Chemometric tools to investigate complex synchrotron radiation FTIR micro-spectra: focus on historical bowed musical instruments

<p class="Abstract">The investigation of the coating systems used on historical bowed string musical instruments is generally highly complex due to the coatings’ reduced thickness and multi-layered structure. Furthermore, sampling is rarely feasible, and non-invasive approaches do not always allow researchers to undertake a thorough characterisation. Thus, in the rare cases of availability, the opportunity must be taken to investigate the best micro-samples in detail using a suite of analytical spectroscopic techniques that allow for obtaining various informative spectra. Their subsequent interpretation should lead to the characterisation of the finishing layers, the preparation of which involves a careful selection of organic and inorganic compounds.</p>In the present work, synchrotron radiation and micro-Fourier-transform infrared spectroscopy were combined in terms of reflection geometry and chemometrics to investigate six cross-sectioned micro-samples detached from four bowed string instruments produced by Antonio Stradivari, Francesco Ruggeri, and Lorenzo Storioni. Various chemometric tools enabled us to perform a preliminary exploration of the entire collected infrared dataset, while a classification model based on partial least squares–discriminant analysis was used to discriminate the materials through the characteristic signals. High model specificity (> 0.9) was achieved in the prediction, providing the groundwork for the application of a fast and rigorous methodological approach.

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Non-invasive identification of organic materials in historical stringed musical instruments by reflection infrared spectroscopy: a methodological approach

Analytical and Bioanalytical Chemistry ◽

10.1007/s00216-017-0296-8 ◽

2017 ◽

Vol 409 (13) ◽

pp. 3281-3288 ◽

Cited By ~ 21

Author(s):

Claudia Invernizzi ◽

Alessia Daveri ◽

Manuela Vagnini ◽

Marco Malagodi

Keyword(s):

Infrared Spectroscopy ◽

Organic Materials ◽

Methodological Approach ◽

Musical Instruments ◽

Non Invasive

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Synchrotron Radiation Microtomography: A Tool for the Non-Invasive Structural Analysis of Historical Musical Instruments

Synchrotron Radiation News ◽

10.1080/08940886.2019.1680210 ◽

2019 ◽

Vol 32 (6) ◽

pp. 17-21

Author(s):

Diego Dreossi ◽

Nicola Sodini ◽

Franco Zanini

Keyword(s):

Structural Analysis ◽

Synchrotron Radiation ◽

Musical Instruments ◽

Non Invasive ◽

Synchrotron Radiation Microtomography

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A Micro-Tomographic Insight into the Coating Systems of Historical Bowed String Instruments

Coatings ◽

10.3390/coatings9020081 ◽

2019 ◽

Vol 9 (2) ◽

pp. 81 ◽

Cited By ~ 10

Author(s):

Giacomo Fiocco ◽

Tommaso Rovetta ◽

Claudia Invernizzi ◽

Michela Albano ◽

Marco Malagodi ◽

...

Keyword(s):

Musical Instrument ◽

Musical Instruments ◽

Micro Computed Tomography ◽

String Instruments ◽

Scientific Investigations ◽

Non Invasive ◽

Construction Methods ◽

Characterization Of Materials ◽

Micro Morphology ◽

Violin Making

Musical instruments are tools for playing music, but for some of them—made by the most important historical violin makers—the myths hide the physical artwork. Ancient violin-making Masters developed peculiar construction methods and defined aesthetic canons that are still recognizable in their musical instruments. Recently, the focus of scientific investigations has been set on the characterization of materials and methods used by the ancient violin makers by means of several scientific approaches. In this work, the merits of synchrotron radiation micro-computed tomography and optical coherence tomography (OCT) for the investigation of complex coatings systems on historical bowed string musical instruments are discussed. Five large fragments removed during past restorations from instruments produced by Jacobus Stainer, Gasparo da Salò, Giovanni Paolo Maggini, and Lorenzo Guadagnini have been considered for a non-invasive insight by tomographic techniques and the results are discussed considering previous micro-invasive investigations. The tomographic approach allows to highlight the micro-morphology of the coating systems and offers preliminary information on the methods that were employed by the ancient Masters to treat the wood and finish the musical instrument.

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Non-invasive infrared spectroscopic techniques for the characterization of medicinal plants and their constituents

Planta Medica ◽

10.1055/s-0029-1234278 ◽

2009 ◽

Vol 75 (09) ◽

Author(s):

CW Huck

Keyword(s):

Medicinal Plants ◽

Spectroscopic Techniques ◽

Non Invasive ◽

Infrared Spectroscopic

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In search of the camp of the IV Scythian legion near ancient Artaxata: research at Pokr Vedi 2015–2018

10.31338/uw.2083-537x.pam29.2.17 ◽

2020 ◽

pp. 409-432

Author(s):

Oskar Kubrak ◽

Paulina Kubrak ◽

Mkrtich H. Zardaryan

Keyword(s):

Electrical Resistivity ◽

Aerial Photography ◽

Magnetic Measurements ◽

Roman Army ◽

Field Surveys ◽

Non Invasive ◽

Southern Border ◽

Building Activities ◽

Geophysical Measurements ◽

Selection Of

During the last years of Emperor Trajan’s reign, the Legio IV Scythica was stationed in the capital of Armenia at that time, Artaxata. It had made its way there within the scope of the Roman campaign against the Parthians. Its presence was immortalised on stamped rooftiles, bricks and a monumental inscription discovered by the southern border of the present-day village of Pokr Vedi. The inscription carved into limestone confirms the building activities of the Roman army. Similar inscriptions were frequently placed on the gates and most important buildings in legionary camps. Polish and Armenian archaeologists undertook a joint search for the supposed camp of the Fourth Scythian Legion in the vicinity of the present-day village of Pokr Vedi, where the above-mentioned construction inscription had been found. The field surveys conducted within the framework of the Pokr Vedi Project were mainly of a non-invasive character. The following were applied: surface prospection, aerial photography, interviews with the inhabitants, scanning of part of the terrain and geophysical measurements done using two methods: electrical resistivity and magnetic measurements. The accumulated data enabled the selection of sites in which survey trenches were located

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Comparison of Spectroscopic Techniques Combined with Chemometrics for Cocaine Powder Analysis

Journal of Analytical Toxicology ◽

10.1093/jat/bkaa101 ◽

2020 ◽

Vol 44 (8) ◽

pp. 851-860

Author(s):

Joy Eliaerts ◽

Natalie Meert ◽

Pierre Dardenne ◽

Vincent Baeten ◽

Juan-Antonio Fernandez Pierna ◽

...

Keyword(s):

Gas Chromatography ◽

Near Infrared ◽

Evaluation Criteria ◽

Classification Model ◽

Support Vector ◽

Spectroscopic Techniques ◽

Data Set ◽

Promising Tool ◽

Powder Analysis ◽

Mir Spectra

Abstract Spectroscopic techniques combined with chemometrics are a promising tool for analysis of seized drug powders. In this study, the performance of three spectroscopic techniques [Mid-InfraRed (MIR), Raman and Near-InfraRed (NIR)] was compared. In total, 364 seized powders were analyzed and consisted of 276 cocaine powders (with concentrations ranging from 4 to 99 w%) and 88 powders without cocaine. A classification model (using Support Vector Machines [SVM] discriminant analysis) and a quantification model (using SVM regression) were constructed with each spectral dataset in order to discriminate cocaine powders from other powders and quantify cocaine in powders classified as cocaine positive. The performances of the models were compared with gas chromatography coupled with mass spectrometry (GC–MS) and gas chromatography with flame-ionization detection (GC–FID). Different evaluation criteria were used: number of false negatives (FNs), number of false positives (FPs), accuracy, root mean square error of cross-validation (RMSECV) and determination coefficients (R2). Ten colored powders were excluded from the classification data set due to fluorescence background observed in Raman spectra. For the classification, the best accuracy (99.7%) was obtained with MIR spectra. With Raman and NIR spectra, the accuracy was 99.5% and 98.9%, respectively. For the quantification, the best results were obtained with NIR spectra. The cocaine content was determined with a RMSECV of 3.79% and a R2 of 0.97. The performance of MIR and Raman to predict cocaine concentrations was lower than NIR, with RMSECV of 6.76% and 6.79%, respectively and both with a R2 of 0.90. The three spectroscopic techniques can be applied for both classification and quantification of cocaine, but some differences in performance were detected. The best classification was obtained with MIR spectra. For quantification, however, the RMSECV of MIR and Raman was twice as high in comparison with NIR. Spectroscopic techniques combined with chemometrics can reduce the workload for confirmation analysis (e.g., chromatography based) and therefore save time and resources.

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Children’s Activity Classification for Domestic Risk Scenarios Using Environmental Sound and a Bayesian Network

Healthcare ◽

10.3390/healthcare9070884 ◽

2021 ◽

Vol 9 (7) ◽

pp. 884

Author(s):

Antonio García-Domínguez ◽

Carlos E. Galván-Tejada ◽

Ramón F. Brena ◽

Antonio A. Aguileta ◽

Jorge I. Galván-Tejada ◽

...

Keyword(s):

Feature Selection ◽

Naive Bayes ◽

Naïve Bayes ◽

Classification Model ◽

Activity Classification ◽

Environmental Sound ◽

Non Invasive ◽

Akaike Criterion ◽

Data Source ◽

Feature Selection Techniques

Children’s healthcare is a relevant issue, especially the prevention of domestic accidents, since it has even been defined as a global health problem. Children’s activity classification generally uses sensors embedded in children’s clothing, which can lead to erroneous measurements for possible damage or mishandling. Having a non-invasive data source for a children’s activity classification model provides reliability to the monitoring system where it is applied. This work proposes the use of environmental sound as a data source for the generation of children’s activity classification models, implementing feature selection methods and classification techniques based on Bayesian networks, focused on the recognition of potentially triggering activities of domestic accidents, applicable in child monitoring systems. Two feature selection techniques were used: the Akaike criterion and genetic algorithms. Likewise, models were generated using three classifiers: naive Bayes, semi-naive Bayes and tree-augmented naive Bayes. The generated models, combining the methods of feature selection and the classifiers used, present accuracy of greater than 97% for most of them, with which we can conclude the efficiency of the proposal of the present work in the recognition of potentially detonating activities of domestic accidents.

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Forensic analysis of beverage stains using hyperspectral imaging

Scientific Reports ◽

10.1038/s41598-021-85737-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Binu Melit Devassy ◽

Sony George

Keyword(s):

Hyperspectral Imaging ◽

Crime Scene ◽

Forensic Analysis ◽

Classification Model ◽

Support Vector ◽

Additional Information ◽

Non Invasive ◽

Spectral Bands ◽

Data Dimensionality Reduction ◽

Gradient Based

AbstractDocumentation and analysis of crime scene evidences are of great importance in any forensic investigation. In this paper, we present the potential of hyperspectral imaging (HSI) to detect and analyze the beverage stains on a paper towel. To detect the presence and predict the age of the commonly used drinks in a crime scene, we leveraged the additional information present in the HSI data. We used 12 different beverages and four types of paper hand towel to create the sample stains in the current study. A support vector machine (SVM) is used to achieve the classification, and a convolutional auto-encoder is used to achieve HSI data dimensionality reduction, which helps in easy perception, process, and visualization of the data. The SVM classification model was re-established for a lighter and quicker classification model on the basis of the reduced dimension. We employed volume-gradient-based band selection for the identification of relevant spectral bands in the HSI data. Spectral data recorded at different time intervals up to 72 h is analyzed to trace the spectral changes. The results show the efficacy of the HSI techniques for rapid, non-contact, and non-invasive analysis of beverage stains.

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