The Clustering of K\sim 20 Galaxies on 17 Radio Galaxy Fields

We investigate the angular correlation function, $\omega(\theta)$, of the galaxi es detected in the K-band on 17 fields (101.5 square arcmin in total), each containing a $z\sim 1.1$ radio galaxy. There is a significant detection of galaxy clustering at $K\sim 20$ limits, with an amplitude higher than expected from simple models which fit the faint galaxy clustering in the blue and red passbands, but consistent with a pure luminosity evolution model i f clustering is stable and early-type galaxies have a steeper correlation function than spirals. We do not detect a significant cross-correlation between the radio galaxies and the other galaxies on these fields, obtaining upper limits consistent with a mean clustering environment of Abell class 0 for $z\sim 1.1$ radio galaxies, similar to that observed for radio galaxies at $z\sim 0.5$. At $K\leq 20$, the number of galaxy-galaxy pairs of 2--3 arcsec separations exceeds the random expectation by a factor of $2.15\pm 0.26$. This excess suggests at least a tripling of the local merger rate at $z\sim 1$.Comment: 13 pages, 3 tables, 7 postscript figures, TEX, submitted to MNRA

Spectral tuning of plasmon-enhanced silicon quantum dot luminescence

In the presence of nanoscale silver island arrays, silicon quantum dots exhibit up to sevenfold luminescence enhancements at emission frequencies that correspond to the collective dipole plasmon resonance frequency of the Ag island array. Using electron-beam lithography to alter the pitch and particle diameter, this wavelength-selective enhancement can be varied as the metal array resonance wavelength is tuned from 600 to 900 nm. The luminescence intensity enhancement upon coupling is attributed to an increase in the radiative decay rate of the silicon quantum dots

Genesis and Propagation of Fractal Structures During Photoelectrochemical Etching of n-Silicon

The genesis, propagation, and dimensions of fractal-etch patterns that form anodically on front- or back-illuminated n-Si(100) photoelectrodes in contact with 11.9 M NH₄F(aq) has been investigated during either linear-sweep voltammetry or when the electrode was held at a constant potential (E = +6.0 V versus Ag/AgCl). Optical images collected in situ during electrochemical experiments revealed the location and underlying mechanism of initiation and propagation of the structures on the surface. X-ray photoelectron spectroscopic (XPS) data collected for samples emersed from the electrolyte at varied times provided detailed information about the chemistry of the surface during fractal etching. The fractal structure was strongly influenced by the orientation of the crystalline Si sample. The etch patterns were initially generated at points along the circumference of bubbles that formed upon immersion of n-Si(100) samples in the electrolyte, most likely due to the electrochemical and electronic isolation of areas beneath bubbles. XPS data showed the presence of a tensile-stressed silicon surface throughout the etching process as well as the presence of SiO_xF_y on the surface. The two-dimensional fractal dimension D_(f,2D) of the patterns increased with etching time to a maximum observed value of D_(f,2D)=1.82. Promotion of fractal etching near etch masks that electrochemically and electronically isolated areas of the photoelectrode surface enabled the selective placement of highly branched structures at desired locations on an electrode surface

Intensity-Resolved Above Threshold Ionization of Xenon with Short Laser Pulses

We present intensity-resolved above threshold ionization (ATI) spectra of xenon using an intensity scanning and deconvolution technique. Experimental data were obtained with laser pulses of 58 fs and central wavelength of 800 nm from a chirped-pulse amplifier. Applying a deconvolution algorithm, we obtained spectra that have higher contrast and are in excellent agreement with characteristic 2 $U_p$ and 10 $U_p$ cutoff energies contrary to that found for raw data. The retrieved electron ionization probability is consistent with the presence of a second electron from double ionization. This recovered ionization probability is confirmed with a calculation based on the PPT tunneling ionization model [Perelomov, Popov, and Terent'ev, Sov. Phys. JETP 23, 924 (1966)]. Thus, the measurements of photoelectron yields and the proposed deconvolution technique allowed retrieval of more accurate spectroscopic information from the ATI spectra and ionization probability features that are usually concealed by volume averaging.Comment: 21 pages, 7 figure

Luminescence Properties of Sm2+-Activated Barium Chloroborates

The luminescence properties of Sm2+-activated stoichiometric and non-stoichiometric Ba2B5O9Cl were investigated from 16 to 450 K. In stoichiometric Ba2B5O9Cl, the emission spectra of Sm2+ are composed of 4f6-4f6 transitions over the 16-450K temperature range studied. Luminescence was observed from Sm2+ in four inequivalent cationic sites at 16K andtwo inequivalent sites at room temperature. In the non-stoichiometric compound, the emission is characterized by 4f6-4f6 transitions at low temperature and 4f->5d1-4f6 transitions at high temperature. The Sm2+ doped into the Ca2+ and Sr 2+ analogues in the M2B5O9Cl series shows the broadband 4f->5d1-4f6 luminescence in both the stoichiometric and non-stoichiometric compounds due to the increased ligand field caused by the smaller ionic radii of the metal ions

Chinese Insolvency Law Lacks Teeth

The speed by which China has moved towards a market economy has not been accompanied by a similar development of its judiciary system. Since the early 1990s, foundational national legislation with a direct effect on firms, such as laws dealing with contract, investment, liability and insolvency have b

Simulating non-unitary dynamics using quantum signal processing with unitary block encoding

We adapt a recent advance in resource-frugal quantum signal processing - the Quantum Eigenvalue Transform with Unitary matrices (QET-U) - to explore non-unitary imaginary time evolution on early fault-tolerant quantum computers using exactly emulated quantum circuits. We test strategies for optimising the circuit depth and the probability of successfully preparing the desired imaginary-time evolved states. For the task of ground state preparation, we confirm that the probability of successful post-selection is quadratic in the initial reference state overlap $\gamma$ as $O(\gamma^2)$. When applied instead to thermal state preparation, we show QET-U can directly estimate partition functions at exponential cost. Finally, we combine QET-U with Trotter product formula to perform non-normal Hamiltonian simulation in the propagation of Lindbladian open quantum system dynamics. We find that QET-U for non-unitary dynamics is flexible, intuitive and straightforward to use, and suggest ways for delivering quantum advantage in simulation tasks.Comment: 14 pages, 10 figures, minor corrections and updated citation

Prognostic models for mesothelioma : variable selection and machine learning

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (leaves 103-107).Malignant pleural mesothelioma is a rare and lethal form of cancer affecting the external lining of the lungs. Extrapleural pneumonectomy (EPP), which involves the removal of the affected lung, is one of the few treatments that has been shown to have some effectiveness in treatment of the disease [39], but this procedure carries with it a high risk of mortality and morbidity [8]. This paper is concerned with building models using gene expression levels to predict patient survival following EPP; these models could potentially be used to guide patient treatment. A study by Gordon et al built a predictor based on ratios of gene expression levels that was 88% accurate on the set of 29 independent test samples, in terms of classifying whether or not the patients survived shorter or longer than the median survival [15]. These results were recreated both on the original data set used by Gordon et al and on a newer data set which contained the same samples but was generated using newer software. The predictors were evaluated using N-fold cross validation. In addition, other methods of variable selection and machine learning were investigated to build different types of predictive models. These analyses used a random training set from the newer data set. These models were evaluated using N-fold cross validation and the best of each of the four main types of models -(cont.) decision trees, logistic regression, artificial neural networks, and support vector machines - were tested using a small set of samples excluded from the training set. Of these four models, the neural network with eight hidden neurons and weight decay regularization performed the best, achieving a zero cross validation error rate and, on the test set, 71% accuracy, an ROC area of .67 and a logrank p value of .219. The support vector machine model with linear kernel also had zero cross validation error and, on the test set, a 71% accuracy and an ROC area of .67 but had a higher logrank p value of .515. These both had a lower cross validation error than the ratio-based predictors of Gordon et al, which had an N-fold cross validation error rate of 35%; however, these results may not be comparable because the neural network and support vector machine used a different training set than the Gordon et al study. Regression analysis was also performed; the best neural network model was incorrect by an average of 4.6 months in the six test samples. The method of variable selection based on the signal-to-noise ratio of genes originally used by Golub et al proved more effective when used on the randomly generated training set than the method involving Student's t tests and fold change used by Gordon et al. Ultimately, however, these models will need to be evaluated using a large independent test.by Nathan Hans Vantzelfde.M.Eng

Identification of the Mechanisms of mRNA Regulation by PUF Proteins.

PUF proteins are conserved RNA-binding proteins that regulate mRNAs through sequence-specific binding. PUFs play integral roles in important biological processes including: development, fertility, and synaptic plasticity. Several mechanisms have been proposed for repression by PUF proteins, including: inhibition of translation initiation, elongation, and activation of deadenylation and mRNA decay. The contribution of these mechanisms was tested in S. cerevisiae, and D. melanogaster models. In yeast, Puf4p and Puf5p negatively regulate the HO mRNA, and both accelerate deadenylation through recruitment of the Pop2-Ccr4 deadenylase machinery. Surprisingly, repression by Puf4p requires deadenylation, whereas Pufp5p does not. We identified the eIF-4E binding protein, (4EBP) Eap1p, to be necessary for repression by Puf5p. Collectively, my findings show that Puf5p activates mRNA decapping, and subsequent 5′-3′ mRNA decay through association with Eap1p, and the activator of decapping, Dhh1p. I have demonstrated that Puf5p recruits Eap1p to HO mRNA to activate mRNA decapping, and this data suggests a model where Puf5p recruits Eap1p, Dhh1p, as well as the decapping and deadenylation machinery to HO mRNA. Eap1p and Dhh1p may collaborate to evict the translational machinery, including eIF-4E and eIF-4G, from a targeted mRNA; this allows the decapping enzyme to access the 5′ cap. I have identified a novel mechanism of repression via a 4EBP in the activation of mRNA decapping. The Drosophila PUF protein, Pumilio, has multiple repression domains including the conserved RNA-Binding Domain RBD. We sought to define the mechanisms of repression exerted by the RBD, and found that, like yeast Puf5p, the RBD accelerates deadenylation and degradation of target mRNAs. Acceleration of deadenylation by the RBD is catalyzed by Ccr4 and Pop2, and requires the Poly(A) Binding Protein, Pabp. Interestingly, Pabp contributes strongly to overall PUM repression, whereas deadenylation is not required for repression. We propose that the PUM RBD targets Pabp to translationally repress an mRNA, and this exposes the poly(A) tail to deadenylases recruited by PUM. Subsequently PUM elicits degradation of the target mRNA through activation of mRNA decapping. Together, this work defines the evolutionarily conserved repression mechanism of PUF proteins via deadenylation, decay and translational repression via Pabp.PHDCellular & Molecular BiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/98060/1/blewett_1.pd