Abstract: This study investigated concentration profiles of trace, rare earth and platinum group metals in fluvial sediments from the Pangani river basin (43,650 km2), one of the largest river basins in Tanzania, to assess its environmental quality. Sediment samples were collected in two distinct seasons from 12 representative sites of diverse land-use practices and characterised by ICP-MS after optimised microwave digestion. Ecological risks were assessed by evaluation of pollution index and comparison with legislated sediment quality guidelines (SQG). The results revealed contamination by some trace metals (e.g. Pb, V, Cu, Cr, Ni, Cd, As, Co, Mn and Zn) in concentrations ranging from 0.7 to 2940 mg kg−1, and four rare earth elements (Y, Ce, Nd, Yb) in concentrations ranging from 0.9 (Yb) to 500 mg kg−1 dry weight (Ce), which significantly exceeded the estimated background values at some stations. Palladium was the only platinum group element that was detected in quantifiable concentrations (0.33.5 mg kg−1). Concentrations of some trace metals exceeded the SQGs at some localised areas. Principal component analysis and multivariate correlations indicated geochemical characteristics of the area as the major control of metal concentrations and spatial variability. Organic matter and clay contents also played a significant role in metal distributions. Assessment of land-use practices upstream of the sampling locations was used to trace potential anthropogenic sources of metal enrichments, where highest levels were found in areas close to urban centres and agricultural activities. The study provides baseline data for future monitoring programs, and highlights the need for more comprehensive analysis involving a wider spatio-temporal scale and ecotoxicological risk assessment.

Abstract: Several authors had estimated the displacements per atom cross sections under different approximations and models, including most of the main gamma- and electron-material interaction processes. These previous works used numerical approximation formulas which are applicable for limited energy ranges. We proposed the Monte Carlo assisted Classical Method (MCCM), which relates the established theories about atom displacements to the electron and positron secondary fluence distributions calculated from the Monte Carlo simulation. In this study the MCCM procedure is adapted in order to estimate the displacements per atom cross sections for gamma and electron irradiation. The results obtained through this procedure are compared with previous theoretical calculations. An improvement in about 10-90% for the gamma irradiation induced dpa cross section is observed in our results on regard to the previous evaluations for the studied incident energies. On the other hand, the dpa cross section values produced by irradiation with electrons are improved by our calculations in about 5-50% when compared with the theoretical approximations. When thin samples are irradiated with electrons, more precise results are obtained through the MCCM (in about 20-70%) with respect to the previous studies. (C) 2014 Elsevier B.V. All rights reserved.

Abstract: The aim of the present work is to study the radiation damage induced in LYSO and LuYAP crystals by the gamma radiation and the secondary electrons/positrons generated. The displacements per atom (dpa) distributions inside each material were calculated following the Monte Carlo assisted Classical Method (MCCM) introduced by the authors. As gamma sources were used Sc-44, Na-22 and V-48. Also the energy of gammas from the annihilation processes (511 keV) was included in the study. This procedure allowed studying the in-depth dpa distributions inside each crystal for all four sources. It was also possible to obtain the separate contribution from each atom to the total dpa. The LYSO crystals were found to receive more damage, mainly provoked by the displacements of silicon and oxygen atoms.

Abstract: Atmospheric nitrogen dioxide (NO2) and sulfur dioxide (SO2) levels were monitored simultaneously by means of Radiello passive samplers at six sites of Santa Clara city, Cuba, in the cold and the warm seasons in 2010. The dissolved ionic forms of NO2 and SO2 as nitrate and sulfite plus sulfate, respectively, were determined by means of ion chromatography. Analysis of NO2 as nitrite was also performed by UVVis spectrophotometry. For NO2, significant t tests show good agreement between the results of IC and UVVis methods. The NO2 and SO2 concentrations peaked in the cold season, while their minimum levels were experienced in the warm season. The pollutant levels do not exceed the maximum allowable limit of the Cuban Standard 39:1999, i.e., 40 μg/m3 and 50 μg/m3 for NO2 and SO2, respectively. The lowest pollutant concentrations obtained in the warm season can be attributed to an increase in their removal via precipitation (scavenging) while to the decreased traffic density and industrial emission during the summer holidays (e.g., July and August).

Abstract: A new method to estimate case specific prediction uncertainty for univariate trilinear partial least squares (tri-PLS1) regression is introduced. This method is, from a theoretical point of view, the most exact finite sample approximation to true prediction uncertainty that has been reported up till now. Using the new method, different error sources can be propagated, which is an advantage that cannot be offered by data driven approaches such as the bootstrap. In a concise example, it is illustrated how the method can be applied. In the Appendix, efficient algorithms are presented to compute the estimates required.

Abstract: X-ray radiographic images of paintings often show little or no contrast. In order to increase the contrast in radiographic images we measured the X-ray spectrum of a low power X-ray tube, after passing through the painting, with a high energy-resolution SDD detector. To obtain images, the detector is collimated with a 400 mu m diameter pinhole and the painting was moved through the beam in the x and y-direction using a dwell time of a few seconds per pixel. The data obtained consists of a data cube of, typically, 200 x 200 pixels and a 512-channel X-ray spectrum for each pixel, spanning the energy range from 0 to 40 keV. Having the absorbance spectrum available for each pixel, we are able, a posteriori, to produce images by edge subtraction for any given element. In this way high contrast, element-specific, images can be obtained. Because of the high energy-resolution a much simpler edge subtraction algorithm can be applied. We also used principal-component imaging to obtain, in a more automated way, images with high contrast. Some of these images can easily be attributed to specific elements. It turns out that preprocessing of the spectral data is crucial for the success of the multivariate image processing.