Optical and Thermal Properties of Nanoporous Material and Devices

In this thesis, we investigate the optical and thermal properties of porous silicon and its applications. In first part, porous silicon's optical properties and application as a highly sensitive refractive index sensor is studied. An integrated Mach-Zehnder interferometer waveguide fabricated from nanoporous silicon is shown to exhibit high sensitivity and measurement stability that exceeds previously demonstrated porous sensors. In second part, we discuss experimental methods to characterize the thermal conductivity of nanoporous silicon films. We use the 3-ω method to characterize the exceptionally low thermal conductivity of porous silicon. Finally, we employ an improved heat conduction analysis method for the 3-ω method to measure the anisotropy in thermal conductivity. Our measurement show that porous silicon has very low in-plane thermal conductivity compared to cross-plane conductivity. We confirmed this anisotropy using direct numerical simulation of the anisotropic heat equation

Fabrication and Sub-Assembly of Electrostatically Actuated Silicon Nitride Microshutter Arrays

We have developed a new microshutter array (MSA) subassembly. The MSA and a silicon substrate are flip-bonded together. The MSA has a new back side fabrication process to actuate the microshutters electrostatically, and the new silicon substrate has light shields. The microshutters with a pixel size of 100 x 200 sq micrometers are fabricated on silicon with thin silicon nitride membranes. The microshutters rotate 90 deg on torsion bars. The selected microshutters are actuated, held, and addressed electrostatically by applying voltages on the electrodes the front and back sides of the microshutters. The substrate has the light shield to block lights around the microshutters. Also, electrical connections are made from the MSA to a controller board via the substrate

Virmid: accurate detection of somatic mutations with sample impurity inference

Detection of somatic variation using sequence from disease-control matched data sets is a critical first step. In many cases including cancer, however, it is hard to isolate pure disease tissue, and the impurity hinders accurate mutation analysis by disrupting overall allele frequencies. Here, we propose a new method, Virmid, that explicitly determines the level of impurity in the sample, and uses it for improved detection of somatic variation. Extensive tests on simulated and real sequencing data from breast cancer and hemimegalencephaly demonstrate the power of our model. A software implementation of our method is available at http://sourceforge.net/projects/virmid/

Reconstructing charge-carrier dynamics in porous silicon membranes from time-resolved interferometric measurements

We performed interferometric time-resolved simultaneous reflectance and transmittance measurements to investigate the carrier dynamics in pump-probe experiments on thin porous silicon membranes. The experimental data was analysed by using a method built on the Wentzel-Kramers-Brillouin approximation and the Drude model, allowing us to reconstruct the excited carriers’ non-uniform distribution in space and its evolution in time. The analysis revealed that the carrier dynamics in porous silicon, with ~50% porosity and native oxide chemistry, is governed by the Shockley-Read-Hall recombination process with a characteristic time constant of 375 picoseconds, whereas diffusion makes an insignificant contribution as it is suppressed by the high rate of scattering

Genome-wide Mapping of DROSHA Cleavage Sites on Primary MicroRNAs and Noncanonical Substrates

MicroRNA (miRNA) maturation is initiated by DROSHA, a double-stranded RNA (dsRNA)-specific RNase III enzyme. By cleaving primary miRNAs (pri-miRNAs) at specific positions, DROSHA serves as a main determinant of miRNA sequences and a highly selective gatekeeper for the canonical miRNA pathway. However, the sites of DROSHA-mediated processing have not been annotated, and it remains unclear to what extent DROSHA functions outside the miRNA pathway. Here, we establish a protocol termed “formaldehyde crosslinking, immunoprecipitation, and sequencing (fCLIP-seq),” which allows identification of DROSHA cleavage sites at single-nucleotide resolution. fCLIP identifies numerous processing sites, suggesting widespread end modifications during miRNA maturation. fCLIP also finds many pri-miRNAs that undergo alternative processing, yielding multiple miRNA isoforms. Moreover, we discovered dozens of DROSHA substrates on non-miRNA loci, which may serve as cis-elements for DROSHA-mediated gene regulation. We anticipate that fCLIP-seq could be a general tool for investigating interactions between dsRNA-binding proteins and structured RNAs. © 2017 Elsevier Inc1991sciescopu

False discovery rates in spectral identification

Abstract Automated database search engines are one of the fundamental engines of high-throughput proteomics enabling daily identifications of hundreds of thousands of peptides and proteins from tandem mass (MS/MS) spectrometry data. Nevertheless, this automation also makes it humanly impossible to manually validate the vast lists of resulting identifications from such high-throughput searches. This challenge is usually addressed by using a Target-Decoy Approach (TDA) to impose an empirical False Discovery Rate (FDR) at a pre-determined threshold x% with the expectation that at most x% of the returned identifications would be false positives. But despite the fundamental importance of FDR estimates in ensuring the utility of large lists of identifications, there is surprisingly little consensus on exactly how TDA should be applied to minimize the chances of biased FDR estimates. In fact, since less rigorous TDA/FDR estimates tend to result in more identifications (at higher 'true' FDR), there is often little incentive to enforce strict TDA/FDR procedures in studies where the major metric of success is the size of the list of identifications and there are no follow up studies imposing hard cost constraints on the number of reported false positives. Here we address the problem of the accuracy of TDA estimates of empirical FDR. Using MS/MS spectra from samples where we were able to define a factual FDR estimator of 'true' FDR we evaluate several popular variants of the TDA procedure in a variety of database search contexts. We show that the fraction of false identifications can sometimes be over 10× higher than reported and may be unavoidably high for certain types of searches. In addition, we further report that the two-pass search strategy seems the most promising database search strategy. While unavoidably constrained by the particulars of any specific evaluation dataset, our observations support a series of recommendations towards maximizing the number of resulting identifications while controlling database searches with robust and reproducible TDA estimation of empirical FDR

False discovery rates in spectral identification

Automated database search engines are one of the fundamental engines of high-throughput proteomics enabling daily identifications of hundreds of thousands of peptides and proteins from tandem mass (MS/MS) spectrometry data. Nevertheless, this automation also makes it humanly impossible to manually validate the vast lists of resulting identifications from such high-throughput searches. This challenge is usually addressed by using a Target-Decoy Approach (TDA) to impose an empirical False Discovery Rate (FDR) at a pre-determined threshold x% with the expectation that at most x% of the returned identifications would be false positives. But despite the fundamental importance of FDR estimates in ensuring the utility of large lists of identifications, there is surprisingly little consensus on exactly how TDA should be applied to minimize the chances of biased FDR estimates. In fact, since less rigorous TDA/FDR estimates tend to result in more identifications (at higher 'true' FDR), there is often little incentive to enforce strict TDA/FDR procedures in studies where the major metric of success is the size of the list of identifications and there are no follow up studies imposing hard cost constraints on the number of reported false positives. Here we address the problem of the accuracy of TDA estimates of empirical FDR. Using MS/MS spectra from samples where we were able to define a factual FDR estimator of 'true' FDR we evaluate several popular variants of the TDA procedure in a variety of database search contexts. We show that the fraction of false identifications can sometimes be over 10× higher than reported and may be unavoidably high for certain types of searches. In addition, we further report that the two-pass search strategy seems the most promising database search strategy. While unavoidably constrained by the particulars of any specific evaluation dataset, our observations support a series of recommendations towards maximizing the number of resulting identifications while controlling database searches with robust and reproducible TDA estimation of empirical FDR

Hur lär barn om väder?

Jag har velat ta reda på hur det är att arbeta med det naturvetenskapliga ämnet väder med åttaåringar. Mina utgångspunkter har varit teorier om lärande, experimentets roll för lärande och lärarens roll för lärandet. Den tematiska arbetsformen har bildat ramen för undersökning om hur barn lär om väder. Jag har intervjuat eleverna i smågrupper och det har kommit fram intressanta reflektioner från eleverna. Eleverna har uttryckt att de har lärt sig nya saker om väder. De har också uttryckt att gamla föreställningar har förändrats. Det finns en utbredd rädsla och forskningen är eftersatt kring barns lärande om naturvetenskap. Jag har i min undersökning upplevt att åttaåringar kan förstå komplexa väderfenomen, med hjälp av olika pedagogiska inlärningsstilar