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A novel multifunctional silica magnetic molecularly imprinted polymer (MQDs-MIPs) nanoparticle probe was synthesized for the rapid detection of triflumuron (TFM). The fluorescence probe consists of magnetite (Fe3O4) as a core and is wrapped with a molecularly imprinted polymer doped with Mn-doped ZnS quantum dots (QDs). Under optimal detection condition, the fluorescence quenching efficiency of MIP@Fe3O4@ZnS:Mn QDs displayed a linear relationship over the concentration range of 0–27.88 μmol/L with a correlation coefficient of 0.9947. Four structurally similar compounds were selected for selectivity testing and the nanocomposite showed good selectivity with a higher imprint factor of 2.52. This developed method has the advantages of simple preparation, fast response and low toxicity for trace TFM detection. [ABSTRACT FROM AUTHOR]

Tunnel failure caused due to geologic heterogeneity and variability in both mining processes and tunnel arrangement in deep metal mines is very complex. In this paper, a quantitative risk assessment for deep tunnel failure was conducted using clustering and logistic regression. The study was performed by considering various representative evaluation indexes of geological conditions, mining disturbance, and microseismic (MS) data. Comprehensive Seismic Event Clustering (CSEC) methodology was used to analyse the MS data to filter noise data and identify seismic sources. Additionally, peak particle velocity (PPV) was used to quantitatively evaluate the influence of MS activities on the response of tunnel which would aid in determining the PPV distribution characteristics of a large regional tunnel. Furthermore, Excavation Vulnerability Potential (EVP) index was used to quantitatively evaluate the effect of site conditions on response of the tunnel. Thus, based on logistic regression, PPV and EVP were used to establish a risk assessment model to determine the tunnel damage levels and probability of damage occurrence. The successful application of the proposed method at the Ashele copper mine demonstrates that it is capable of conducting a risk assessment for tunnel failure in deep metal mines. [ABSTRACT FROM AUTHOR]