Rock mass structural recognition from drill monitoring technology in underground mining using discontinuity index and machine learning techniques

A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for calibration.Data from two underground operations with different drilling technology and different rock mass characteristics are considered,which generalizes the application of the methodology to different sites and ensures the full operational integration of MWD data analysis.Two approaches are followed for site-specific structural model building:a discontinuity index(DI)built from variations in MWD parameters,and a machine learning(ML)classifier as function of the drilling parameters and their variability.The prediction ability of the models is quantitatively assessed as the rate of recognition of discontinuities observed in borehole logs.Differences between the parameters involved in the models for each site,and differences in their weights,highlight the site-dependence of the resulting models.The ML approach offers better performance than the classical DI,with recognition rates in the range 89%to 96%.However,the simpler DI still yields fairly accurate results,with recognition rates 70%to 90%.These results validate the adaptive MWD-based methodology as an engineering solution to predict rock structural condition in underground mining operations.

Study of Functionalized Gold Nanoparticles with Anti-gp63 IgG Antibody for the Detection of Glycoprotein gp63 in Membrane Surface of <i>Leishmania</i>Genus Parasites

In this work we present the preparation and functionalization of gold nanoparticles (AuNPs) for the detection of presence of gp63 glycoprotein in the surface of Leishmania genus parasites. AuNPs were prepared by induced laser ablation in a clean and biologically suitable media. The nanoparticles were functionalized with anti-gp63 lgG antibody in order to study the interaction with the glycoprotein component gp63 (63 kDa) present on the membrane surface of Leishmania genus parasites. The functionalized AuNPs showed potential as a spectrometric indicator of the parasite existence, both by the detection of the presence of the gp63 in solution and through the specific interaction with the parasites in vitro. The specificity of the study opens a new line of research on the use of modified nanoparticles in the development of a fast and easy assay for Leishmaniosis diagnostics.

Radioisotopes and Analytical Chemistry

When Periodic Chart of elements is consulted to find natural radioisotopes, one firstly finds tritium, followed by 10Be, 14C, 50V and many others. Before Bi, 12 cosmogenic radioisotopes are listed. They are those continuously produced by nuclear reactions among light elements present in earthly atmosphere and radiations coming from the outside space. Eighteen additional primordial radioisotopes are listed. They were created at the same time that the non-radioactive isotopes composing the 92 natural elements in the periodic table. From Bi on, every isotope is radioactive, up to U. Then follow the artificial elements produced by laboratory nuclear reactions from Np to element with atomic number 118. In this way, from 118 known elements, 64 are radioactive, which amount 55% of all those units forming the chemical compounds. Therefore, the complete understanding of radioactivity should be a suitable tool to advance our knowledge of Universe, and consequent applications to get better living conditions. So, this paper deals with radioisotopes as suitable instruments for chemical analysis.