Applications of active microwave imagery

The following topics were discussed in reference to active microwave applications: (1) Use of imaging radar to improve the data collection/analysis process; (2) Data collection tasks for radar that other systems will not perform; (3) Data reduction concepts; and (4) System and vehicle parameters: aircraft and spacecraft

Analysis of Integrating Sphere Performance for IR Enhanced DT Layering

Absorbed IR energy can supplement the beta decay energy from DT ice to improve the driving force toward uniform layers. A significant problem with this approach has been to deliver the added IR energy with sufficient uniformity to enhance rather than destroy the uniformity of the ice layers. Computer modeling has indicated that one can achieve {approximately}1% uniformity in the angular variation of the absorbed power using an integrating sphere containing holes large enough to allow external inspection of the ice layer uniformity. The power required depends on the integrating sphere size, a 25 mm diameter sphere requires {approximately}35 mW of IR to deposit as much energy in the ice as the 50 mW/cm{sup 3}(35 pW total) received from tritium decay in DT. Power absorbed in the plastic can cause unacceptable ice-layer non-uniformities for the integrating sphere design considered here

Femtosecond Laser-Produced Plasma X-Rays from Periodically Modulated Surface Targets

We have studied theoretically and experimentally the x-ray production above 1 keV from femtosecond laser plasmas generated on periodically modulated surface targets. Laser energy coupling to plasma surface waves has been modeled using a numerical differential method. Almost total absorption of incident laser radiation is predicted for optimized interaction conditions. Silicon gratings have been irradiated by a 120fs Ti:sapphire laser at irradiances in excess of 1016 W/cm2. X-ray intensities above 1.5 keV (K-shell lines) have been measured as a function of the incidence angle. Results show a distinct x-ray emission maximum for the first order diffraction angle and are in good qualitative agreement with our theoretical predictions

Reliability of Bioelectrical Impedance Analysis for Estimating Whole‐Fish Energy Density and Percent Lipids

We evaluated bioelectrical impedance analysis (BIA) as a nonlethal means of predicting energy density and percent lipids for three fish species: Yellow perch Perca flavescens, walleye Sander vitreus, and lake whitefish Coregonus clupeaformis. Although models that combined BIA measures with fish wet mass provided strong predictions of total energy, total lipids, and total dry mass for whole fish, including BIA provided only slightly better predictions than using fish mass alone. Regression models that used BIA measures to directly predict the energy density or percent lipids of whole fish were generally better than those using body mass alone (based on Akaike’s information criterion). However, the goodness of fit of models that used BIA measures varied widely across species and at best explained only slightly more than one‐half the variation observed in fish energy density or percent lipids. Models that combined BIA measures with body mass for prediction had the strongest correlations between predicted and observed energy density or percent lipids for a validation group of fish, but there were significant biases in these predictions. For example, the models underestimated energy density and percent lipids for lipid‐rich fish and overestimated energy density and percent lipids for lipid‐poor fish. A comparison of observed versus predicted whole‐fish energy densities and percent lipids demonstrated that models that incorporated BIA measures had lower maximum percent error than models without BIA measures in them, although the errors for the BIA models were still generally high (energy density: 15‐18%; percent lipids: 82‐89%). Considerable work is still required before BIA can provide reliable predictions of whole‐fish energy density and percent lipids, including understanding how temperature, electrode placement, and the variation in lipid distribution within a fish affect BIA measures.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141722/1/tafs1519.pd

Involvement of RDR6 in short-range intercellular RNA silencing in Nicotiana benthamiana

In plants, non-cell autonomous RNA silencing spreads between cells and over long distances. Recent work has revealed insight on the genetic and molecular components essential for cell-to-cell movement of RNA silencing in Arabidopsis. Using a local RNA silencing assay, we report on a distinct mechanism that may govern the short-range (6–10 cell) trafficking of virus-induced RNA silencing from epidermal to neighbouring palisade and spongy parenchyma cells in Nicotiana benthamiana. This process involves a previously unrecognised function of the RNA-dependent RNA polymerase 6 (RDR6) gene. Our data suggest that plants may have evolved distinct genetic controls in intercellular RNA silencing among different types of cells

Deep Neural Network Discrimination of Multiplexed Superconducting Qubit States

Demonstrating a quantum computational advantage will require high-fidelity control and readout of multi-qubit systems. As system size increases, multiplexed qubit readout becomes a practical necessity to limit the growth of resource overhead. Many contemporary qubit-state discriminators presume single-qubit operating conditions or require considerable computational effort, limiting their potential extensibility. Here, we present multi-qubit readout using neural networks as state discriminators. We compare our approach to contemporary methods employed on a quantum device with five superconducting qubits and frequency-multiplexed readout. We find that fully-connected feedforward neural networks increase the qubit-state-assignment fidelity for our system. Relative to contemporary discriminators, the assignment error rate is reduced by up to 25% due to the compensation of system-dependent nonidealities such as readout crosstalk which is reduced by up to one order of magnitude. Our work demonstrates a potentially extensible building block for high-fidelity readout relevant to both near-term devices and future fault-tolerant systems.Comment: 18 Pages, 9 figure

Relational Contracts and Organizational Capabilities

A large literature identifies unique organizational capabilities as a potent source of competitive advantage, yet our knowledge of why capabilities fail to diffuse more rapidly—particularly in situations in which competitors apparently have strong incentives to adopt them and a well-developed understanding of how they work—remains incomplete. In this paper we suggest that competitively significant capabilities often rest on managerial practices that in turn rely on relational contracts (i.e., informal agreements sustained by the shadow of the future). We argue that one of the reasons these practices may be difficult to copy is that effective relational contracts must solve the twin problems of credibility and clarity and that although credibility might, in principle, be instantly acquired, clarity may take time to develop and may interact with credibility in complex ways so that relational contracts may often be difficult to build