Multiple quantum solid-state NMR indicates a parallel, not antiparallel, organization of β-sheets in Alzheimer's β-amyloid fibrils

Senile plaques associated with Alzheimer's disease contain deposits of fibrils formed by 39- to 43-residue β-amyloid peptides with possible neurotoxic effects. X-ray diffraction measurements on oriented fibril bundles have indicated an extended β-sheet structure for Alzheimer's β-amyloid fibrils and other amyloid fibrils, but the supramolecular organization of the β-sheets and other structural details are not well established because of the intrinsically noncrystalline, insoluble nature of amyloid fibrils. Here we report solid-state NMR measurements, using a multiple quantum (MQ) 13C NMR technique, that probe the β-sheet organization in fibrils formed by the full-length, 40-residue β-amyloid peptide (Aβ1–40). Although an antiparallel β-sheet organization often is assumed and is invoked in recent structural models for full-length β-amyloid fibrils, the MQNMR data indicate an in-register, parallel organization. This work provides site-specific, atomic-level structural constraints on full-length β-amyloid fibrils and applies MQNMR to a significant problem in structural biology.

Multi-responsiveness of single anterior pituitary cells to hypothalamic-releasing hormones: A cellular basis for paradoxical secretion

The classic view for hypothalamic regulation of anterior pituitary (AP) hormone secretion holds that release of each AP hormone is controlled specifically by a corresponding hypothalamic-releasing hormone (HRH). In this scenario, binding of a given HRH (thyrotropin-, growth hormone-, corticotropin-, and luteinizing hormone-releasing hormones) to specific receptors in its target cell increases the concentration of cytosolic Ca2+ ([Ca2+]i), thereby selectively stimulating the release of the appropriate hormone. However, “paradoxical” responses of AP cells to the four well-established HRHs have been observed repeatedly with both in vivo and in vitro systems, raising the possibility of functional overlap between the different AP cell types. To explore this possibility, we evaluated the effects of HRHs on [Ca2+]i in single AP cells identified immunocytochemically by the hormone they stored. We found that each of the five major AP cell types contained discrete subpopulations that were able to respond to several HRHs. The relative abundance of these multi-responsive cells was 59% for lactotropes, 33% for thyrotropes, and in the range of 47–55% for gonadotropes, corticotropes, and somatotropes. Analysis of prolactin release from single living cells revealed that each of the four HRHs tested were able to induce hormone release from a discrete lactotrope subpopulation, the size of which corresponded closely to that in which [Ca2+]i changes were induced by the same secretagogues. When viewed as a whole, our diverse functional measurements of multi-responsiveness suggest that hypothalamic control of pituitary function is more complicated than previously envisioned. Moreover, they provide a cellular basis for the so-called “paradoxical” behavior of pituitary cells to hypothalamic hypophysiotropic agents.

Increase in the Quantum Yield of Photoinhibition Contributes to Copper Toxicity in Vivo1

The effect of copper on photoinhibition of photosystem II in vivo was studied in bean (Phaseolus vulgaris L. cv Dufrix). The plants were grown hydroponically in the presence of various concentrations of Cu2+ ranging from the optimum 0.3 μm (control) to 15 μm. The copper concentration of leaves varied according to the nutrient medium from a control value of 13 mg kg−1 dry weight to 76 mg kg−1 dry weight. Leaf samples were illuminated in the presence and absence of lincomycin at different light intensities (500–1500 μmol photons m−2 s−1). Lincomycin prevents the concurrent repair of photoinhibitory damage by blocking chloroplast protein synthesis. The photoinhibitory decrease in the light-saturated rate of O2 evolution measured from thylakoids isolated from treated leaves correlated well with the decrease in the ratio of variable to maximum fluorescence measured from the leaf discs; therefore, the fluorescence ratio was used as a routine measurement of photoinhibition in vivo. Excess copper was found to affect the equilibrium between photoinhibition and repair, resulting in a decrease in the steady-state concentration of active photosystem II centers of illuminated leaves. This shift in equilibrium apparently resulted from an increase in the quantum yield of photoinhibition (ΦPI) induced by excess copper. The kinetic pattern of photoinhibition and the independence of ΦPI on photon flux density were not affected by excess copper. An increase in ΦPI may contribute substantially to Cu2+ toxicity in certain plant species.

Sampling Quantum Nonlocal Correlations with High Probability

It is well known that quantum correlations for bipartite dichotomic measurements are those of the form (Formula presented.), where the vectors ui and vj are in the unit ball of a real Hilbert space. In this work we study the probability of the nonlocal nature of these correlations as a function of (Formula presented.), where the previous vectors are sampled according to the Haar measure in the unit sphere of (Formula presented.). In particular, we prove the existence of an (Formula presented.) such that if (Formula presented.), (Formula presented.) is nonlocal with probability tending to 1 as (Formula presented.), while for (Formula presented.), (Formula presented.) is local with probability tending to 1 as (Formula presented.).

Single-exciton spectroscopy of semimagnetic quantum dots

A photoexcited II-VI semiconductor quantum dots doped with a few Mn spins is considered. The effects of spin-exciton interactions and the resulting multispin correlations on the photoluminescence are calculated by numerical diagonalization of the Hamiltonian, including exchange interaction between electrons, holes, and Mn spins, as well as spin-orbit interaction. The results provide a unified description of recent experiments on the photoluminesnce of dots with one and many Mn atoms as well as optically induced ferromagnetism in semimagnetic quantum dots.

Impurity states in the quantum spin Hall phase in graphene

Two-dimensional insulators with time-reversal symmetry can have two topologically different phases, the quantum spin Hall and the normal phase. The former is revealed by the existence of conducting edge states that are topologically protected. Here we show that the reaction to impurity, in bulk, is radically different in the two phases and can be used as a marker for the topological phase. Within the context of the Kane-Mele model for graphene, we find that strictly normalizable in-gap impurity states only occur in the quantum spin Hall phase and carry a dissipationless current whose chirality is determined by the spin and pseudospin of the residing electron.

Quantum Hall effect in gapped graphene heterojunctions

We model the quantum Hall effect in heterostructures made of two gapped graphene stripes with different gaps, Δ1 and Δ2. We consider two main situations, Δ1=0,Δ2≠0, and Δ1=−Δ2. They are different in a fundamental aspect: only the latter features kink states that, when intervalley coupling is absent, are protected against backscattering. We compute the two-terminal conductance of heterostructures with channel length up to 430 nm, in two transport configurations, parallel and perpendicular to the interface. By studying the effect of disorder on the transport along the boundary, we quantify the robustness of kink states with respect to backscattering. Transport perpendicular to the boundary shows how interface states open a backscattering channel for the conducting edge states, spoiling the perfect conductance quantization featured by the homogeneously gapped graphene Hall bars. Our results can be relevant for the study of graphene deposited on hexagonal boron-nitride, as well as to model graphene with an interaction-driven gapped phase with two equivalent phases separated by a domain wall.

Question answering and multi-search engines in geo-temporal information retrieval

In this paper we present a complete system for the treatment of both geographical and temporal dimensions in text and its application to information retrieval. This system has been evaluated in both the GeoTime task of the 8th and 9th NTCIR workshop in the years 2010 and 2011 respectively, making it possible to compare the system to contemporary approaches to the topic. In order to participate in this task we have added the temporal dimension to our GIR system. The system proposed here has a modular architecture in order to add or modify features. In the development of this system, we have followed a QA-based approach as well as multi-search engines to improve the system performance.

Multi-objective adaptive evolutionary strategy for tuning compilations

Tuning compilations is the process of adjusting the values of a compiler options to improve some features of the final application. In this paper, a strategy based on the use of a genetic algorithm and a multi-objective scheme is proposed to deal with this task. Unlike previous works, we try to take advantage of the knowledge of this domain to provide a problem-specific genetic operation that improves both the speed of convergence and the quality of the results. The evaluation of the strategy is carried out by means of a case of study aimed to improve the performance of the well-known web server Apache. Experimental results show that a 7.5% of overall improvement can be achieved. Furthermore, the adaptive approach has shown an ability to markedly speed-up the convergence of the original strategy.

Consequences of Kondo exchange on quantum spins

When individual quantum spins are placed in close proximity to conducting substrates, the localized spin is coupled to the nearby itinerant conduction electrons via Kondo exchange. In the strong coupling limit this can result in the Kondo effect — the formation of a correlated, many body singlet state — and a resulting renormalization of the density of states near the Fermi energy. However, even when Kondo screening does not occur, Kondo exchange can give rise to a wide variety of other phenomena. In addition to the well known renormalization of the g factor and the finite spin decoherence and relaxation times, Kondo exchange has recently been found to give rise to a newly discovered effect: the renormalization of the single ion magnetic anisotropy. Here we put these apparently different phenomena on equal footing by treating the effect of Kondo exchange perturbatively. In this formalism, the central quantity is ρJ, the product of the density of states at the Fermi energy ρ and the Kondo exchange constant J. We show that perturbation theory correctly describes the experimentally observed exchange induced shifts of the single spin excitation energies, demonstrating that Kondo exchange can be used to tune the effective magnetic anisotropy of a single spin.

Tuning compilations by multi-objective optimization: Application to Apache web server

Modern compilers present a great and ever increasing number of options which can modify the features and behavior of a compiled program. Many of these options are often wasted due to the required comprehensive knowledge about both the underlying architecture and the internal processes of the compiler. In this context, it is usual, not having a single design goal but a more complex set of objectives. In addition, the dependencies between different goals are difficult to be a priori inferred. This paper proposes a strategy for tuning the compilation of any given application. This is accomplished by using an automatic variation of the compilation options by means of multi-objective optimization and evolutionary computation commanded by the NSGA-II algorithm. This allows finding compilation options that simultaneously optimize different objectives. The advantages of our proposal are illustrated by means of a case study based on the well-known Apache web server. Our strategy has demonstrated an ability to find improvements up to 7.5% and up to 27% in context switches and L2 cache misses, respectively, and also discovers the most important bottlenecks involved in the application performance.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

Quantum spin Hall phase in multilayer graphene

The so-called quantum spin Hall phase is a topologically nontrivial insulating phase that is predicted to appear in graphene and graphenelike systems. In this paper we address the question of whether this topological property persists in multilayered systems. We consider two situations: purely multilayer graphene and heterostructures where graphene is encapsulated by trivial insulators with a strong spin-orbit coupling. We use a four-orbital tight-binding model that includes full atomic spin-orbit coupling and we calculate the Z2 topological invariant of the bulk states as well as the edge states of semi-infinite crystals with armchair termination. For homogeneous multilayers we find that even when the spin-orbit interaction opens a gap for all possible stackings, only those with an odd number of layers host gapless edge states while those with an even number of layers are trivial insulators. For heterostructures where graphene is encapsulated by trivial insulators, it turns out that interlayer coupling is able to induce a topological gap whose size is controlled by the spin-orbit coupling of the encapsulating materials, indicating that the quantum spin Hall phase can be induced by proximity to trivial insulators.

Quantum fluctuations stabilize skyrmion textures

We study the quantum spin waves associated to skyrmion textures. We show that the zero-point energy associated to the quantum spin fluctuations of a noncollinear spin texture produce Casimir-like magnetic fields. We study the effect of these Casimir fields on the topologically protected noncollinear spin textures known as skyrmions. In a Heisenberg model with Dzyalonshinkii-Moriya interactions, chosen so the classical ground state displays skyrmion textures, we calculate the spin-wave spectrum, using the Holstein-Primakoff approximation, and the associated zero-point energy, to the lowest order in the spin-wave expansion. Our calculations are done both for the single-skyrmion case, for which we obtain a discrete set of skyrmion bound states, as well as for the skyrmion crystal, for which the resulting spectrum gives the spin-wave bands. In both cases, our calculations show that the Casimir magnetic field contributes up to 10% of the total Zeeman energy necessary to delete the skyrmion texture with an applied field.

FPGA implementation of a multi-population PBIL algorithm

Evolutionary-based algorithms play an important role in finding solutions to many problems that are not solved by classical methods, and particularly so for those cases where solutions lie within extreme non-convex multidimensional spaces. The intrinsic parallel structure of evolutionary algorithms are amenable to the simultaneous testing of multiple solutions; this has proved essential to the circumvention of local optima, and such robustness comes with high computational overhead, though custom digital processor use may reduce this cost. This paper presents a new implementation of an old, and almost forgotten, evolutionary algorithm: the population-based incremental learning method. We show that the structure of this algorithm is well suited to implementation within programmable logic, as compared with contemporary genetic algorithms. Further, the inherent concurrency of our FPGA implementation facilitates the integration and testing of micro-populations.