P-code enhanced method for processing encrypted GPS signals without knowledge of the encryption code

In the preferred embodiment, an encrypted GPS signal is down-converted from RF to baseband to generate two quadrature components for each RF signal (L1 and L2). Separately and independently for each RF signal and each quadrature component, the four down-converted signals are counter-rotated with a respective model phase, correlated with a respective model P code, and then successively summed and dumped over presum intervals substantially coincident with chips of the respective encryption code. Without knowledge of the encryption-code signs, the effect of encryption-code sign flips is then substantially reduced by selected combinations of the resulting presums between associated quadrature components for each RF signal, separately and independently for the L1 and L2 signals. The resulting combined presums are then summed and dumped over longer intervals and further processed to extract amplitude, phase and delay for each RF signal. Precision of the resulting phase and delay values is approximately four times better than that obtained from straight cross-correlation of L1 and L2. This improved method provides the following options: separate and independent tracking of the L1-Y and L2-Y channels; separate and independent measurement of amplitude, phase and delay L1-Y channel; and removal of the half-cycle ambiguity in L1-Y and L2-Y carrier phase

Kalman Orbit Optimized Loop Tracking

Under certain conditions of low signal power and/or high noise, there is insufficient signal to noise ratio (SNR) to close tracking loops with individual signals on orbiting Global Navigation Satellite System (GNSS) receivers. In addition, the processing power available from flight computers is not great enough to implement a conventional ultra-tight coupling tracking loop. This work provides a method to track GNSS signals at very low SNR without the penalty of requiring very high processor throughput to calculate the loop parameters. The Kalman Orbit-Optimized Loop (KOOL) tracking approach constitutes a filter with a dynamic model and using the aggregate of information from all tracked GNSS signals to close the tracking loop for each signal. For applications where there is not a good dynamic model, such as very low orbits where atmospheric drag models may not be adequate to achieve the required accuracy, aiding from an IMU (inertial measurement unit) or other sensor will be added. The KOOL approach is based on research JPL has done to allow signal recovery from weak and scintillating signals observed during the use of GPS signals for limb sounding of the Earth s atmosphere. That approach uses the onboard PVT (position, velocity, time) solution to generate predictions for the range, range rate, and acceleration of the low-SNR signal. The low- SNR signal data are captured by a directed open loop. KOOL builds on the previous open loop tracking by including feedback and observable generation from the weak-signal channels so that the MSR receiver will continue to track and provide PVT, range, and Doppler data, even when all channels have low SNR

Quantum non-demolition measurements of single donor spins in semiconductors

We propose a technique for measuring the state of a single donor electron spin using a field-effect transistor induced two-dimensional electron gas and electrically detected magnetic resonance techniques. The scheme is facilitated by hyperfine coupling to the donor nucleus. We analyze the potential sensitivity and outline experimental requirements. Our measurement provides a single-shot, projective, and quantum non-demolition measurement of an electron-encoded qubit state.Comment: 8+ pages. 4 figures. Published versio

Translation Regulation of the Glutamyl-prolyl-tRNA Synthetase Gene EPRS through Bypass of Upstream Open Reading Frames with Noncanonical Initiation Codons

In the integrated stress response, phosphorylation of eIF2α (eIF2α-P) reduces protein synthesis while concomitantly promoting preferential translation of specific transcripts associated with stress adaptation. Translation of the glutamyl-prolyl-tRNA synthetase gene EPRS is enhanced in response to eIF2α-P. To identify the underlying mechanism of translation control, we employed biochemical approaches to determine the regulatory features by which upstream ORFs (uORFs) direct downstream translation control and expression of the EPRS coding region. Our findings reveal that translation of two inhibitory uORFs encoded by noncanonical CUG and UUG initiation codons in the EPRS mRNA 5'-leader serve to dampen levels of translation initiation at the EPRS coding region. By a mechanism suggested to involve increased translation initiation stringency during stress-induced eIF2α-P, we observed facilitated ribosome bypass of these uORFs, allowing for increased translation of the EPRS coding region. Importantly, EPRS protein expression is enhanced through this preferential translation mechanism in response to multiple known activators of eIF2α-P and likely serves to facilitate stress adaptation in response to a variety of cellular stresses. The rules presented here for the regulated ribosome bypass of noncanonical initiation codons in the EPRS 5'-leader add complexity into the nature of uORF-mediated translation control mechanisms during eIF2α-P and additionally illustrate the roles that previously unexamined uORFs with noncanonical initiation codons can play in modulating gene expression

Quark-meson coupling model with the cloudy bag

Using the volume coupling version of the cloudy bag model, the quark-meson coupling model is extended to study the role of pion field and the properties of nuclear matter. The extended model includes the effect of gluon exchange as well as the pion-cloud effect, and provides a good description of the nuclear matter properties. The relationship between the extended model and the EFT approach to nuclear matter is also discussed.Comment: 13 pages, 3 figure

Strange quarks and lattice QCD

The last few years have seen a dramatic improvement in our knowledge of the strange form factors of the nucleon. With regard to the vector from factors the level of agreement between theory and experiment gives us considerable confidence in our ability to calculate with non-perturbative QCD. The calculation of the strange scalar form factor has moved significantly in the last two years, with the application of new techniques which yield values considerably smaller than believed for the past 20 years. These new values turn out to have important consequences for the detection of neutralinos, a favourite dark matter candidate. Finally, very recent lattice studies have resurrected interest in the famed H-dibaryon, with modern chiral extrapolation of lattice data suggesting that it may be only slightly unbound. We review some of the major sources of uncertainty in that chiral extrapolation.Comment: Invited talk at the Asia-Pacific few Body Conference, Seoul Kore

A genetic linkage map and comparative mapping of the prairie vole (Microtus ochrogaster) genome

<p>Abstract</p> <p>Background</p> <p>The prairie vole (<it>Microtus ochrogaster</it>) is an emerging rodent model for investigating the genetics, evolution and molecular mechanisms of social behavior. Though a karyotype for the prairie vole has been reported and low-resolution comparative cytogenetic analyses have been done in this species, other basic genetic resources for this species, such as a genetic linkage map, are lacking.</p> <p>Results</p> <p>Here we report the construction of a genome-wide linkage map of the prairie vole. The linkage map consists of 406 markers that are spaced on average every 7 Mb and span an estimated ~90% of the genome. The sex average length of the linkage map is 1707 cM, which, like other Muroid rodent linkage maps, is on the lower end of the length distribution of linkage maps reported to date for placental mammals. Linkage groups were assigned to 19 out of the 26 prairie vole autosomes as well as the X chromosome. Comparative analyses of the prairie vole linkage map based on the location of 387 Type I markers identified 61 large blocks of synteny with the mouse genome. In addition, the results of the comparative analyses revealed a potential elevated rate of inversions in the prairie vole lineage compared to the laboratory mouse and rat.</p> <p>Conclusions</p> <p>A genetic linkage map of the prairie vole has been constructed and represents the fourth genome-wide high-resolution linkage map reported for Muroid rodents and the first for a member of the Arvicolinae sub-family. This resource will advance studies designed to dissect the genetic basis of a variety of social behaviors and other traits in the prairie vole as well as our understanding of genome evolution in the genus <it>Microtus</it>.</p

Identification and analysis of in planta expressed genes of Magnaporthe oryzae

<p>Abstract</p> <p>Background</p> <p>Infection of plants by pathogens and the subsequent disease development involves substantial changes in the biochemistry and physiology of both partners. Analysis of genes that are expressed during these interactions represents a powerful strategy to obtain insights into the molecular events underlying these changes. We have employed expressed sequence tag (EST) analysis to identify rice genes involved in defense responses against infection by the blast fungus <it>Magnaporthe oryzae </it>and fungal genes involved in infectious growth within the host during a compatible interaction.</p> <p>Results</p> <p>A cDNA library was constructed with RNA from rice leaves (<it>Oryza sativa </it>cv. Hwacheong) infected with <it>M. oryzae </it>strain KJ201. To enrich for fungal genes, subtraction library using PCR-based suppression subtractive hybridization was constructed with RNA from infected rice leaves as a tester and that from uninfected rice leaves as the driver. A total of 4,148 clones from two libraries were sequenced to generate 2,302 non-redundant ESTs. Of these, 712 and 1,562 ESTs could be identified to encode fungal and rice genes, respectively. To predict gene function, Gene Ontology (GO) analysis was applied, with 31% and 32% of rice and fungal ESTs being assigned to GO terms, respectively. One hundred uniESTs were found to be specific to fungal infection EST. More than 80 full-length fungal cDNA sequences were used to validate <it>ab initio</it> annotated gene model of <it>M. oryzae</it> genome sequence.</p> <p>Conclusion</p> <p>This study shows the power of ESTs to refine genome annotation and functional characterization. Results of this work have advanced our understanding of the molecular mechanisms underpinning fungal-plant interactions and formed the basis for new hypothesis.</p

Dynamics of collective performance in collaboration networks

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Today, many complex tasks are assigned to teams, rather than individuals. One reason for teaming up is expansion of the skill coverage of each individual to the joint team skill set. However, numerous empirical studies of human groups suggest that the performance of equally skilled teams can widely differ. Two natural question arise: What are the factors defining team performance? and How can we best predict the performance of a given team on a specific task? While the team members' task-related capabilities constrain the potential for the team's success, the key to understanding team performance is in the analysis of the team process, encompassing the behaviors of the team members during task completion. In this study, we extend the existing body of research on team process and prediction models of team performance. Specifically, we analyze the dynamics of historical team performance over a series of tasks as well as the fine-grained patterns of collaboration between team members, and formally connect these dynamics to the team performance in the predictive models. Our major qualitative finding is that higher performing teams have well-connected collaboration networks-as indicated by the topological and spectral properties of the latter-which are more robust to perturbations, and where network processes spread more efficiently. Our major quantitative finding is that our predictive models deliver accurate team performance predictions-with a prediction error of 15-25%-on a variety of simple tasks, outperforming baseline models that do not capture the micro-level dynamics of team member behaviors. We also show how to use our models in an application, for optimal online planning of workload distribution in an organization. Our findings emphasize the importance of studying the dynamics of team collaboration as the major driver of high performance in teams.National Science Foundation (U.S.) (Grant 1322254