Probing charge fluctuator correlations using quantum dot pairs

We study a pair of quantum dot exciton qubits interacting with a number of fluctuating charges that can induce a Stark shift of both exciton transition energies. We do this by solving the optical master equation using a numerical transfer matrix method. We find that the collective influence of the charge environment on the dots can be detected by measuring the correlation between the photons emitted when each dot is driven independently. Qubits in a common charge environment display photon bunching, if both dots are driven on resonance or if the driving laser detunings have the same sense for both qubits, and antibunching if the laser detunings have in opposite signs. We also show that it is possible to detect several charges fluctuating at different rates using this technique. Our findings expand the possibility of measuring qubit dynamics in order to investigate the fundamental physics of the environmental noise that causes decoherence.Comment: 9 pages, 13 figure

Self-organizing maps: a tool to ascertain taxonomic relatedness based on features derived from 16S rDNA sequence

Exploitation of microbial wealth, of which almost 95% or more is still unexplored, is a growing need. The taxonomic placements of a new isolate based on phenotypic characteristics are now being supported by information preserved in the 16S rRNA gene. However, the analysis of 16S rDNA sequences retrieved from metagenome, by the available bioinformatics tools, is subject to limitations. In this study, the occurrences of nucleotide features in 16S rDNA sequences have been used to ascertain the taxonomic placement of organisms. The tetra- and penta-nucleotide features were extracted from the training data set of the 16S rDNA sequence, and was subjected to an artificial neural network (ANN) based tool known as self-organizing map (SOM), which helped in visualization of unsupervised classification. For selection of significant features, principal component analysis (PCA) or curvilinear component analysis (CCA) was applied. The SOM along with these techniques could discriminate the sample sequences with more than 90% accuracy, highlighting the relevance of features. To ascertain the confidence level in the developed classification approach, the test data set was specifically evaluated for Thiobacillus, with Acidiphilium, Paracocus and Starkeya, which are taxonomically reassigned. The evaluation proved the excellent generalization capability of the developed tool. The topology of genera in SOM supported the conventional chemo-biochemical classification reported in the Bergey manual

Characterizing cognitive deficits and dementia in an aging urban population in India.

Rapid rise in the population of older adults in India will lead to the need for increased health care services related to diagnosis, management, and long-term care for those with dementia and cognitive impairment. A direct approach for service provision through memory clinics can be an effective, successful, and sustaining means of delivering specialized health care services. We have established a memory clinic in Mumbai, India by employing the diverse clinical skills available in Indian academic institutions, diagnostic and research expertise of clinicians and psychologists, and the support of the U.S. National Institutes of Health. Our project involved recruitment of patients, clinical and neuropsychological assessment, and standardized diagnostic procedures, demonstrating the feasibility of using research methods to develop a memory clinic. In this paper, we describe the development of a community-based memory clinic in urban India, including linguistic and cultural factors and present detailed results, including diagnostic characterization, on 194 subjects with various stages of cognitive deficits. Our findings support the feasibility of developing a memory clinic in a public hospital and successful use of research diagnostic criteria to categorize cognitive deficits observed in this population, which may be used to inform the development of other such clinics

Renaissance of the ~1 TeV Fixed-Target Program

This document describes the physics potential of a new fixed-target program based on a ~1 TeV proton source. Two proton sources are potentially available in the future: the existing Tevatron at Fermilab, which can provide 800 GeV protons for fixed-target physics, and a possible upgrade to the SPS at CERN, called SPS+, which would produce 1 TeV protons on target. In this paper we use an example Tevatron fixed-target program to illustrate the high discovery potential possible in the charm and neutrino sectors. We highlight examples which are either unique to the program or difficult to accomplish at other venues.Comment: 31 pages, 11 figure

The Case for a Muon Collider Higgs Factory

We propose the construction of a compact Muon Collider Higgs Factory. Such a machine can produce up to \sim 14,000 at 8\times 10^{31} cm^-2 sec^-1 clean Higgs events per year, enabling the most precise possible measurement of the mass, width and Higgs-Yukawa coupling constants.Comment: Supporting letter for the document: "Muon Collider Higgs Factory for Smowmass 2013", A White Paper submitted to the 2013 U.S. Community Summer Study of the Division of Particles and Fields of the American Physical Society, Y. Alexahin, et. al, FERMILAB-CONF-13-245-T (July, 2013

MUC1 mucin stabilizes and activates hypoxia-inducible factor 1 alpha to regulate metabolism in pancreatic cancer

Aberrant glucose metabolism is one of the hallmarks of cancer that facilitates cancer cell survival and proliferation. Here, we demonstrate that MUC1, a large, type I transmembrane protein that is overexpressed in several carcinomas including pancreatic adenocarcinoma, modulates cancer cell metabolism to facilitate growth properties of cancer cells. MUC1 occupies the promoter elements of multiple genes directly involved in glucose metabolism and regulates their expression. Furthermore, MUC1 expression enhances glycolytic activity in pancreatic cancer cells. We also demonstrate that MUC1 expression enhances in vivo glucose uptake and expression of genes involved in glucose uptake and metabolism in orthotopic implantation models of pancreatic cancer. The MUC1 cytoplasmic tail is known to activate multiple signaling pathways through its interactions with several transcription factors/coregulators at the promoter elements of various genes. Our results indicate that MUC1 acts as a modulator of the hypoxic response in pancreatic cancer cells by regulating the expression/stability and activity of hypoxia-inducible factor-1α (HIF-1α). MUC1 physically interacts with HIF-1α and p300 and stabilizes the former at the protein level. By using a ChIP assay, we demonstrate that MUC1 facilitates recruitment of HIF-1α and p300 on glycolytic gene promoters in a hypoxia-dependent manner. Also, by metabolomic studies, we demonstrate that MUC1 regulates multiple metabolite intermediates in the glucose and amino acid metabolic pathways. Thus, our studies indicate that MUC1 acts as a master regulator of the metabolic program and facilitates metabolic alterations in the hypoxic environments that help tumor cells survive and proliferate under such conditions