Thick-target PIGE analysis of plant materials preconcentrated by dry ashing

An analytical methodology has been developed for the UV-spectrophotometric determination of carbaryl in waters after its preconcentration onto a polyether type polyurethane foam followed by on-line elution. The aforementioned strategy offers an easy way for in-field sampling and to improve the analytical sensitivity. Several chemical and flow variables (mass of sorbent, sample flow rate, sample volume and carrier flow rate) were studied to ensure the best performance of the system. Recovery studies, carried out on natural water samples spiked with known amounts of carbaryl at concentration levels between 250 and 500 mug l(-1), provided recovery percentages between 94 and 105%. A detection limit of 12 mug l(-1) was achieved and a variation coefficient of 3.4% was obtained at 0.50 mug ml(-1).     

Amino substituted 1-oxa-3-azabutatrienium salts: preparation, structure and reaction with carbonyl compounds

N,N-Dimethylformamide ($\text{4a}$) and N,N-dimethylpivalamide ($\text{4b}$) react with carbonyl chloride isocyanate ($\text{5}$) in the presence of antimony pentachloride to afford the amino substituted 1-oxa-3-azabutatrienium hexachloroantimonates $\text{6a}$,$\text{b}$. An X-ray diffraction analysis of $\text{6a}$ confirms the proposed structure. The heterocumulenes $\text{6a}$,$\text{b}$ react with aldehydes, ketones and tertiary carboxamides to give the amino substituted 2-azaallenium salts $\text{13a}$-$\text{O}$ in high yields.     

Smart materials based on self-assembled hydrogen-bonded comb-shaped supramolecules

Block copolymer self-assembly and supramolecular chemistry can be combined most naturally to prepare smart polymer nanomaterials. An attractive route is based on comb-shaped supramolecules, obtained by attaching side chains to (co)polymers by physical (non-covalent) interactions. Hydrogen bonding is a key element of our approach. It combines an ease of synthesis with other important approach-specific elements, such as hierarchical self-assembly, strongly enhanced processability, swelling, and cleaving. Functional properties discussed include anisotropic proton conductivity, switching proton conductivity, electronically conducting nanowires, polarized luminance, dielectric stacks (optical reflectivity), functional membranes, and nano objects.     

On applicability of PCA,voxel-wise variance normalization and dimensionality assumptions for sliding temporal window sICA in resting-state fMRI

Subject-level resting-state fMRI (RS-fMRI) spatial independent component analysis (sICA) may provide new ways to analyze the data when performed in the sliding time window. However, whether principal component analysis (PCA) and voxel-wise variance normalization (VN) are applicable pre-processing procedures in the sliding-window context, as they are for regular sICA, has not been addressed so far. Also model order selection requires further studies concerning sliding-window sICA. In this paper we have addressed these concerns. First, we compared PCA-retained subspaces concerning overlapping parts of consecutive temporal windows to answer whether in-window PCA and VN can confound comparisons between sICA analyses in consecutive windows. Second, we compared the PCA subspaces between windowed and full data to assess expected comparability between windowed and full-data sICA results. Third, temporal evolution of dimensionality estimates in RS-fMRI data sets was monitored to identify potential challenges in model order selection in a sliding-window sICA context. Our results illustrate that in-window VN can be safely used, in-window PCA is applicable with most window widths and that comparisons between windowed and full data should not be performed from a subspace similarity point of view. In addition, our studies on dimensionality estimates demonstrated that there are sustained, periodic and very case-specific changes in signal-to-noise ratio within RS-fMRI data sets. Consequently, dimensionality estimation is needed for well-founded model order determination in the sliding-window case. The observed periodic changes correspond to a frequency band of ≤ 0.1 Hz, which is commonly associated with brain activity in RS-fMRI and become on average most pronounced at window widths of 80 and 60 time points (144 and 108 s, respectively). Wider windows provided only slightly better comparability between consecutive windows, and 60 time point or shorter windows also provided the best comparability with full-data results. Further studies are needed to determine the cause for dimensionality variations.     

Spectroscopic imaging with volume selection by unpaired adiabatic pi pulses: theory and application

In NMR spectroscopy, volume selection can be advantageously achieved using adiabatic pi pulses, which enable high bandwidth and B(1) insensitivity. In order to avoid the generation of non-linear phase profiles and the subsequent signal loss caused by incoherent averaging, adiabatic pi pulses are usually used in pairs for volume selection in each spatial dimension. Alternatively, when performing spectroscopic imaging (SI), a high enough spatial resolution results in negligible phase dispersion within each pixel. This allows using only one pulse per selected spatial dimension, resulting in a reduced echo-time and reduced power deposition. In this work, the feasibility of such an approach is explored theoretically and numerically, allowing the derivation of explicit conditions to obtain SI images without artifact. Adequate spatial and spectral post-processing procedures are described to compensate for the effect of non-linear phase profiles. These developments are applied to SI in the rat brain at 9.4 T, using a new adiabatic sequence named Pseudo-LASER.