterized strains. The FT-IR method is potentially less expensive and more rapid compared to genetic subtyping methods, and can be used for L. monocytogenes strain typing by food industries and public health agencies to enable faster response and intervention to listeriosis outbreaks. FT-IR can also be applied for routine monitoring of the pathogen in food processing plants and for investigating postprocessing contamination because it is capable of differentiating heat-killed and viable L. monocytogenes populations. © 2014 Institute of Food Technologists®

Potential of laser-induced breakdown spectroscopy for discrimination of nano-sized carbon materials. Insights on the optical characterization of graphene

NASA Astrophysics Data System (ADS)

Serrano, J.; Cabalín, L. M.; Moros, J.; Laserna, J. J.

2014-07-01

Since its invention in 2004, graphene has attracted considerable interest worldwide. Advances in the use of graphene in materials science and engineering require important increases in the quality of the final product for integration in photonic and electronic devices. To meet this demand, which will become increasingly strict in the future, analytical techniques capable of differentiating between the starting materials and graphene need to be developed. The interest in the use of laser-induced breakdown spectroscopy (LIBS) for this application rests on the rapid progress experienced by this technology for identification of carbon-based materials of close chemical composition. The potential of LIBS has been explored here by a careful investigation of the spectral properties of both multi-layer and few-layer graphene, graphite and graphene oxide. Results reveal significant differences in the specific optical emission responses of these materials, expressly reflected on the behavior of CN and C2 molecular emissions. These differences result from the particularities of the materials, such as the number of carbon layers and the carbon hybridization in the bonding structure, together with the post-ablation evolution of the concerned plasma plume. In short, this interconnection between ablation and emission events generated from each material allows its characterization and its differentiation from other materials with highly similar chemical composition.

[Discriminant Analysis of Lavender Essential Oil by Attenuated Total Reflectance Infrared Spectroscopy].

PubMed

Tang, Jun; Wang, Qing; Tong, Hong; Liao, Xiang; Zhang, Zheng-fang

2016-03-01

This work aimed to use attenuated total reflectance Fourier transform infrared spectroscopy to identify the lavender essential oil by establishing a Lavender variety and quality analysis model. So, 96 samples were tested. For all samples, the raw spectra were pretreated as second derivative, and to determine the 1 750-900 cm(-1) wavelengths for pattern recognition analysis on the basis of the variance calculation. The results showed that principal component analysis (PCA) can basically discriminate lavender oil cultivar and the first three principal components mainly represent the ester, alcohol and terpenoid substances. When the orthogonal partial least-squares discriminant analysis (OPLS-DA) model was established, the 68 samples were used for the calibration set. Determination coefficients of OPLS-DA regression curve were 0.959 2, 0.976 4, and 0.958 8 respectively for three varieties of lavender essential oil. Three varieties of essential oil's the root mean square error of prediction (RMSEP) in validation set were 0.142 9, 0.127 3, and 0.124 9, respectively. The discriminant rate of calibration set and the prediction rate of validation set had reached 100%. The model has the very good recognition capability to detect the variety and quality of lavender essential oil. The result indicated that a model which provides a quick, intuitive and feasible method had been built to discriminate lavender oils.

Structural studies on Demospongiae sponges from Gökçeada Island in the Northern Aegean Sea

NASA Astrophysics Data System (ADS)

Bayari, Sevgi Haman; Şen, Elif Hilal; Ide, Semra; Topaloglu, Bülent

2018-03-01

The Demospongiae is the largest Class in the phylum Porifera (sponges). Most sponge species in the Class Demospongiae have a skeleton of siliceous spicules and/or protein spongin or both. The first aim of this study was to perform the morphological and structural characterization of the siliceous spicules of four species belonging to Class Demospongiae (Suberites domuncula, Axinella polypoides, Axinella damicornis and Agelas oroides) collected around Gökçeada Island-Turkey (Northern Aegean Sea). The characterizations were carried out using a combination of Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy (SEM/EDX), Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy (ATR-FTIR) and Small Angle X-ray Scattering (SAXS) techniques. The sponge Chondrosia reniformis (Porifera, Demospongiae) lacks a structural skeleton of spicules or the spongin. It consists mainly of a collagenous tissue. The collagen with sponge origin is an important source in biomedical and pharmaceutical applications. The second aim of this study was to provide more information on the molecular structure of collagen of outer (ectosome) and inner (choanosome) regions of the Chondrosia reniformis using ATR-FTIR spectroscopy. Hierarchical clustering analysis (HCA) was also used for the discrimination of ATR-FTIR spectra of species.

Discrimination of cultivation ages and cultivars of ginseng leaves using Fourier transform infrared spectroscopy combined with multivariate analysis

PubMed Central

Kwon, Yong-Kook; Ahn, Myung Suk; Park, Jong Suk; Liu, Jang Ryol; In, Dong Su; Min, Byung Whan; Kim, Suk Weon

2013-01-01

To determine whether Fourier transform (FT)-IR spectral analysis combined with multivariate analysis of whole-cell extracts from ginseng leaves can be applied as a high-throughput discrimination system of cultivation ages and cultivars, a total of total 480 leaf samples belonging to 12 categories corresponding to four different cultivars (Yunpung, Kumpung, Chunpung, and an open-pollinated variety) and three different cultivation ages (1 yr, 2 yr, and 3 yr) were subjected to FT-IR. The spectral data were analyzed by principal component analysis and partial least squares-discriminant analysis. A dendrogram based on hierarchical clustering analysis of the FT-IR spectral data on ginseng leaves showed that leaf samples were initially segregated into three groups in a cultivation age-dependent manner. Then, within the same cultivation age group, leaf samples were clustered into four subgroups in a cultivar-dependent manner. The overall prediction accuracy for discrimination of cultivars and cultivation ages was 94.8% in a cross-validation test. These results clearly show that the FT-IR spectra combined with multivariate analysis from ginseng leaves can be applied as an alternative tool for discriminating of ginseng cultivars and cultivation ages. Therefore, we suggest that this result could be used as a rapid and reliable F1 hybrid seed-screening tool for accelerating the conventional breeding of ginseng. PMID:24558311

Discrimination between basal cell carcinoma and hair follicles in skin tissue sections by Raman micro-spectroscopy

NASA Astrophysics Data System (ADS)

Larraona-Puy, M.; Ghita, A.; Zoladek, A.; Perkins, W.; Varma, S.; Leach, I. H.; Koloydenko, A. A.; Williams, H.; Notingher, I.

2011-05-01

Skin cancer is the most common human malignancy and basal cell carcinoma (BCC) represents approximately 80% of the non-melanoma cases. Current methods of treatment require histopathological evaluation of the tissues by qualified personnel. However, this method is subjective and in some cases BCC can be confused with other structures in healthy skin, including hair follicles. In this preliminary study, we investigated the potential of Raman micro-spectroscopy (RMS) to discriminate between hair follicles and BCC in skin tissue sections excised during Mohs micrographic surgery (MMS). Imaging and diagnosis of skin sections was automatically generated using ' a priori'-built spectral model based on LDA. This model had 90 ± 9% sensitivity and 85 ± 9% specificity for discrimination of BCC from dermis and epidermis. The model used selected Raman bands corresponding to the largest spectral differences between the Raman spectra of BCC and the normal skin regions, associated mainly with nucleic acids and collagen type I. Raman spectra corresponding to the epidermis regions of the hair follicles were found to be closer to those of healthy epidermis rather than BCC. Comparison between Raman spectral images and the gold standard haematoxylin and eosin (H&E) histopathology diagnosis showed good agreement. Some hair follicle regions were misclassified as BCC; regions corresponded mainly to the outermost layer of hair follicle (basal cells) which are expected to have higher nucleic acid concentration. This preliminary study shows the ability of RMS to distinguish between BCC and other tissue structures associated to healthy skin which can be confused with BCC due to their similar morphology.

Discrimination and classification of acute lymphoblastic leukemia cells by Raman spectroscopy

NASA Astrophysics Data System (ADS)

Managò, Stefano; Valente, Carmen; Mirabelli, Peppino; De Luca, Anna Chiara

2015-05-01

Currently, a combination of technologies is typically required to identify and classify leukemia cells. These methods often lack the specificity and sensitivity necessary for early and accurate diagnosis. Here, we demonstrate the use of Raman spectroscopy to identify normal B cells, collected from healthy patients, and three ALL cell lines (RS4;11, REH and MN60 at different differentiation level, respectively). Raman markers associated with DNA and protein vibrational modes have been identified that exhibit excellent discriminating power for leukemia cell identification. Principal Component Analysis was finally used to confirm the significance of these markers for identify leukemia cells and classifying the data. The obtained results indicate a sorting accuracy of 96% between the three leukemia cell lines.

Authentication of edible vegetable oils adulterated with used frying oil by Fourier Transform Infrared Spectroscopy.

PubMed

Zhang, Qing; Liu, Cheng; Sun, Zhijian; Hu, Xiaosong; Shen, Qun; Wu, Jihong

2012-06-01

The application of Fourier Transform Infrared (FTIR) Spectroscopy to authenticate edible vegetable oils (corn, peanut, rapeseed and soybean oil) adulterated with used frying oil was introduced in this paper. The FTIR spectrum of oil was divided into 22 regions which corresponded to the constituents and molecular structures of vegetable oils. Samples of calibration set were classified into four categories for corn and peanut oils and five categories for rapeseed and soybean oils by cluster analysis. Qualitative analysis of validation set was obtained by discriminant analysis. Area ratio between absorption band 19 and 20 and wavenumber shift of band 19 were treated by linear regression for quantitative analysis. For four adulteration types, LODs of area ratio were 6.6%, 7.2%, 5.5%, 3.6% and wavenumber shift were 8.1%, 9.0%, 6.9%, 5.6%, respectively. The proposed methodology is a useful tool to authenticate the edible vegetable oils adulterated with used frying oil. Copyright © 2011 Elsevier Ltd. All rights reserved.

Applications of Infrared and Raman Spectroscopies to Probiotic Investigation

PubMed Central

Santos, Mauricio I.; Gerbino, Esteban; Tymczyszyn, Elizabeth; Gomez-Zavaglia, Andrea

2015-01-01

In this review, we overview the most important contributions of vibrational spectroscopy based techniques in the study of probiotics and lactic acid bacteria. First, we briefly introduce the fundamentals of these techniques, together with the main multivariate analytical tools used for spectral interpretation. Then, four main groups of applications are reported: (a) bacterial taxonomy (Subsection 4.1); (b) bacterial preservation (Subsection 4.2); (c) monitoring processes involving lactic acid bacteria and probiotics (Subsection 4.3); (d) imaging-based applications (Subsection 4.4). A final conclusion, underlying the potentialities of these techniques, is presented. PMID:28231205

Selection of Hyperspectral Narrowbands (HNBs) and Composition of Hyperspectral Twoband Vegetation Indices (HVIs) for Biophysical Characterization and Discrimination of Crop Types Using Field Reflectance and Hyperion-EO-1 Data

NASA Technical Reports Server (NTRS)

Thenkabail, Prasad S.; Mariotto, Isabella; Gumma, Murali Krishna; Middleton, Elizabeth M.; Landis, David R.; Huemmrich, K. Fred

2013-01-01

The overarching goal of this study was to establish optimal hyperspectral vegetation indices (HVIs) and hyperspectral narrowbands (HNBs) that best characterize, classify, model, and map the world's main agricultural crops. The primary objectives were: (1) crop biophysical modeling through HNBs and HVIs, (2) accuracy assessment of crop type discrimination using Wilks' Lambda through a discriminant model, and (3) meta-analysis to select optimal HNBs and HVIs for applications related to agriculture. The study was conducted using two Earth Observing One (EO-1) Hyperion scenes and other surface hyperspectral data for the eight leading worldwide crops (wheat, corn, rice, barley, soybeans, pulses, cotton, and alfalfa) that occupy approx. 70% of all cropland areas globally. This study integrated data collected from multiple study areas in various agroecosystems of Africa, the Middle East, Central Asia, and India. Data were collected for the eight crop types in six distinct growth stages. These included (a) field spectroradiometer measurements (350-2500 nm) sampled at 1-nm discrete bandwidths, and (b) field biophysical variables (e.g., biomass, leaf area index) acquired to correspond with spectroradiometer measurements. The eight crops were described and classified using approx. 20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was approx. 25% better than the multi-spectral results possible from Landsat-7's Enhanced Thematic Mapper+ or EO-1's Advanced Land Imager. Further, based on this research and meta-analysis involving over 100 papers, the study established 33 optimal HNBs and an equal number of specific two-band normalized difference HVIs to best model and study specific biophysical and biochemical quantities of major agricultural crops of the world. Redundant bands identified in this study will help overcome the Hughes Phenomenon (or "the curse of high dimensionality") in hyperspectral data for a particular application (e.g., biophysical characterization of crops). The findings of this study will make a significant contribution to future hyperspectral missions such as NASA's HyspIRI. Index Terms-Hyperion, field reflectance, imaging spectroscopy, HyspIRI, biophysical parameters, hyperspectral vegetation indices, hyperspectral narrowbands, broadbands.