Abstract: The radiation damage, in terms of atom displacements, induced by gamma irradiation in LYSO and LuYAP crystals is presented. Sc-44, Na-22 and V-48 are used as gamma sources for this study. The energy of gammas from the electron positron annihilation processes (511 keV) is also included in the study. The atom displacements distributions inside each material are calculated following the Monte Carlo assisted Classical Method introduced by the authors. This procedure also allows to study the atom displacements in-depth distributions inside each crystal. The atom displacements damage in LYSO crystals is found to be higher than in LuYAP crystals, mainly provoked by the displacements of silicon and oxygen atoms. But the difference between atom displacements produced in LYSO and LuYAP decreases when more energetic sources are used. On the other hand, the correlation between the atom displacements and energy deposition in-depth distributions is excellent. The atom displacements to energy deposition ratio is found to increases with more energetic photon sources. LYSO crystals are then more liable to the atom displacements damage than LuYAP crystals. (C) 2015 Elsevier B.V. All rights reserved.

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: Two sampling campaigns in suburban places in the north zone of Santa Clara city, Cuba, have been carried out on a weekly base with the use of Radiello passive diffusion tubes in order to monitor the tropospheric ozone (O3) levels in 2010. The first campaign was scheduled from February to April (cold season) and the second one in August and October (warm season), both of them at two sampling sites, i.e., Farm and School of Art Instructors. After aqueous extraction, the samples were analyzed by UVVIS spectrophotometry. A seasonal trend was observed with the maximum O3 concentrations in the cold season and the minimum levels in the warm season. Samples collected during the cold season showed the highest O3 levels. Higher levels were reached at the Farm site with average values of about 58 ± 12 μg/m3, which exceeded the limit of the Cuban Standard 99:1999. In the warm season, the O3 concentrations were similar for both sites, but lower than those observed in the cold season. The overall, seasonal average value was found to be 24 μg/m3. Despite the higher weekly average temperatures in August, the O3 concentrations during this month showed the lowest values of the whole sampling period, which finding is in agreement with that reported by the Meteorological Institute of Cuba. Mathematical models, based on the Cochrane-Orcutt algorithm, were fitted to the acquired data set to explain the change in the tropospheric ozone concentrations under various meteorological conditions during the two campaigns. The correlation coefficients for both the cold and the warm seasons demonstrated a strong correlation, i.e., 0.779 and 0.951, respectively. The high correlation of wind speed in the model from the first sampling campaign explains the sharp decrease in O3 concentrations at the SAI sampling site from the sixth week of sampling.

Abstract: Size-fractionated aerosol samples, collected over the Atlantic Ocean, were analyzed for up to 20 elements by PIXE. Using a sailboat as sampling platform, duplicate samples were taken for two-day periods by means of battery operated 6-stage cascade impactors, positioned about 8 m above the sea surface. In the PIXE analysis of the fine particle stages (stages 3 to 5) a 5 times smaller beam size was used than for stages 1 and 2. This led to significant improvement in the detection limits for the former stages. The results from the duplicate impactor samples were normally in good agreement, indicating that the combined uncertainty of sampling and PIXE analysis was of the order of 20%. The precision of the PIXE analysis alone was investigated by rebombarding some samples six months after the first analysis. The trends with time of the fine particle sulfur and the coarse particle iron concentrations are discussed in some detail.

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: The most unique and only known 16th century Antwerp majolica tile floor in Belgium is situated in a tower of the Rameyenhof castle (Gestel, Belgium). This exceptional work of art has recently been investigated in situ by using X-ray fluorescence (XRF) and Raman spectroscopy in order to study the material characteristics. This study reports on the result of the analyses based on the novel combination of non-destructive and portable instrumentation, including a handheld XRF spectrometer for obtaining elemental information and a mobile Raman spectrometer for retrieving structural and molecular information on the floor tiles in the Rameyenhof castle and on a second, similar medallion, which is stored in the Rubens House museum in Antwerp (Belgium). The investigated material, majolica, is a type of ceramic, which fascinated many people and potters throughout history by its beauty and colourful appearance. In this study the characteristic major/minor and trace element signature of 16th century Antwerp majolica is determined and the pigments used for the colourful paintings present on the floor are identified. Furthermore, based on the elemental fingerprint of the white glaze, and in particular on the presence of zinc in the tiles – an element that was not used for making 16th century majolica – valuable information about the originality of the chapel floor and the two central medallions is acquired. (C) 2014 Elsevier B.V. All rights reserved.

Abstract: Bridging the gap between complex signal data output and clear interpretation by non-expert end-users is a major challenge many scientists face when converting their scientific technology into a real-life application. Currently, pattern recognition algorithms are the most frequently encountered signal data interpretation algorithms to close this gap, not in the least because of their straight-forward implementation via convenient software packages. Paradoxically, just because their implementation is so straight-forward, it becomes cumbersome to integrate the expert's domain-specific knowledge. In this work, a novel signal data interpretation approach is presented that uses this domain-specific knowledge as its fundament, thereby fully exploiting the unique expertise of the scientist. The new approach applies data preprocessing in an innovative way that transcends its usual purpose and is easy to translate into a software application. Multiple case studies illustrate the straight-forward application of the novel approach. Ultimately, the approach is highly suited for integration in various (bio)analytical applications that require interpretation of signal data.