Size distribution prediction of nanoparticle agglomerates in a fluidized bed

Nanoparticles have acquired considerable attention from academia and industry due to their unique properties arising from the large surface area to volume ratio. A promising method to process these particles is fluidization. Furthermore, it is worth knowing that nanoparticles fluidize as clusters called agglomerates, formed by the relatively strong adhesion forces among the individual particles (1). These agglomerates are large, highly porous fractal structures; thus, easy to access but extremely fragile. During fluidization, agglomerates move, collide, break, reform, deform, and combine, which make them suitable for a wide range of applications. Nanopowders can fluidize with bubbles or uniformly, which show different dynamics that might affect the morphology of the fluidized agglomerates. In order to better understand the dynamic behaviour of the system, it is crucial to know the agglomerate size distribution within the fluidized bed. Therefore, we developed a model based on a simple force balance to predict the agglomerate size distribution, which enables the optimization of processing methods. Please click Additional Files below to see the full abstract

The selective reduction of NOx with NH3 over zirconia-supported vanadia catalysts

A series of sub-monolayer vanadia-on-zirconia catalysts have been prepared and the activities of these have been measured for the selective reduction of NO with NH3. It has been found that the activity per vanadium surface species depends on the square of the vanadium surface coverage. We therefore conclude that clusters of vanadia species on the surface of the catalysts are responsible for the de-NOx activity rather than isolated vanadia surface molecules

The selective reduction of NOx with NH3 over zirconia-supported vanadia catalysts

A series of sub-monolayer vanadia-on-zirconia catalysts have been prepared and the activities of these have been measured for the selective reduction of NO with NH3. It has been found that the activity per vanadium surface species depends on the square of the vanadium surface coverage. We therefore conclude that clusters of vanadia species on the surface of the catalysts are responsible for the de-NOx activity rather than isolated vanadia surface molecules

New methods for next generation sequencing based microRNA expression profiling

<p>Abstract</p> <p>Background</p> <p>MicroRNAs are small non-coding RNA transcripts that regulate post-transcriptional gene expression. The millions of short sequence reads generated by next generation sequencing technologies make this technique explicitly suitable for profiling of known and novel microRNAs. A modification to the small-RNA expression kit (SREK, Ambion) library preparation method for the SOLiD sequencing platform is described to generate microRNA sequencing libraries that are compatible with the Illumina Genome Analyzer.</p> <p>Results</p> <p>High quality sequencing libraries can successfully be prepared from as little as 100 ng small RNA enriched RNA. An easy to use perl-based analysis pipeline called E-miR was developed to handle the sequencing data in several automated steps including data format conversion, 3' adapter removal, genome alignment and annotation to non-coding RNA transcripts. The sample preparation and E-miR pipeline were used to identify 37 cardiac enriched microRNAs in stage 16 chicken embryos. Isomir expression profiles between the heart and embryo were highly correlated for all miRNAs suggesting that tissue or cell specific miRNA modifications do not occur.</p> <p>Conclusions</p> <p>In conclusion, our alternative sample preparation method can successfully be applied to generate high quality miRNA sequencing libraries for the Illumina genome analyzer.</p

Recommendations for future research in relation to pediatric pulmonary embolism: communication from the SSC of the ISTH

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142464/1/jth13902_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142464/2/jth13902.pd

A 2000-year annual record of snow accumulation rates for Law Dome, East Antarctica

Accurate high-resolution records of snow accumulation rates in Antarctica are crucial for estimating ice sheet mass balance and subsequent sea level change. Snowfall rates at Law Dome, East Antarctica, have been linked with regional atmospheric circulation to the mid-latitudes as well as regional Antarctic snowfall. Here, we extend the length of the Law Dome accumulation record from 750 years to 2035 years, using recent annual layer dating that extends to 22 BCE. Accumulation rates were calculated as the ratio of measured to modelled layer thicknesses, multiplied by the long-term mean accumulation rate. The modelled layer thicknesses were based on a power-law vertical strain rate profile fitted to observed annual layer thickness. The periods 380–442, 727–783 and 1970–2009 CE have above-average snow accumulation rates, while 663–704, 933–975 and 1429–1468 CE were below average, and decadal-scale snow accumulation anomalies were found to be relatively common (74 events in the 2035-year record). The calculated snow accumulation rates show good correlation with atmospheric reanalysis estimates, and significant spatial correlation over a wide expanse of East Antarctica, demonstrating that the Law Dome record captures larger-scale variability across a large region of East Antarctica well beyond the immediate vicinity of the Law Dome summit. Spectral analysis reveals periodicities in the snow accumulation record which may be related to El Niño–Southern Oscillation (ENSO) and Interdecadal Pacific Oscillation (IPO) frequencies

CORE_TF: a user-friendly interface to identify evolutionary conserved transcription factor binding sites in sets of co-regulated genes

<p>Abstract</p> <p>Background</p> <p>The identification of transcription factor binding sites is difficult since they are only a small number of nucleotides in size, resulting in large numbers of false positives and false negatives in current approaches. Computational methods to reduce false positives are to look for over-representation of transcription factor binding sites in a set of similarly regulated promoters or to look for conservation in orthologous promoter alignments.</p> <p>Results</p> <p>We have developed a novel tool, "CORE_TF" (Conserved and Over-REpresented Transcription Factor binding sites) that identifies common transcription factor binding sites in promoters of co-regulated genes. To improve upon existing binding site predictions, the tool searches for position weight matrices from the TRANSFAC^{<it>R </it>}database that are over-represented in an experimental set compared to a random set of promoters and identifies cross-species conservation of the predicted transcription factor binding sites. The algorithm has been evaluated with expression and chromatin-immunoprecipitation on microarray data. We also implement and demonstrate the importance of matching the random set of promoters to the experimental promoters by GC content, which is a unique feature of our tool.</p> <p>Conclusion</p> <p>The program CORE_TF is accessible in a user friendly web interface at <url>http://www.LGTC.nl/CORE_TF</url>. It provides a table of over-represented transcription factor binding sites in the users input genes' promoters and a graphical view of evolutionary conserved transcription factor binding sites. In our test data sets it successfully predicts target transcription factors and their binding sites.</p