Optimized, unequal pulse spacing in multiple echo sequences improves refocusing in magnetic resonance.

A recent quantum computing paper (G. S. Uhrig, Phys. Rev. Lett. 98, 100504 (2007)) analytically derived optimal pulse spacings for a multiple spin echo sequence designed to remove decoherence in a two-level system coupled to a bath. The spacings in what has been called a "Uhrig dynamic decoupling (UDD) sequence" differ dramatically from the conventional, equal pulse spacing of a Carr-Purcell-Meiboom-Gill (CPMG) multiple spin echo sequence. The UDD sequence was derived for a model that is unrelated to magnetic resonance, but was recently shown theoretically to be more general. Here we show that the UDD sequence has theoretical advantages for magnetic resonance imaging of structured materials such as tissue, where diffusion in compartmentalized and microstructured environments leads to fluctuating fields on a range of different time scales. We also show experimentally, both in excised tissue and in a live mouse tumor model, that optimal UDD sequences produce different T(2)-weighted contrast than do CPMG sequences with the same number of pulses and total delay, with substantial enhancements in most regions. This permits improved characterization of low-frequency spectral density functions in a wide range of applications.

The spacing effect depends on an encoding deficit, retrieval, and time in working memory: evidence from once-presented words.

The spacing effect in list learning occurs because identical massed items suffer encoding deficits and because spaced items benefit from retrieval and increased time in working memory. Requiring the retrieval of identical items produced a spacing effect for recall and recognition, both for intentional and incidental learning. Not requiring retrieval produced spacing only for intentional learning because intentional learning encourages retrieval. Once-presented words provided baselines for these effects. Next, massed and spaced word pairs were judged for matches on their first three letters, forcing retrieval. The words were not identical, so there was no encoding deficit. Retrieval could and did cause spacing only for the first word of each pair; time in working memory, only for the second.

Two-stage Kondo effect and Kondo-box level spectroscopy in a carbon nanotube

The concept of the "Kondo box" describes a single spin, antiferromagnetically coupled to a quantum dot with a finite level spacing. Here, a Kondo box is formed in a carbon nanotube interacting with a localized electron. We investigate the spins of its first few eigenstates and compare them to a recent theory. In an "open" Kondo-box, strongly coupled to the leads, we observe a nonmonotonic temperature dependence of the nanotube conductance, which results from a competition between the Kondo-box singlet and the "conventional" Kondo state that couples the nanotube to the leads. © 2010 The American Physical Society.

Using fractal downscaling of satellite precipitation products for hydrometeorological applications

The objective of spatial downscaling strategies is to increase the information content of coarse datasets at smaller scales. In the case of quantitative precipitation estimation (QPE) for hydrological applications, the goal is to close the scale gap between the spatial resolution of coarse datasets (e.g., gridded satellite precipitation products at resolution L × L) and the high resolution (l × l; L»l) necessary to capture the spatial features that determine spatial variability of water flows and water stores in the landscape. In essence, the downscaling process consists of weaving subgrid-scale heterogeneity over a desired range of wavelengths in the original field. The defining question is, which properties, statistical and otherwise, of the target field (the known observable at the desired spatial resolution) should be matched, with the caveat that downscaling methods be as a general as possible and therefore ideally without case-specific constraints and/or calibration requirements? Here, the attention is focused on two simple fractal downscaling methods using iterated functions systems (IFS) and fractal Brownian surfaces (FBS) that meet this requirement. The two methods were applied to disaggregate spatially 27 summertime convective storms in the central United States during 2007 at three consecutive times (1800, 2100, and 0000 UTC, thus 81 fields overall) from the Tropical Rainfall Measuring Mission (TRMM) version 6 (V6) 3B42 precipitation product (~25-km grid spacing) to the same resolution as the NCEP stage IV products (~4-km grid spacing). Results from bilinear interpolation are used as the control. A fundamental distinction between IFS and FBS is that the latter implies a distribution of downscaled fields and thus an ensemble solution, whereas the former provides a single solution. The downscaling effectiveness is assessed using fractal measures (the spectral exponent β, fractal dimension D, Hurst coefficient H, and roughness amplitude R) and traditional operational scores statistics scores [false alarm rate (FR), probability of detection (PD), threat score (TS), and Heidke skill score (HSS)], as well as bias and the root-mean-square error (RMSE). The results show that both IFS and FBS fractal interpolation perform well with regard to operational skill scores, and they meet the additional requirement of generating structurally consistent fields. Furthermore, confidence intervals can be directly generated from the FBS ensemble. The results were used to diagnose errors relevant for hydrometeorological applications, in particular a spatial displacement with characteristic length of at least 50 km (2500 km2) in the location of peak rainfall intensities for the cases studied. © 2010 American Meteorological Society.

Analytic expressions for the constitutive parameters of magnetoelectric metamaterials

Electromagnetic metamaterials are artificially structured media typically composed of arrays of resonant electromagnetic circuits, the dimension and spacing of which are considerably smaller than the free-space wavelengths of operation. The constitutive parameters for metamaterials, which can be obtained using full-wave simulations in conjunction with numerical retrieval algorithms, exhibit artifacts related to the finite size of the metamaterial cell relative to the wavelength. Liu showed that the complicated, frequency-dependent forms of the constitutive parameters can be described by a set of relatively simple analytical expressions. These expressions provide useful insight and can serve as the basis for more intelligent interpolation or optimization schemes. Here, we show that the same analytical expressions can be obtained using a transfer-matrix formalism applied to a one-dimensional periodic array of thin, resonant, dielectric, or magnetic sheets. The transfer-matrix formalism breaks down, however, when both electric and magnetic responses are present in the same unit cell, as it neglects the magnetoelectric coupling between unit cells. We show that an alternative analytical approach based on the same physical model must be applied for such structures. Furthermore, in addition to the intercell coupling, electric and magnetic resonators within a unit cell may also exhibit magnetoelectric coupling. For such cells, we find an analytical expression for the effective index, which displays markedly characteristic dispersion features that depend on the strength of the coupling coefficient. We illustrate the applicability of the derived expressions by comparing to full-wave simulations on magnetoelectric unit cells. We conclude that the design of metamaterials with tailored simultaneous electric and magnetic response-such as negative index materials-will generally be complicated by potentially unwanted magnetoelectric coupling. © 2010 The American Physical Society.

Reexamining the science of marine protected areas: Linking knowledge to action

Marine protected areas (MPAs) are often implemented to conserve or restore species, fisheries, habitats, ecosystems, and ecological functions and services; buffer against the ecological effects of climate change; and alleviate poverty in coastal communities. Scientific research provides valuable insights into the social and ecological impacts of MPAs, as well as the factors that shape these impacts, providing useful guidance or "rules of thumb" for science-based MPA policy. Both ecological and social factors foster effective MPAs, including substantial coverage of representative habitats and oceanographic conditions; diverse size and spacing; protection of habitat bottlenecks; participatory decisionmaking arrangements; bounded and contextually appropriate resource use rights; active and accountable monitoring and enforcement systems; and accessible conflict resolution mechanisms. For MPAs to realize their full potential as a tool for ocean governance, further advances in policy-relevant MPA science are required. These research frontiers include MPA impacts on nontarget and wide-ranging species and habitats; impacts beyond MPA boundaries, on ecosystem services, and on resource-dependent human populations, as well as potential scale mismatches of ecosystem service flows. Explicitly treating MPAs as "policy experiments" and employing the tools of impact evaluation holds particular promise as a way for policy-relevant science to inform and advance science-based MPA policy. © 2011 Wiley Periodicals, Inc.

Experimental evidence that phenotypic divergence in predators drives community divergence in prey.

Studies of adaptive divergence have traditionally focused on the ecological causes of trait diversification, while the ecological consequences of phenotypic divergence remain relatively unexplored. Divergence in predator foraging traits, in particular, has the potential to impact the structure and dynamics of ecological communities. To examine the effects of predator trait divergence on prey communities, we exposed zooplankton communities in lake mesocosms to predation from either anadromous or landlocked (freshwater resident) alewives, which have undergone recent and rapid phenotypic differentiation in foraging traits (gape width, gill raker spacing, and prey size-selectivity). Anadromous alewives, which exploit large prey items, significantly reduced the mean body size, total biomass, species richness, and diversity of crustacean zooplankton relative to landlocked alewives, which exploit smaller prey. The zooplankton responses observed in this experiment are consistent with patterns observed in lakes. This study provides direct evidence that phenotypic divergence in predators, even in its early stages, can play a critical role in determining prey community structure.