Kinetic model of II-VI(001) semiconductor surfaces: Growth rates in atomic layer epitaxy

We present a zinc-blende lattice gas model of II-VI(001) surfaces, which is investigated by means of Kinetic Monte Carlo (KMC) simulations. Anisotropic effective interactions between surface metal atoms allow for the description of, e.g., the sublimation of CdTe(001), including the reconstruction of Cd-terminated surfaces and its dependence on the substrate temperature T. Our model also includes Te-dimerization and the potential presence of excess Te in a reservoir of weakly bound atoms at the surface. We study the self-regulation of atomic layer epitaxy (ALE) and demonstrate how the interplay of the reservoir occupation with the surface kinetics results in two different regimes: at high T the growth rate is limited to 0.5 layers per ALE cycle, whereas at low enough T each cycle adds a complete layer of CdTe. The transition between the two regimes occurs at a characteristic temperature and its dependence on external parameters is studied. Comparing the temperature dependence of the ALE growth rate in our model with experimental results for CdTe we find qualitative agreement.Comment: 9 pages (REVTeX), 8 figures (EPS). Content revised, references added, typos correcte

Synthetic Aperture Radar (SAR) data processing

The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed

Phase transitions in soft-committee machines

Equilibrium statistical physics is applied to layered neural networks with differentiable activation functions. A first analysis of off-line learning in soft-committee machines with a finite number (K) of hidden units learning a perfectly matching rule is performed. Our results are exact in the limit of high training temperatures. For K=2 we find a second order phase transition from unspecialized to specialized student configurations at a critical size P of the training set, whereas for K > 2 the transition is first order. Monte Carlo simulations indicate that our results are also valid for moderately low temperatures qualitatively. The limit K to infinity can be performed analytically, the transition occurs after presenting on the order of N K examples. However, an unspecialized metastable state persists up to P= O (N K^2).Comment: 8 pages, 4 figure

A lattice gas model of II-VI(001) semiconductor surfaces

We introduce an anisotropic two-dimensional lattice gas model of metal terminated II-IV(001) seminconductor surfaces. Important properties of this class of materials are represented by effective NN and NNN interactions, which result in the competition of two vacancy structures on the surface. We demonstrate that the experimentally observed c(2x2)-(2x1) transition of the CdTe(001) surface can be understood as a phase transition in thermal equilbrium. The model is studied by means of transfer matrix and Monte Carlo techniques. The analysis shows that the small energy difference of the competing reconstructions determines to a large extent the nature of the different phases. Possible implications for further experimental research are discussed.Comment: 7 pages, 2 figure

Inhibition of Dipeptidyl Peptidase-4 by Vildagliptin During Glucagon-Like Peptide 1 Infusion Increases Liver Glucose Uptake in the Conscious Dog

OBJECTIVE—This study investigated the acute effects of treatment with vildagliptin on dipeptidyl peptidase-4 (DPP-4) activity, glucagon-like peptide 1 (GLP-1) concentration, pancreatic hormone levels, and glucose metabolism. The primary aims were to determine the effects of DPP-4 inhibition on GLP-1 clearance and on hepatic glucose uptake

Computational capabilities of multilayer committee machines

We obtained an analytical expression for the computational complexity of many layered committee machines with a finite number of hidden layers (L < 8) using the generalization complexity measure introduced by Franco et al (2006) IEEE Trans. Neural Netw. 17 578. Although our result is valid in the large-size limit and for an overlap synaptic matrix that is ultrametric, it provides a useful tool for inferring the appropriate architecture a network must have to reproduce an arbitrary realizable Boolean function

T-cell metagene predicts a favorable prognosis in estrogen receptor-negative and HER2-positive breast cancers

Introduction: Lymphocyte infiltration (LI) is often seen in breast cancer but its importance remains controversial. A positive correlation of human epidermal growth factor receptor 2 (HER2) amplification and LI has been described, which was associated with a more favorable outcome. However, specific lymphocytes might also promote tumor progression by shifting the cytokine milieu in the tumor. Methods: Affymetrix HG-U133A microarray data of 1,781 primary breast cancer samples from 12 datasets were included. The correlation of immune system-related metagenes with different immune cells, clinical parameters, and survival was analyzed. Results: A large cluster of nearly 600 genes with functions in immune cells was consistently obtained in all datasets. Seven robust metagenes from this cluster can act as surrogate markers for the amount of different immune cell types in the breast cancer sample. An IgG metagene as a marker for B cells had no significant prognostic value. In contrast, a strong positive prognostic value for the T-cell surrogate marker (lymphocyte-specific kinase (LCK) metagene) was observed among all estrogen receptor (ER)-negative tumors and those ER-positive tumors with a HER2 overexpression. Moreover ER-negative tumors with high expression of both IgG and LCK metagenes seem to respond better to neoadjuvant chemotherapy. Conclusions: Precise definitions of the specific subtypes of immune cells in the tumor can be accomplished from microarray data. These surrogate markers define subgroups of tumors with different prognosis. Importantly, all known prognostic gene signatures uniformly assign poor prognosis to all ER-negative tumors. In contrast, the LCK metagene actually separates the ER-negative group into better or worse prognosis

Plx1 is required for chromosomal DNA replication under stressful conditions

Polo-like kinase (Plk)1 is required for mitosis progression. However, although Plk1 is expressed throughout the cell cycle, its function during S-phase is unknown. Using Xenopus laevis egg extracts, we demonstrate that Plx1, the Xenopus orthologue of Plk1, is required for DNA replication in the presence of stalled replication forks induced by aphidicolin, etoposide or reduced levels of DNA-bound Mcm complexes. Plx1 binds to chromatin and suppresses the ATM/ATR-dependent intra-S-phase checkpoint that inhibits origin firing. This allows Cdc45 loading and derepression of DNA replication initiation. Checkpoint activation increases Plx1 binding to the Mcm complex through its Polo box domain. Plx1 recruitment to chromatin is independent of checkpoint mediators Tipin and Claspin. Instead, ATR-dependent phosphorylation of serine 92 of Mcm2 is required for the recruitment of Plx1 to chromatin and for the recovery of DNA replication under stress. Depletion of Plx1 leads to accumulation of chromosomal breakage that is prevented by the addition of recombinant Plx1. These data suggest that Plx1 promotes genome stability by regulating DNA replication under stressful conditions