SRC seal testing

Small venthole drilled in semisealed silicon-controlled rectifier (SCR) cavity eliminates entrapped helium. Although these devices show slightly greater leak than those before lead installation, it is now possible to distinguish device with good hermetic seal from defective one

The Plant Growth-Promoting Potential of Root-Associated Bacteria from Plants Growing in Stressed Environments

Several studies have demonstrated the potential of plant growth-promoting bacteria, including their use as inoculants, in the contexts of both agriculture and enhanced phytoremediation. Despite their promise, there is still a need to characterize and identify plant growth-promoting bacteria amidst isolates cultured to date. Therefore the purpose of this study was to i) screen bacterial endophytes isolated from plants growing in both a chronically nutrient-deficient agricultural soil and a hydrocarbon-contaminated soil for plant growth-promoting potential in vitro and ii) assess the plant growth-promoting capabilities of isolates in vivo. Bacterial isolates belonging to genera common to both environments were screened for plant growth-promoting genotypes and phenotypes including ACC deaminase activity (acds), hydrocarbon degradation (alkB and CYP153), alkaline phosphatase activity (phoD), and nitrogen fixation (nifH). After screening, 28 isolates from 16 genera were subjected to further study in vivo. After using seed germination and root elongation screening in wheat (Trictum aestivum) and sweet clover (Melilotus alba), four isolates were selected for further study—A3 (Pseudomonas sp.) and A9 (Delftia sp.) in sweet clover and A12 (Kluyvera sp.) and B34 (Luteimonas sp.) in wheat—as they promoted early plant growth and development. Plant growth-promoting capabilities were then assessed by inoculating wheat and sweet clover seeds and growing plants in a growth chamber for 60 days in either a marginal agricultural soil or the same soil amended with diesel. Isolates A12 (Kluyvera sp.) and B34 (Luteimonas sp.) increased the acquisition of nitrogen (N) and phosphorous (P) by plants when growing in the marginal agricultural soil. However, plant growth-promoting effects were lost when diesel fuel was added. Further, no effect was observed in sweet clover in either soil condition. Initial screening for plant growth-promoting potential highlighted the importance of including functionality screening as the presence or absence of a plant growth-promoting genotype did not always indicate a positive phenotype. Further, this work exemplified the importance of in vivo screening assays to identify potential plant growth-promoting bacteria. Finally, results showed bacteria with plant growth-promotion potential can be isolated from stressed environments and may promote wheat growth in a marginal agricultural soil

Ram Opportunity

RAM Opportunity is a self-sustaining mentoring and experiential learning program designed to serve high school students in the local community through programs led by graduate student mentors. RAM Opportunity operates using a plug-and-play structure that can be implemented in the arts, business, education, humanities, sciences, or any other discipline. Partnerships will be formed with local high schools and their guidance counseling services to develop a pipeline for potential students to participate in the program. The program benefits VCU by enhancing engagement with the local community, generating interest in high school students pursuing post-secondary education at VCU, and developing graduate students by providing professional development funding and real-world teaching and mentoring experience

Federal Life Sciences Funding and University R&D

This paper investigates the impact of federal extramural research funding on total expenditures for life sciences research and development (R&D) at U.S. universities, to determine whether federal R&D funding spurs funding from non-federal (private and state/local government) sources. We use a fixed effects instrumental variable approach to estimate the causal effect of federal funding on non-federal funding. Our results indicate that a dollar increase in federal funding leads to a $0.33 increase in non-federal funding at U.S. universities. Our evidence also suggests that successful applications for federal funding may be interpreted by non-federal funders as a signal of recipient quality: for example, non-PhD-granting universities, lower ranked universities and those that have historically received less funding experience greater increases in non-federal funding per federal dollar received.

Scalable Noise Estimation with Random Unitary Operators

We describe a scalable stochastic method for the experimental measurement of generalized fidelities characterizing the accuracy of the implementation of a coherent quantum transformation. The method is based on the motion reversal of random unitary operators. In the simplest case our method enables direct estimation of the average gate fidelity. The more general fidelities are characterized by a universal exponential rate of fidelity loss. In all cases the measurable fidelity decrease is directly related to the strength of the noise affecting the implementation -- quantified by the trace of the superoperator describing the non--unitary dynamics. While the scalability of our stochastic protocol makes it most relevant in large Hilbert spaces (when quantum process tomography is infeasible), our method should be immediately useful for evaluating the degree of control that is achievable in any prototype quantum processing device. By varying over different experimental arrangements and error-correction strategies additional information about the noise can be determined.Comment: 8 pages; v2: published version (typos corrected; reference added

Minimax mean estimator for the trine

We explore the question of state estimation for a qubit restricted to the $x$-$z$ plane of the Bloch sphere, with the trine measurement. In our earlier work [H. K. Ng and B.-G. Englert, eprint arXiv:1202.5136[quant-ph] (2012)], similarities between quantum tomography and the tomography of a classical die motivated us to apply a simple modification of the classical estimator for use in the quantum problem. This worked very well. In this article, we adapt a different aspect of the classical estimator to the quantum problem. In particular, we investigate the mean estimator, where the mean is taken with a weight function identical to that in the classical estimator but now with quantum constraints imposed. Among such mean estimators, we choose an optimal one with the smallest worst-case error-the minimax mean estimator-and compare its performance with that of other estimators. Despite the natural generalization of the classical approach, this minimax mean estimator does not work as well as one might expect from the analogous performance in the classical problem. While it outperforms the often-used maximum-likelihood estimator in having a smaller worst-case error, the advantage is not significant enough to justify the more complicated procedure required to construct it. The much simpler adapted estimator introduced in our earlier work is still more effective. Our previous work emphasized the similarities between classical and quantum state estimation; in contrast, this paper highlights how intuition gained from classical problems can sometimes fail in the quantum arena.Comment: 18 pages, 3 figure

Information preserving structures: A general framework for quantum zero-error information

Quantum systems carry information. Quantum theory supports at least two distinct kinds of information (classical and quantum), and a variety of different ways to encode and preserve information in physical systems. A system's ability to carry information is constrained and defined by the noise in its dynamics. This paper introduces an operational framework, using information-preserving structures to classify all the kinds of information that can be perfectly (i.e., with zero error) preserved by quantum dynamics. We prove that every perfectly preserved code has the same structure as a matrix algebra, and that preserved information can always be corrected. We also classify distinct operational criteria for preservation (e.g., "noiseless", "unitarily correctible", etc.) and introduce two new and natural criteria for measurement-stabilized and unconditionally preserved codes. Finally, for several of these operational critera, we present efficient (polynomial in the state-space dimension) algorithms to find all of a channel's information-preserving structures.Comment: 29 pages, 19 examples. Contains complete proofs for all the theorems in arXiv:0705.428

Robust Online Hamiltonian Learning

In this work we combine two distinct machine learning methodologies, sequential Monte Carlo and Bayesian experimental design, and apply them to the problem of inferring the dynamical parameters of a quantum system. We design the algorithm with practicality in mind by including parameters that control trade-offs between the requirements on computational and experimental resources. The algorithm can be implemented online (during experimental data collection), avoiding the need for storage and post-processing. Most importantly, our algorithm is capable of learning Hamiltonian parameters even when the parameters change from experiment-to-experiment, and also when additional noise processes are present and unknown. The algorithm also numerically estimates the Cramer-Rao lower bound, certifying its own performance.Comment: 24 pages, 12 figures; to appear in New Journal of Physic

Shock-Wave Experiment with the Chelyabinsk LL5 Meteorite : Experimental Parameters and the Texture of the Shock-Affected Material

A spherical geometry shock experiment with the light-colored lithology material of the Chelyabinsk LL5 ordinary chondrite was carried out. The material was affected by shock and thermal metamorphism whose grade ranged from initial stage S3-4 to complete melting. The temperature and pressure were estimated at >2000 degrees C and >90 GPa. The textural shock effects were studied by optical and electron microscopy. A single experimental impact has produced the whole the range of shock pressures and temperatures and, correspondingly, four zones identified by petrographic analysis: (1) a melt zone, (2) a zone of melting silicates, (3) a black ring zone, and (4) a zone of weakly shocked initial material. The following textural features of the material were identified: displacement of the metal and troilite phases from the central melt zone; the development of a zone of mixed lithology (light-colored fragments in silicate melt); the origin of a dark-colored lithology ring; and the generation of radiating shock veinlets. The experimental sample shows four textural zones that correspond to the different lithology types of the Chelyabinsk LL5 meteorite found in fragments of the meteoritic shower in the collection at the Ural Federal University. Our results prove that shock wave loading experiment can be successfully applied in modeling of space shocks and can be used to experimentally model processes at the small bodies of the solar system.Peer reviewe