9,402 research outputs found
Kinetics and Products of the Acid-Catalyzed Ring-Opening of Atmospherically Relevant Butyl Epoxy Alcohols
Epoxydiols are produced in the gas phase from the photo-oxidation of isoprene in the absence of significant mixing ratios of nitrogen oxides (NO_x). The reactive uptake of these compounds onto acidic aerosols has been shown to produce secondary organic aerosol (SOA). To better characterize the fate of isoprene epoxydiols in the aerosol phase, the kinetics and products of the acid-catalyzed ring-opening reactions of four hydroxy-substituted epoxides were studied by nuclear magnetic resonance (NMR) techniques. Polyols and sulfate esters are observed from the ring-opening of the epoxides in solutions of H_2SO_4/Na_2SO_4. Likewise, polyols and nitrate esters are produced in solutions of HNO_3/NaNO_3. In sulfuric acid, the rate of acid-catalyzed ring-opening is dependent on hydronium ion activity, sulfate ion, and bisulfate. The rates are much slower than the nonhydroxylated equivalent epoxides; however, the hydroxyl groups make them much more water-soluble. A model was constructed with the major channels for epoxydiol loss (i.e., aerosol-phase ring-opening, gas-phase oxidation, and deposition). In the atmosphere, SOA formation from epoxydiols will depend on a number of variables (e.g., pH and aerosol water content) with the yield of ring-opening products varying from less than 1% to greater than 50%
Field-assisted Shockley-Read-Hall recombinations in III-Nitride quantum wells
The physical process driving low-current non-radiative recombinations in
high-quality III-Nitride quantum wells is investigated. Lifetime measurements
reveal that these recombinations scale with the overlap of the electron and
hole wavefunctions and show weak temperature dependence, in contrast with
common empirical expectations for Shockley-Read-Hall recombinations. A model of
field-assisted multiphonon point defect recombination in quantum wells is
introduced, and shown to quantitatively explain the data. This study provides
insight on the high efficiency of III-Nitride light emitters
Determinants of Mortality and Disease Progression of Kaposi Sarcoma in a Primary care ART Programme in Khayelitsha, South Africa
CROI 200
Quantum Hamiltonian Learning Using Imperfect Quantum Resources
Identifying an accurate model for the dynamics of a quantum system is a
vexing problem that underlies a range of problems in experimental physics and
quantum information theory. Recently, a method called quantum Hamiltonian
learning has been proposed by the present authors that uses quantum simulation
as a resource for modeling an unknown quantum system. This approach can, under
certain circumstances, allow such models to be efficiently identified. A major
caveat of that work is the assumption of that all elements of the protocol are
noise-free. Here, we show that quantum Hamiltonian learning can tolerate
substantial amounts of depolarizing noise and show numerical evidence that it
can tolerate noise drawn from other realistic models. We further provide
evidence that the learning algorithm will find a model that is maximally close
to the true model in cases where the hypothetical model lacks terms present in
the true model. Finally, we also provide numerical evidence that the algorithm
works for non-commuting models. This work illustrates that quantum Hamiltonian
learning can be performed using realistic resources and suggests that even
imperfect quantum resources may be valuable for characterizing quantum systems.Comment: 16 pages 11 Figure
Invasive Wild pigs as primary nest predators for Wild turkeys
Depredation of wild turkey (Meleagris gallopavo) nests is a leading cause of reduced recruitment for the recovering and iconic game species. invasive wild pigs (Sus scrofa) are known to depredate nests, and have been expanding throughout the distributed range of wild turkeys in north America. We sought to gain better insight on the magnitude of wild pigs depredating wild turkey nests. We constructed simulated wild turkey nests throughout the home ranges of 20 GPS-collared wild pigs to evaluate nest depredation relative to three periods within the nesting season (i.e., early, peak, and late) and two nest densities (moderate = 12.5-25 nests/km2, high = 25-50 nests/km2) in south-central Texas, USA during March–June 2016. Overall, the estimated probability of nest depredation by wild pigs was 0.3, equivalent to native species of nest predators in the study area (e.g., gray fox [Urocyon cinereoargenteus], raccoon [Procyon lotor], and coyote [Canis latrans]). female wild pigs exhibited a constant rate of depredation regardless of nesting period or density of nests. However, male wild pigs increased their rate of depredation in areas with higher nest densities. Management efforts should remove wild pigs to reduce nest failure in wild turkey populations especially where recruitment is low
Paradoxical popups: Why are they hard to catch?
Even professional baseball players occasionally find it difficult to
gracefully approach seemingly routine pop-ups. This paper describes a set of
towering pop-ups with trajectories that exhibit cusps and loops near the apex.
For a normal fly ball, the horizontal velocity is continuously decreasing due
to drag caused by air resistance. But for pop-ups, the Magnus force (the force
due to the ball spinning in a moving airflow) is larger than the drag force. In
these cases the horizontal velocity decreases in the beginning, like a normal
fly ball, but after the apex, the Magnus force accelerates the horizontal
motion. We refer to this class of pop-ups as paradoxical because they appear to
misinform the typically robust optical control strategies used by fielders and
lead to systematic vacillation in running paths, especially when a trajectory
terminates near the fielder. In short, some of the dancing around when
infielders pursue pop-ups can be well explained as a combination of bizarre
trajectories and misguidance by the normally reliable optical control strategy,
rather than apparent fielder error. Former major league infielders confirm that
our model agrees with their experiences.Comment: 28 pages, 10 figures, sumitted to American Journal of Physic
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The Persistent Southern Disadvantage in Us Early Life Mortality, 1965‒2014
Background: Recent studies of US adult mortality demonstrate a growing disadvantage among southern states. Few studies have examined long-term trends and geographic patterns in US early life (ages 1 to 24) mortality, ages at which key risk factors and causes of death are quite different than among adults. Objective: This article examines trends and variations in early life mortality rates across US states and census divisions. We assess whether those variations have changed over a 50-year time period and which causes of death contribute to contemporary geographic disparities. Methods: We calculate all-cause and cause-specific death rates using death certificate data from the Multiple Cause of Death files, combining public-use files from 1965‒2004 and restricted data with state geographic identifiers from 2005‒2014. State population (denominator) data come from US decennial censuses or intercensal estimates. Results: Results demonstrate a persistent mortality disadvantage for young people (ages 1 to 24) living in southern states over the last 50 years, particularly those located in the East South Central and West South Central divisions. Motor vehicle accidents and homicide by firearm account for most of the contemporary southern disadvantage in US early life mortality. Contribution: Our results illustrate that US children and youth living in the southern United States have long suffered from higher levels of mortality than children and youth living in other parts of the country. Our findings also suggest the contemporary southern disadvantage in US early life mortality could potentially be reduced with state-level policies designed to prevent deaths involving motor vehicles and firearms
Behavioral modeling of integrated phase-change photonic devices for neuromorphic computing applications
The combination of phase-change materials and integrated photonics has led to the development of new forms of all-optical devices, including photonic memories, arithmetic and logic processors, and synaptic and neuronal mimics. Such devices can be readily fabricated into photonic integrated circuits, so potentially delivering large-scale all-optical arithmetic-logic units and neuromorphic processing chips. To facilitate in the design and optimization of such large-scale systems, and to aid in the understanding of device and system performance, fast yet accurate computer models are needed. Here, we describe the development of a behavioral modeling tool that meets such requirements, being capable of essentially instantaneous modeling of the write, erase, and readout performance of various integrated phase-change photonic devices, including those for synaptic and neuronal mimics
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