Federal Aviation Administration's approach to engine rotor integrity

Sections of the U.S. Airworthiness Standards which contribute to rotor integrity are explored. Reports published under NASA's Rotor Burst Protection program are included in current FAA studies to determine the weight penalty for two different levels of increased containment, and the penalty associated with protecting critical structure and systems, the passenger cabin, and the flight deck by strategic location of armor shields or deflector plates. Findings of the two studies will be used to propose revisions to regulations to reduce uncontained rotor failures

Good Quantum Convolutional Error Correction Codes And Their Decoding Algorithm Exist

Quantum convolutional code was introduced recently as an alternative way to protect vital quantum information. To complete the analysis of quantum convolutional code, I report a way to decode certain quantum convolutional codes based on the classical Viterbi decoding algorithm. This decoding algorithm is optimal for a memoryless channel. I also report three simple criteria to test if decoding errors in a quantum convolutional code will terminate after a finite number of decoding steps whenever the Hilbert space dimension of each quantum register is a prime power. Finally, I show that certain quantum convolutional codes are in fact stabilizer codes. And hence, these quantum stabilizer convolutional codes have fault-tolerant implementations.Comment: Minor changes, to appear in PR

Mixed quantum state detection with inconclusive results

We consider the problem of designing an optimal quantum detector with a fixed rate of inconclusive results that maximizes the probability of correct detection, when distinguishing between a collection of mixed quantum states. We develop a sufficient condition for the scaled inverse measurement to maximize the probability of correct detection for the case in which the rate of inconclusive results exceeds a certain threshold. Using this condition we derive the optimal measurement for linearly independent pure-state sets, and for mixed-state sets with a broad class of symmetries. Specifically, we consider geometrically uniform (GU) state sets and compound geometrically uniform (CGU) state sets with generators that satisfy a certain constraint. We then show that the optimal measurements corresponding to GU and CGU state sets with arbitrary generators are also GU and CGU respectively, with generators that can be computed very efficiently in polynomial time within any desired accuracy by solving a semidefinite programming problem.Comment: Submitted to Phys. Rev.

Multi-Exciton Spectroscopy of a Single Self Assembled Quantum Dot

We apply low temperature confocal optical microscopy to spatially resolve, and spectroscopically study a single self assembled quantum dot. By comparing the emission spectra obtained at various excitation levels to a theoretical many body model, we show that: Single exciton radiative recombination is very weak. Sharp spectral lines are due to optical transitions between confined multiexcitonic states among which excitons thermalize within their lifetime. Once these few states are fully occupied, broad bands appear due to transitions between states which contain continuum electrons.Comment: 12 pages, 4 figures, submitted for publication on Jan,28 199

Quantifying the Performance of Quantum Codes

We study the properties of error correcting codes for noise models in the presence of asymmetries and/or correlations by means of the entanglement fidelity and the code entropy. First, we consider a dephasing Markovian memory channel and characterize the performance of both a repetition code and an error avoiding code in terms of the entanglement fidelity. We also consider the concatenation of such codes and show that it is especially advantageous in the regime of partial correlations. Finally, we characterize the effectiveness of the codes and their concatenation by means of the code entropy and find, in particular, that the effort required for recovering such codes decreases when the error probability decreases and the memory parameter increases. Second, we consider both symmetric and asymmetric depolarizing noisy quantum memory channels and perform quantum error correction via the five qubit stabilizer code. We characterize this code by means of the entanglement fidelity and the code entropy as function of the asymmetric error probabilities and the degree of memory. Specifically, we uncover that while the asymmetry in the depolarizing errors does not affect the entanglement fidelity of the five qubit code, it becomes a relevant feature when the code entropy is used as a performance quantifier.Comment: 21 pages, 10 figure

Common structure in the heterogeneity of plant-matter decay

Carbon removed from the atmosphere by photosynthesis is released back by respiration. Although some organic carbon is degraded quickly, older carbon persists; consequently carbon stocks are much larger than predicted by initial decomposition rates. This disparity can be traced to a wide range of first-order decay-rate constants, but the rate distributions and the mechanisms that determine them are unknown. Here, we pose and solve an inverse problem to find the rate distributions corresponding to the decomposition of plant matter throughout North America. We find that rate distributions are lognormal, with a mean and variance that depend on climatic conditions and substrate. Changes in temperature and precipitation scale all rates similarly, whereas the initial substrate composition sets the time scale of faster rates. These findings probably result from the interplay of stochastic processes and biochemical kinetics, suggesting that the intrinsic variability of decomposers, substrate and environment results in a predictable distribution of rates. Within this framework, turnover times increase exponentially with the kinetic heterogeneity of rates, thereby providing a theoretical expression for the persistence of recalcitrant organic carbon in the natural environment

PGC1α

PGC1α, a transcriptional coactivator, interacts with PPARs and others to regulate skeletal muscle metabolism. PGC1α undergoes splicing to produce several mRNA variants, with the NTPGC1α variant having a similar biological function to the full length PGC1α (FLPGC1α). CVD is associated with obesity and T2D and a lower percentage of type 1 oxidative fibers and impaired mitochondrial function in skeletal muscle, characteristics determined by PGC1α expression. PGC1α expression is epigenetically regulated in skeletal muscle to determine mitochondrial adaptations, and epigenetic modifications may regulate mRNA splicing. We report in this paper that skeletal muscle PGC1α  −1 nucleosome (−1N) position is associated with splice variant NTPGC1α but not FLPGC1α expression. Division of participants based on the −1N position revealed that those individuals with a −1N phased further upstream from the transcriptional start site (UP) expressed lower levels of NTPGC1α than those with the −1N more proximal to TSS (DN). UP showed an increase in body fat percentage and serum total and LDL cholesterol. These findings suggest that the −1N may be a potential epigenetic regulator of NTPGC1α splice variant expression, and −1N position and NTPGC1α variant expression in skeletal muscle are linked to CVD risk. This trial is registered with clinicaltrials.gov, identifier NCT00458133

Radiation Characteristics of a 0.11 Micrometer Modified Commercial CMOS Process

We present radiation data, Total Ionizing Dose and Single Event Effects, on the LSI Logic 0.11 micron commercial process and two modified versions of this process. Modified versions include a buried layer to guarantee Single Event Latchup immunity

The impact of predation by marine mammals on Patagonian toothfish longline fisheries

Predatory interaction of marine mammals with longline fisheries is observed globally, leading to partial or complete loss of the catch and in some parts of the world to considerable financial loss. Depredation can also create additional unrecorded fishing mortality of a stock and has the potential to introduce bias to stock assessments. Here we aim to characterise depredation in the Patagonian toothfish (Dissostichus eleginoides) fishery around South Georgia focusing on the spatio-temporal component of these interactions. Antarctic fur seals (Arctocephalus gazella), sperm whales (Physeter macrocephalus), and orcas (Orcinus orca) frequently feed on fish hooked on longlines around South Georgia. A third of longlines encounter sperm whales, but loss of catch due to sperm whales is insignificant when compared to that due to orcas, which interact with only 5% of longlines but can take more than half of the catch in some cases. Orca depredation around South Georgia is spatially limited and focused in areas of putative migration routes, and the impact is compounded as a result of the fishery also concentrating in those areas at those times. Understanding the seasonal behaviour of orcas and the spatial and temporal distribution of “depredation hot spots” can reduce marine mammal interactions, will improve assessment and management of the stock and contribute to increased operational efficiency of the fishery. Such information is valuable in the effort to resolve the human-mammal conflict for resources

Projecting marine mammal distribution in a changing climate

Climate-related shifts in marine mammal range and distribution have been observed in some populations; however, the nature and magnitude of future responses are uncertain in novel environments projected under climate change. This poses a challenge for agencies charged with management and conservation of these species. Specialized diets, restricted ranges, or reliance on specific substrates or sites (e.g., for pupping) make many marine mammal populations particularly vulnerable to climate change. High-latitude, predominantly ice-obligate, species have experienced some of the largest changes in habitat and distribution and these are expected to continue. Efforts to predict and project marine mammal distributions to date have emphasized data-driven statistical habitat models. These have proven successful for short time-scale (e.g., seasonal) management activities, but confidence that such relationships will hold for multi-decade projections and novel environments is limited. Recent advances in mechanistic modeling of marine mammals (i.e., models that rely on robust physiological and ecological principles expected to hold under climate change) may address this limitation. The success of such approaches rests on continued advances in marine mammal ecology, behavior, and physiology together with improved regional climate projections. The broad scope of this challenge suggests initial priorities be placed on vulnerable species or populations (those already experiencing declines or projected to undergo ecological shifts resulting from climate changes that are consistent across climate projections) and species or populations for which ample data already exist (with the hope that these may inform climate change sensitivities in less well observed species or populations elsewhere). The sustained monitoring networks, novel observations, and modeling advances required to more confidently project marine mammal distributions in a changing climate will ultimately benefit management decisions across time-scales, further promoting the resilience of marine mammal populations