The Effect of Boundary Conditions on Gas-phase Synthesised Silver Nanoparticles

We have prepared spherical non-agglomerated silver nanoparticles by an evaporation–condensation–dilution/cooling technique. Silver was evaporated from a crucible in a tubular flow reactor. A porous tube diluter was used to quench the carrier gas at the outlet of the reactor to enhance the formation of small particles and to suppress agglomeration and other particle growth mechanisms. The number size distribution of the prepared particles was measured with a differential mobility analyser–condensation nucleus counter combination and the size and the shape of the particles were analysed with transmission electron microscope. The system was modelled using a sectional aerosol dynamics computer code to estimate the importance of different aerosol processes. In all conditions the particles obtained were non-agglomerated and spherical. The mean particle diameter varied from 4 to 10-nm depending on boundary conditions. From the modelling studies it can be concluded that the nucleation rate is the most important parameter controlling the final particle size.     

The preparation of a cabbage reference material for environmental monitoring and food analysis

 Cabbage is frequently used in environmental monitoring and food control, and, hence, cabbage reference materials (RMs) are required for ensuring quality assurance. A cabbage RM was prepared in view of certification of specific elements from the "black list" of high toxicological interest and nutritive importance. All tasks of the RM production (production of the plant material, cutting and freeze-drying, determination of the residual water content, preparation of the RM, homogeneity testing, stability testing, certification measurements) are described in detail. Received: 12 November 1999 / Accepted: 29 January 2000     

Effects of various washing procedures on the chromium content of human scalp hair

The effects of four wash procedures on the concentration of chromium in a pooled sample of human scalp hair are compared. The wash solutions examined are Triton X-100, sodium lauryl sulphate, acetone, and a mixture (1 + 1) of hexane and ethanol. The plateaux reached for hair chromium concentration are functions of the number of washings, and are characteristic for each wash solution. The wash procedure recommended involves two 20-min washes with aqueous 1% sodium lauryl sulphate solution after a hexane rinse.     

Determination of naphthodianthrones and phloroglucinols from Hypericum perforatum extracts by liquid chromatography/tandem mass spectrometry

Hypericum perforatum L. (St. John's Wort) has long been known as a medicinal plant, and has been used for the treatment of depression and neuralgic disorders. Its main active constituents are believed to be a naphthodianthrone, hypericin, and a phloroglucinol, hyperforin. A sensitive high performance liquid chromatography (HPLC)/electrospray tandem mass spectrometric method for fast simultaneous determination of six major naphthodianthrones and phloroglucinols of Hypericum perforatum extract has been developed. The method, based on multiple dissociation reaction monitoring (MRM), allows the analysis of hypericin, protohypericin, pseudohypericin, protopseudo-hypericin, hyperforin and adhyperforin from the extract in less than 5 min. Good linearity over the range 0.1-1000 ng/mL for hyperforin and 2-500 ng/mL for hypericin was observed. Intra-assay accuracy and precision varied from 2 to 19% within these ranges. Lower levels of quantitation for hyperforin were 0.5 ng/mL and 2 ng/mL for hypericin.     

Model selection by sequentially normalized least squares

Model selection by means of the predictive least squares (PLS) principle has been thoroughly studied in the context of regression model selection and autoregressive (AR) model order estimation. We introduce a new criterion based on sequentially minimized squared deviations, which are smaller than both the usual least squares and the squared prediction errors used in PLS. We also prove that our criterion has a probabilistic interpretation as a model which is asymptotically optimal within the given class of distributions by reaching the lower bound on the logarithmic prediction errors, given by the so called stochastic complexity, and approximated by BIC. This holds when the regressor (design) matrix is non-random or determined by the observed data as in AR models. The advantages of the criterion include the fact that it can be evaluated efficiently and exactly, without asymptotic approximations, and importantly, there are no adjustable hyper-parameters, which makes it applicable to both small and large amounts of data.     

Random waypoint model in n-dimensional space

The random waypoint model (RWP) is one of the most widely used mobility models in performance analysis of mobile wireless networks. In this paper we extend the previous work by deriving an analytical formula for the stationary distribution of a node moving according to a RWP model in n-dimensional space.