Performance tests of signature extension algorithms

Comparative tests were performed on seven signature extension algorithms to evaluate their effectiveness in correcting for changes in atmospheric haze and sun angle in a LANDSAT scene. Four of the algorithms were cluster matching, and two were maximum likelihood algorithms. The seventh algorithm determined the haze level in both training and recognition segments and used a set of tables calculated from an atmospheric model to determine the affine transformation that corrects the training signatures for changes in sun angle and haze level. Three of the algorithms were tested on a simulated data set, and all of the algorithms were tested on consecutive-day data

The effects of peripheral and central high insulin on brain insulin signaling and amyloid-β in young and old APP/PS1 mice

Hyperinsulinemia is a risk factor for late-onset Alzheimer's disease (AD). In vitro experiments describe potential connections between insulin, insulin signaling, and amyloid-β (Aβ), but in vivo experiments are needed to validate these relationships under physiological conditions. First, we performed hyperinsulinemic-euglycemic clamps with concurrent hippocampal microdialysis in young, awake, behaving APP(swe)/PS1(dE9) transgenic mice. Both a postprandial and supraphysiological insulin clamp significantly increased interstitial fluid (ISF) and plasma Aβ compared with controls. We could detect no increase in brain, ISF, or CSF insulin or brain insulin signaling in response to peripheral hyperinsulinemia, despite detecting increased signaling in the muscle. Next, we delivered insulin directly into the hippocampus of young APP/PS1 mice via reverse microdialysis. Brain tissue insulin and insulin signaling was dose-dependently increased, but ISF Aβ was unchanged by central insulin administration. Finally, to determine whether peripheral and central high insulin has differential effects in the presence of significant amyloid pathology, we repeated these experiments in older APP/PS1 mice with significant amyloid plaque burden. Postprandial insulin clamps increased ISF and plasma Aβ, whereas direct delivery of insulin to the hippocampus significantly increased tissue insulin and insulin signaling, with no effect on Aβ in old mice. These results suggest that the brain is still responsive to insulin in the presence of amyloid pathology but increased insulin signaling does not acutely modulate Aβ in vivo before or after the onset of amyloid pathology. Peripheral hyperinsulinemia modestly increases ISF and plasma Aβ in young and old mice, independent of neuronal insulin signaling. SIGNIFICANCE STATEMENT The transportation of insulin from blood to brain is a saturable process relevant to understanding the link between hyperinsulinemia and AD. In vitro experiments have found direct connections between high insulin and extracellular Aβ, but these mechanisms presume that peripheral high insulin elevates brain insulin significantly. We found that physiological hyperinsulinemia in awake, behaving mice does not increase CNS insulin to an appreciable level yet modestly increases extracellular Aβ. We also found that the brain of aged APP/PS1 mice was not insulin resistant, contrary to the current state of the literature. These results further elucidate the relationship between insulin, the brain, and AD and its conflicting roles as both a risk factor and potential treatment

Bosons in optical lattices - from the Mott transition to the Tonks-Girardeau gas

We present results from quantum Monte Carlo simulations of trapped bosons in optical lattices, focusing on the crossover from a gas of softcore bosons to a Tonks-Girardeau gas in a one-dimensional optical lattice. We find that depending on the quantity being measured, the behavior found in the Tonks-Girardeau regime is observed already at relatively small values of the interaction strength. A finite critical value for entering the Tonks-Girardeau regime does not exist. Furthermore, we discuss the computational efficiency of two quantum Monte Carlo methods to simulate large scale trapped bosonic systems: directed loops in stochastic series expansions and the worm algorithm.Comment: 7 pages with 9 figures;v2: improved discussion on Tonks-Girardeau ga

Cohomological Hasse principle and motivic cohomology for arithmetic schemes

In 1985 Kazuya Kato formulated a fascinating framework of conjectures which generalizes the Hasse principle for the Brauer group of a global field to the so-called cohomological Hasse principle for an arithmetic scheme. In this paper we prove the prime-to-characteristic part of the cohomological Hasse principle. We also explain its implications on finiteness of motivic cohomology and special values of zeta functions.Comment: 47 pages, final versio

Complete Genome Sequence of a thermotolerant sporogenic lactic acid bacterium, Bacillus coagulans strain 36D1

Bacillus coagulans is a ubiquitous soil bacterium that grows at 50-55 °C and pH 5.0 and ferments various sugars that constitute plant biomass to L (+)-lactic acid. The ability of this sporogenic lactic acid bacterium to grow at 50-55 °C and pH 5.0 makes this organism an attractive microbial biocatalyst for production of optically pure lactic acid at industrial scale not only from glucose derived from cellulose but also from xylose, a major constituent of hemicellulose. This bacterium is also considered as a potential probiotic. Complete genome sequence of a representative strain, B. coagulans strain 36D1, is presented and discussed

Oxygen-deficient water zones in the Baltic Sea promote uncharacterized Hg methylating microorganisms in underlying sediments

Human-induced expansion of oxygen-deficient zones can have dramatic impacts on marine systems and its resident biota. One example is the formation of the potent neurotoxic methylmercury (MeHg) that is mediated by microbial methylation of inorganic divalent Hg (Hg-II) under oxygen-deficient conditions. A negative consequence of the expansion of oxygen-deficient zones could be an increase in MeHg production due to shifts in microbial communities in favor of microorganisms methylating Hg. There is, however, limited knowledge about Hg-methylating microbes, i.e., those carrying hgc genes critical for mediating the process, from marine sediments. Here, we aim to study the presence of hgc genes and transcripts in metagenomes and metatranscriptomes from four surface sediments with contrasting concentrations of oxygen and sulfide in the Baltic Sea. We show that potential Hg methylators differed among sediments depending on redox conditions. Sediments with an oxygenated surface featured hgc-like genes and transcripts predominantly associated with uncultured Desulfobacterota (OalgD group) and Desulfobacterales (including Desulfobacula sp.) while sediments with a hypoxic-anoxic surface included hgc-carrying Verrucomicrobia, unclassified Desulfobacterales, Desulfatiglandales, and uncharacterized microbes. Our data suggest that the expansion of oxygen-deficient zones in marine systems may lead to a compositional change of Hg-methylating microbial groups in the sediments, where Hg methylators whose metabolism and biology have not yet been characterized will be promoted and expand

Human HSP70-escort protein 1 (hHep1) interacts with negatively charged lipid bilayers and cell membranes

Human Hsp70-escort protein 1 (hHep1) is a cochaperone that assists in the function and stability of mitochondrial HSPA9. Similar to HSPA9, hHep1 is located outside the mitochondria and can interact with liposomes. In this study, we further investigated the structural and thermodynamic behavior of interactions between hHep1 and negatively charged liposomes, as well as interactions with cellular membranes. Our results showed that hHep1 interacts peripherally with liposomes formed by phosphatidylserine and cardiolipin and remains partially structured, exhibiting similar affinities for both. In addition, after being added to the cell membrane, recombinant hHep1 was incorporated by cells in a dose-dependent manner. Interestingly, the association of HSPA9 with hHep1 improved the incorporation of these proteins into the lipid bilayer. These results demonstrated that hHep1 can interact with lipids also present in the plasma membrane, indicating roles for this cochaperone outside of mitochondria

Accurate ab initio spin densities

We present an approach for the calculation of spin density distributions for molecules that require very large active spaces for a qualitatively correct description of their electronic structure. Our approach is based on the density-matrix renormalization group (DMRG) algorithm to calculate the spin density matrix elements as basic quantity for the spatially resolved spin density distribution. The spin density matrix elements are directly determined from the second-quantized elementary operators optimized by the DMRG algorithm. As an analytic convergence criterion for the spin density distribution, we employ our recently developed sampling-reconstruction scheme [J. Chem. Phys. 2011, 134, 224101] to build an accurate complete-active-space configuration-interaction (CASCI) wave function from the optimized matrix product states. The spin density matrix elements can then also be determined as an expectation value employing the reconstructed wave function expansion. Furthermore, the explicit reconstruction of a CASCI-type wave function provides insights into chemically interesting features of the molecule under study such as the distribution of $\alpha$- and $\beta$-electrons in terms of Slater determinants, CI coefficients, and natural orbitals. The methodology is applied to an iron nitrosyl complex which we have identified as a challenging system for standard approaches [J. Chem. Theory Comput. 2011, 7, 2740].Comment: 37 pages, 13 figure

Discovering universal statistical laws of complex networks

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their generalisation power, which we identify with large structural variability and absence of constraints imposed by the construction scheme. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This allows, for instance, to infer global features from local ones using regression models trained on networks with high generalisation power. Our results confirm and extend previous findings regarding the synchronisation properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks with good approximation. Finally, we demonstrate on three different data sets (C. elegans' neuronal network, R. prowazekii's metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models

Hardy's inequality for functions vanishing on a part of the boundary

We develop a geometric framework for Hardy's inequality on a bounded domain when the functions do vanish only on a closed portion of the boundary.Comment: 26 pages, 2 figures, includes several improvements in Sections 6-8 allowing to relax the assumptions in the main results. Final version published at http://link.springer.com/article/10.1007%2Fs11118-015-9463-