Graph clustering and portable X-Ray Fluorescence: An application for in situ, fast and preliminary classification of transport amphoras

In the last decade, numerous papers have been delivered on the potential of portable X-Ray Fluorescence (XRF) in archaeological ceramics. Additionally, new chemometric methods have been proposed to manage chemical dataset and facilitate the use of geochemical discrimination for provenance classification of ancient ceramics. In this contribute, the potential of portable Energy Dispersive X-Ray Fluorescence (ED-XRF) analysis and chemical data processing by Graph Clustering is evaluated for provenance classification of archaeological potteries, discussing possible merits and limits of the employed routine. A ceramic assemblage represented by seventy-three transport amphorae classified by typological analysis have been used as testing materials; spectra have been collected on samples simulating in situ analysis conditions (e.g. on fresh cut surfaces without any preparation) and Graph Clustering method has been applied in chemical data processing; comparison with classical Cluster Analysis (CA) and Principal Component Analysis (PCA) is also evaluated. The obtained results favor the use of Graph Clustering for a preliminary classification of ceramics, which can be chemically analyzed in easy, fast and non-destructive way. With a 75.35% of correct attribution, the study shows the suitability of portable ED-XRF in rapid screening of a large number of ceramic samples usually recovered in the framework of archaeological excavation. Misclassifications have been mostly verified for samples exhibiting a coarse-grained clay paste, suggesting that the method is particularly suitable for fine-grained ceramic materials

Shock waves in laser-induced plasmas

The production of a plasma by a pulsed laser beam in solids, liquids or gas is often associated with the generation of a strong shock wave, which can be studied and interpreted in the framework of the theory of strong explosion. In this review, we will briefly present a theoretical interpretation of the physical mechanisms of laser-generated shock waves. After that, we will discuss how the study of the dynamics of the laser-induced shock wave can be used for obtaining useful information about the laser-target interaction (for example, the energy delivered by the laser on the target material) or on the physical properties of the target itself (hardness). Finally, we will focus the discussion on how the laser-induced shock wave can be exploited in analytical applications of Laser-Induced Plasmas as, for example, in Double-Pulse Laser-Induced Breakdown Spectroscopy experiments

Application of double-pulse micro-LIBS 3D compositional mapping to the analysis of ceramics

We developed a new Laser-Induced Breakdown Spectroscopy (LIBS) instrument for 3D compositional mappings of archaeological objects. The system, based on the Modì double-pulse instrument, allows the reconstruction of maps with lateral resolution up to 20 microns and sub-micron depth resolution

Improvement of the performances of a commercial hand-held laser-induced breakdown spectroscopy instrument for steel analysis using multiple artificial neural networks.

In this article, we present a study on the optimization of the analytical performance of a commercial hand-held laser-induced breakdown spectroscopy instrument for steel analysis. We show how the performances of the instrument can be substantially improved using a non-linear calibration approach based on a set of Artificial Neural Networks (ANNs), one optimized for the determination of the major elements of the alloy, and the others specialized for the analysis of minor components. Tests of the instrument on steel samples used for instrument internal calibration demonstrate a comparable accuracy with the results of the ANNs, while the latter are considerably more accurate when unknown samples, not used for calibration/training, are tested

Radiogenomics in clear cell renal cell carcinoma: correlations between advanced CT imaging (texture analysis) and microRNAs expression

Purpose: A relevant challenge for the improvement of clear cell renal cell carcinoma management could derive from the identification of novel molecular biomarkers that could greatly improve the diagnosis, prognosis, and treatment choice of these neoplasms. In this study, we investigate whether quantitative parameters obtained from computed tomography texture analysis may correlate with the expression of selected oncogenic microRNAs. Methods: In a retrospective single-center study, multiphasic computed tomography examination (with arterial, portal, and urographic phases) was performed on 20 patients with clear cell renal cell carcinoma and computed tomography texture analysis parameters such as entropy, kurtosis, skewness, mean, and standard deviation of pixel distribution were measured using multiple filter settings. These quantitative data were correlated with the expression of selected microRNAs (miR-21-5p, miR-210-3p, miR-185-5p, miR-221-3p, miR-145-5p). Both the evaluations (microRNAs and computed tomography texture analysis) were performed on matched tumor and normal corticomedullar tissues of the same patients cohort. Results: In this pilot study, we evidenced that computed tomography texture analysis has robust parameters (eg, entropy, mean, standard deviation) to distinguish normal from pathological tissues. Moreover, a higher coefficient of determination between entropy and miR-21-5p expression was evidenced in tumor versus normal tissue. Interestingly, entropy and miR-21-5p show promising correlation in clear cell renal cell carcinoma opening to a radiogenomic strategy to improve clear cell renal cell carcinoma management. Conclusion: In this pilot study, a promising correlation between microRNAs and computed tomography texture analysis has been found in clear cell renal cell carcinoma. A clear cell renal cell carcinoma can benefit from noninvasive evaluation of texture parameters in adjunction to biopsy results. In particular, a promising correlation between entropy and miR-21-5p was found

Classification of sedimentary and igneous rocks by laser induced breakdown spectroscopy and nanoparticle-enhanced laser induced breakdown spectroscopy combined with principal component analysis and graph theory

In this work, results are presented on the application of standard LIBS and Nanoparticle-Enhanced LIBS (NELIBS) to the classification of rocks (igneous and sedimentary). The classification of the spectra obtained with the two methods was performed using Principal Component Analysis (PCA) and Graph Theory method. The results obtained confirmed the advantages of the LIBS technique in geological applications, showing that excellent classification of the rocks analyzed (more than 99% of the spectra correctly classified) can be obtained using standard LIBS coupled to Graph Theory analysis, while NELIBS spectra, analyzed with the same technique, provide acceptable results, but with 10% of the spectra not classified. These findings are particularly interesting given the application of the LIBS technique in investigating natural samples having porous and/or rough surfaces

Green-synthetized silver nanoparticles for Nanoparticle-Enhanced Laser Induced Breakdown Spectroscopy (NELIBS) using a mobile instrument

When compared to other analytical techniques, LIBS shows relatively low precision and, generally, high Limits of Detection (LODs). Until recently, the attempts in improving the LIBS performances have been based on the use of more stable/powerful lasers, high sensitivity detectors or controlled environmental parameters. This can hinder the competitiveness of LIBS by increasing the instrumental setup cost and the difficulty of operation. Sample treatment has proved to be a viable and simple way to increase the LIBS signal; in particular, the Nanoparticle-Enhanced Laser Induced Breakdown Spectroscopy (NELIBS) methodology uses a deposition of metal nanoparticles on the sample to greatly increase the emission of the LIBS plasma. In this work, we used a simple, fast, â\u80\u9cgreenâ\u80\u9d and low-cost method to synthetize silver nanoparticles by using coffee extract as reducing agents for a silver nitrate solution. This allowed us to obtain nanoparticles of about 25 nm in diameter. We then explored the application of such nanoparticles to the NELIBS analysis of metallic samples with a mobile LIBS instrument. By adjusting the laser parameters and optimizing the sample preparation procedure, we obtained a NELIBS signal that is 4 times the LIBS one. This showed the potential of green-synthetized nanoparticle for NELIBS applications and suggests the possibility of an in-situ application of the technique