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

2017 ◽  
Vol 409 (13) ◽  
pp. 3281-3288 ◽  
Author(s):  
Claudia Invernizzi ◽  
Alessia Daveri ◽  
Manuela Vagnini ◽  
Marco Malagodi
ACTA IMEKO ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 201
Author(s):  
Giacomo Fiocco ◽  
Silvia Grassi ◽  
Claudia Invernizzi ◽  
Tommaso Rovetta ◽  
Michela Albano ◽  
...  

<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 (&gt; 0.9) was achieved in the prediction, providing the groundwork for the application of a fast and rigorous methodological approach.


Biosensors ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 389
Author(s):  
Kogulan Paulmurugan ◽  
Vimalan Vijayaragavan ◽  
Sayantan Ghosh ◽  
Parasuraman Padmanabhan ◽  
Balázs Gulyás

Functional Near-Infrared Spectroscopy (fNIRS) is a wearable optical spectroscopy system originally developed for continuous and non-invasive monitoring of brain function by measuring blood oxygen concentration. Recent advancements in brain–computer interfacing allow us to control the neuron function of the brain by combining it with fNIRS to regulate cognitive function. In this review manuscript, we provide information regarding current advancement in fNIRS and how it provides advantages in developing brain–computer interfacing to enable neuron function. We also briefly discuss about how we can use this technology for further applications.


2021 ◽  
Vol 22 (18) ◽  
pp. 9940
Author(s):  
Soo-In Sohn ◽  
Subramani Pandian ◽  
Young-Ju Oh ◽  
John-Lewis Zinia Zaukuu ◽  
Hyeon-Jung Kang ◽  
...  

Near-infrared spectroscopy (NIRS) has become a more popular approach for quantitative and qualitative analysis of feeds, foods and medicine in conjunction with an arsenal of chemometric tools. This was the foundation for the increased importance of NIRS in other fields, like genetics and transgenic monitoring. A considerable number of studies have utilized NIRS for the effective identification and discrimination of plants and foods, especially for the identification of genetically modified crops. Few previous reviews have elaborated on the applications of NIRS in agriculture and food, but there is no comprehensive review that compares the use of NIRS in the detection of genetically modified organisms (GMOs). This is particularly important because, in comparison to previous technologies such as PCR and ELISA, NIRS offers several advantages, such as speed (eliminating time-consuming procedures), non-destructive/non-invasive analysis, and is inexpensive in terms of cost and maintenance. More importantly, this technique has the potential to measure multiple quality components in GMOs with reliable accuracy. In this review, we brief about the fundamentals and versatile applications of NIRS for the effective identification of GMOs in the agricultural and food systems.


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