4,299 research outputs found
Nonmodal Growth of TravelingWaves on Blunt Cones at Hypersonic Speeds
The existing database of transition measurements in hypersonic ground facilities has established that, as the nosetip bluntness is increased, the onset of boundary layer transition over a circular cone at zero angle of attack shifts downstream. However, this trend is reversed at sufficiently large values of the nose Reynolds number, so that the transition onset location eventually moves upstream with a further increase in nose-tip bluntness. Because modal amplification is too weak to initiate transition at moderate-to-large bluntness values, nonmodal growth has been investigated as the potential basis for a physics-based model for the frustum transition. The present analysis investigates the nonmodal growth of traveling disturbances initiated within the nose-tip vicinity that peak within the entropy layer. Results show that, with increasing nose bluntness, both planar and oblique traveling disturbances experience appreciable energy amplification up to successively higher frequencies. For moderately blunt cones, the initial nonmmodal growth is followed by a partial decay that is more than overcome by an eventual, modal growth as Mack-mode waves. For larger bluntness values, the Mack-mode waves are not amplified anywhere upstream of the experimentally measured transition location, but the traveling modes still undergo a significant amount of nonmodal growth. This finding does not provide a definitive link between optimal growth and the onset of transition, but it is qualitatively consistent with the experimental observations that frustum transition in the absence of sufficient Mack-mode amplification implies a double peak in disturbance amplification and the appearance of transitional events above the boundary-layer edge
Production of Astaxanthin Using Modified E. coli Cells
There are several promising markets for naturally synthesized Astaxanthin, a carotenoid found in krill, shrimp, salmon, and other marine life that imparts to these creatures a pink coloring of the flesh and has demonstrated human health-promoting anti-inflammatory and antioxidant activity. Compared to Astaxanthin produced through chemical synthesis, Astaxanthin synthesized through natural fermentative processes (in yeast and algae) is esterified, imparting greater antioxidant activity as well as bioavailability and making it the preferred ingredient for nutraceutical formulations. Additionally, as consumer preferences trend toward natural production processes free from the use of petrochemical solvents which may pose hazards to health hazards, fermentative production coupled with an extraction process featuring more environment- and health-friendly solvents is desired. Recently, a strain of E.coli has been genetically optimized to produce Astaxanthin, offering a cheaper synthesis route compared with algal cultivation. Herein, the authors propose a process for the production of natural Astaxanthin through fermentation in genetically modified E.coli and recovery of the compound from biomass via supercritical CO2 extraction. The fermentation seed train is composed of three pre-seed, two seed, and three production fed-batch fermenters. Biomass from the production stage is collected in a harvest/surge tank for continuous downstream processing. The biomass is concentrated in broth, the cells are lysed, and the slurry of lysed cells are dried. The lysis product is loaded with fructose and diatomaceous earth in order to produce biomass pellets that are appropriate for the extraction phase. Supercritical CO2 with ethanol co-solvent is used to extract Astaxanthin from these pellets. Astaxanthin is heat-sensitive and has low accumulation in cells. Despite the expensive equipment necessary to preserve the structure and activity of the product and the low yearly production rate, the high selling price of Astaxanthin makes this process economically profitable, with an investor’s rate of return of 125%, net present value of $468 million, and return on investment of 171%
Hamiltonian simulation with optimal sample complexity
© 2017 Author(s). We investigate the sample complexity of Hamiltonian simulation: how many copies of an unknown quantum state are required to simulate a Hamiltonian encoded by the density matrix of that state? We show that the procedure proposed by Lloyd, Mohseni, and Rebentrost [Nat. Phys., 10(9):631-633, 2014] is optimal for this task. We further extend their method to the case of multiple input states, showing how to simulate any Hermitian polynomial of the states provided. As applications, we derive optimal algorithms for commutator simulation and orthogonality testing, and we give a protocol for creating a coherent superposition of pure states, when given sample access to those states. We also show that this sample-based Hamiltonian simulation can be used as the basis of a universal model of quantum computation that requires only partial swap operations and simple single-qubit states.S.K. and C.Y.L. are funded by the Department of Defense. G.H.L. is funded by the NSF CCR and the ARO quantum computing projects. M.O. acknowledges Leverhulme Trust Early Career Fellowship (ECF-2015-256) and European Union project QALGO (Grant Agreement No. 600700) for financial support. T.J.Y. thanks the DoD, Air Force Office of Scientific Research, National Defense Science and Engineering Graduate (NDSEG) Fellowship, 32 CFR 168a. The authors are grateful to the University of Maryland Libraries’ Open Access Publishing Fund and the Massachusetts Institute of Technology Open Access Publishing Fund for partial funding for open access
Quantum algorithms for connectivity and related problems
An important family of span programs, st-connectivity span programs, have been used to design quantum algorithms in various contexts, including a number of graph problems and formula evaluation problems. The complexity of the resulting algorithms depends on the largest positive witness size of any 1-input, and the largest negative witness size of any 0-input. Belovs and Reichardt first showed that the positive witness size is exactly characterized by the effective resistance of the input graph, but only rough upper bounds were known previously on the negative witness size. We show that the negative witness size in an st-connectivity span program is exactly characterized by the capacitance of the input graph. This gives a tight analysis for algorithms based on st-connectivity span programs on any set of inputs. We use this analysis to give a new quantum algorithm for estimating the capacitance of a graph. We also describe a new quantum algorithm for deciding if a graph is connected, which improves the previous best quantum algorithm for this problem if we're promised that either the graph has at least k > 1 components, or the graph is connected and has small average resistance, which is upper bounded by the diameter. We also give an alternative algorithm for deciding if a graph is connected that can be better than our first algorithm when the maximum degree is small. Finally, using ideas from our second connectivity algorithm, we give an algorithm for estimating the algebraic connectivity of a graph, the second largest eigenvalue of the Laplacian
The origin of ultra diffuse galaxies: stellar feedback and quenching
We test if the cosmological zoom-in simulations of isolated galaxies from the
FIRE project reproduce the properties of ultra diffuse galaxies. We show that
stellar feedback-generated outflows that dynamically heat galactic stars,
together with a passively aging stellar population after imposed quenching
(from e.g. infall into a galaxy cluster), naturally reproduce the observed
population of red UDGs, without the need for high spin halos or dynamical
influence from their host cluster. We reproduce the range of surface
brightness, radius and absolute magnitude of the observed z=0 red UDGs by
quenching simulated galaxies at a range of different times. They represent a
mostly uniform population of dark matter-dominated galaxies with M_star ~1e8
Msun, low metallicity and a broad range of ages. The most massive simulated
UDGs require earliest quenching and are therefore the oldest. Our simulations
provide a good match to the central enclosed masses and the velocity
dispersions of the observed UDGs (20-50 km/s). The enclosed masses of the
simulated UDGs remain largely fixed across a broad range of quenching times
because the central regions of their dark matter halos complete their growth
early. A typical UDG forms in a dwarf halo mass range of Mh~4e10-1e11 Msun. The
most massive red UDG in our sample requires quenching at z~3 when its halo
reached Mh ~ 1e11 Msun. If it, instead, continues growing in the field, by z=0
its halo mass reaches > 5e11 Msun, comparable to the halo of an L* galaxy. If
our simulated dwarfs are not quenched, they evolve into bluer low-surface
brightness galaxies with mass-to-light ratios similar to observed field dwarfs.
While our simulation sample covers a limited range of formation histories and
halo masses, we predict that UDG is a common, and perhaps even dominant, galaxy
type around Ms~1e8 Msun, both in the field and in clusters.Comment: 20 pages, 13 figures; match the MNRAS accepted versio
Neighborhood size-effects shape growing population dynamics in evolutionary public goods games
An evolutionary game emerges when a subset of individuals incur costs to provide benefits to all individuals. Public goods games (PGG) cover the essence of such dilemmas in which cooperators are prone to exploitation by defectors. We model the population dynamics of a non-linear\ua0PGG and consider density-dependence on the global level, while the game occurs within local neighborhoods. At low cooperation, increases in the public good provide increasing returns. At high cooperation, increases provide diminishing returns. This mechanism leads to diverse evolutionarily stable strategies, including monomorphic and polymorphic populations, and neighborhood-size-driven state changes, resulting in hysteresis between equilibria. Stochastic or strategy-dependent variations in neighborhood sizes favor coexistence by destabilizing monomorphic states. We integrate our model with experiments of cancer cell growth and confirm that our framework describes PGG dynamics observed in cellular populations. Our findings advance the understanding of how neighborhood-size effects in PGG shape the dynamics of growing populations. \ua9 2019, The Author(s)
Effects of Dietary Sodium Intake on Blood Flow Regulation During Exercise in Salt Resistant Individuals
PURPOSE: Dietary sodium intake guidelines is ≤2,300 mg/day, yet is exceeded by 90% of Americans. This study examined the impact of a high sodium diet on blood flow regulation during exercise. METHODS: Six males (25 ± 2 years) consumed dietary sodium intake guidelines for two weeks, with one week salt-capsule supplemented (HS: 6,900 mg/day of sodium) and the other week placebo-capsule supplemented (LS: 2,300 mg/day of sodium). At the end of each week, peripheral hemodynamic measurements [blood flow (BF), shear rate (SR), and flow mediated dilation (FMD)/SR)] of the brachial and superficial femoral artery were taken during handgrip (HG) and plantar flexion (PF) exercise, respectively. Each exercise workload was 3 minutes and progressed by 8 kilograms until exhaustion. RESULTS: There were no differences between LS and HS in blood pressure (82 ± 4 v 80 ± 5 mmHg; p = 0.3) or heart rate (56 ± 6 v 59 ± 10 bpm; p = 0.4). HG and PF exercise increased BF, SR, and FMD/SR across workload (p \u3c 0.03 for all), but no difference between diets (p \u3e 0.05 for all). CONCLUSION: Despite previous reports that HS impairs resting vascular function, this study revealed that peripheral vascular function and blood flow regulation during exercise is not impacted by a HS diet.https://scholarscompass.vcu.edu/gradposters/1082/thumbnail.jp
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