Microscopic Modeling of the Growth of Order in an Alloy: Nucleated and Continuous Ordering

We study the early-stages of ordering in $Cu_3 Au$ using a model Hamiltonian derived from the effective medium theory of cohesion in metals: an approach providing a microscopic description of interatomic interactions in alloys. Our simulations show a crossover from a nucleated growth regime to a region where the ordering does not follow any simple growth laws. This mirrors the experimental observations in $Cu_3 Au$. The kinetics of growth, obtained from the simulations, is in semi-quantitative agreement with experiments. The real-space structures observed in our simulations offer some insight into the nature of early-stage kineticsComment: 13 pages, Revtex, 3 postscript figures in a second file

Failure by Simultaneous Grain Growth, Strain Localization, and Interface Debonding in Metal Films on Polymer Substrates

In a previous paper, we have demonstrated that a microcrystalline copper film well bonded to a polymer substrate can be stretched beyond 50% without cracking. The film eventually fails through the co-evolution of necking and debonding from the substrate. Here we report much lower strains to failure (around 10%) for polymer-supported nanocrystalline metal films, whose microstructure is revealed to be unstable under mechanical loading. We find that strain localization and deformation-associated grain growth facilitate each other, resulting in an unstable deformation process. Film/substrate delamination can be found wherever strain localization occurs. We therefore propose that three concomitant mechanisms are responsible for the failure of a plastically deformable but microstructurally unstable thin metal film: strain localization at large grains, deformation-induced grain growth and film debonding from the substrate.Engineering and Applied Science

Magnetic quantum oscillations of the topological insulator surface states

We study quantum oscillations of the magnetization in Bi$_{2}$Se$_{3}$(111) surface system in the presence of a perpendicular magnetic field. The combined spin-chiral Dirac cone and Landau quantization produce profound effects on the magnetization properties that are fundamentally different from those in the conventional semiconductor two-dimensional electron gas. In particular, we show that the oscillating center in the magnetization chooses to pick up positive or negative values depending on whether the zero-mode Landau level is occupied or empty. An intuitive analysis of these new features is given and the subsequent effects on the magnetic susceptibility and Hall conductance are also discussed.Comment: 5.5 PRB pages, 5 figure

Magnetic Resonance Spectroscopy Quantification Aided by Deep Estimations of Imperfection Factors and Macromolecular Signal

Objective: Magnetic Resonance Spectroscopy (MRS) is an important technique for biomedical detection. However, it is challenging to accurately quantify metabolites with proton MRS due to serious overlaps of metabolite signals, imperfections because of non-ideal acquisition conditions, and interference with strong background signals mainly from macromolecules. The most popular method, LCModel, adopts complicated non-linear least square to quantify metabolites and addresses these problems by designing empirical priors such as basis-sets, imperfection factors. However, when the signal-to-noise ratio of MRS signal is low, the solution may have large deviation. Methods: Linear Least Squares (LLS) is integrated with deep learning to reduce the complexity of solving this overall quantification. First, a neural network is designed to explicitly predict the imperfection factors and the overall signal from macromolecules. Then, metabolite quantification is solved analytically with the introduced LLS. In our Quantification Network (QNet), LLS takes part in the backpropagation of network training, which allows the feedback of the quantification error into metabolite spectrum estimation. This scheme greatly improves the generalization to metabolite concentrations unseen for training compared to the end-to-end deep learning method. Results: Experiments show that compared with LCModel, the proposed QNet, has smaller quantification errors for simulated data, and presents more stable quantification for 20 healthy in vivo data at a wide range of signal-to-noise ratio. QNet also outperforms other end-to-end deep learning methods. Conclusion: This study provides an intelligent, reliable and robust MRS quantification. Significance: QNet is the first LLS quantification aided by deep learning

Dynamics of Ordering in Alloys with Modulated Phases

This paper presents a theoretical model for studying the dynamics of ordering in alloys which exhibit modulated phases. The model is different from the standard time-dependent Ginzburg-Landau description of the evolution of a non-conserved order parameter and resembles the Swift-Hohenberg model. The early-stage growth kinetics is analyzed and compared to the Cahn-Hilliard theory of continuous ordering. The effects of non-linearities on the growth kinetics are discussed qualitatively and it is shown that the presence of an underlying elastic lattice introduces qualitatively new effects. A lattice Hamiltonian capable of describing these effects and suitable for carrying out simulations of the growth kinetics is also constructed.Comment: 18 pages, 3 figures (postscript files appended), Brandeis-BC9

A Role for a Dioxygenase in Auxin Metabolism and Reproductive Development in Rice

SummaryIndole-3-acetic acid (IAA), the natural auxin in plants, regulates many aspects of plant growth and development. Extensive analyses have elucidated the components of auxin biosynthesis, transport, and signaling, but the physiological roles and molecular mechanisms of auxin degradation remain elusive. Here, we demonstrate that the dioxygenase for auxin oxidation (DAO) gene, encoding a putative 2-oxoglutarate-dependent-Fe (II) dioxygenase, is essential for anther dehiscence, pollen fertility, and seed initiation in rice. Rice mutant lines lacking a functional DAO display increased levels of free IAA in anthers and ovaries. Furthermore, exogenous application of IAA or overexpression of the auxin biosynthesis gene OsYUCCA1 phenocopies the dao mutants. We show that recombinant DAO converts the active IAA into biologically inactive 2-oxoindole-3-acetic acid (OxIAA) in vitro. Collectively, these data support a key role of DAO in auxin catabolism and maintenance of auxin homeostasis central to plant reproductive development

Reduction of structural impacts and distinction of photosynthetic pathways in a global estimation of GPP from space-borne solar-induced chlorophyll fluorescence

Quantifying global photosynthesis remains a challenge due to a lack of accurate remote sensing proxies. Solar-induced chlorophyll fluorescence (SIF) has been shown to be a good indicator of photosynthetic activity across various spatial scales. However, a global and spatially challenging estimate of terrestrial gross primary production (GPP) based on satellite SIF remains unresolved due to the confounding effects of species-specific physical and physiological traits and external factors, such as canopy structure or photosynthetic pathway (C-3 or C-4). Here we analyze an ensemble of far-red SIF data from OCO-2 satellite and ground observations at multiple sites, using the spectral invariant theory to reduce the effects of canopy structure and to retrieve a structure-corrected total canopy SIF emission (SIFtotal). We find that the relationships between observed canopy-leaving SIF and ecosystem GPP vary significantly among biomes. In contrast, the relationships between SIFtotal and GPP converge around two unique models, one for C-3 and one for C-4 plants. We show that the two single empirical models can be used to globally scale satellite SIF observations to terrestrial GPP. We obtain an independent estimate of global terrestrial GPP of 129.56 +/- 6.54 PgC/year for the 2015-2017 period, which is consistent with the state-of-the-art data- and process-oriented models. The new GPP product shows improved sensitivity to previously undetected 'hotspots' of productivity, being able to resolve the double-peak in GPP due to rotational cropping systems. We suggest that the direct scheme to estimate GPP presented here, which is based on satellite SIF, may open up new possibilities to resolve the dynamics of global terrestrial GPP across space and time.Peer reviewe

Increased Migration of Monocytes in Essential Hypertension Is Associated with Increased Transient Receptor Potential Channel Canonical Type 3 Channels

Increased transient receptor potential canonical type 3 (TRPC3) channels have been observed in patients with essential hypertension. In the present study we tested the hypothesis that increased monocyte migration is associated with increased TRPC3 expression. Monocyte migration assay was performed in a microchemotaxis chamber using chemoattractants formylated peptide Met-Leu-Phe (fMLP) and tumor necrosis factor-α (TNF-α). Proteins were identified by immunoblotting and quantitative in-cell Western assay. The effects of TRP channel-inhibitor 2–aminoethoxydiphenylborane (2-APB) and small interfering RNA knockdown of TRPC3 were investigated. We observed an increased fMLP-induced migration of monocytes from hypertensive patients compared with normotensive control subjects (246±14% vs 151±10%). The TNF-α-induced migration of monocytes in patients with essential hypertension was also significantly increased compared to normotensive control subjects (221±20% vs 138±18%). In the presence of 2-APB or after siRNA knockdown of TRPC3 the fMLP-induced monocyte migration was significantly blocked. The fMLP-induced changes of cytosolic calcium were significantly increased in monocytes from hypertensive patients compared to normotensive control subjects. The fMLP-induced monocyte migration was significantly reduced in the presence of inhibitors of tyrosine kinase and phosphoinositide 3-kinase. We conclude that increased monocyte migration in patients with essential hypertension is associated with increased TRPC3 channels

Neutrino Physics with JUNO

The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purposeunderground liquid scintillator detector, was proposed with the determinationof the neutrino mass hierarchy as a primary physics goal. It is also capable ofobserving neutrinos from terrestrial and extra-terrestrial sources, includingsupernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos,atmospheric neutrinos, solar neutrinos, as well as exotic searches such asnucleon decays, dark matter, sterile neutrinos, etc. We present the physicsmotivations and the anticipated performance of the JUNO detector for variousproposed measurements. By detecting reactor antineutrinos from two power plantsat 53-km distance, JUNO will determine the neutrino mass hierarchy at a 3-4sigma significance with six years of running. The measurement of antineutrinospectrum will also lead to the precise determination of three out of the sixoscillation parameters to an accuracy of better than 1\%. Neutrino burst from atypical core-collapse supernova at 10 kpc would lead to ~5000inverse-beta-decay events and ~2000 all-flavor neutrino-proton elasticscattering events in JUNO. Detection of DSNB would provide valuable informationon the cosmic star-formation rate and the average core-collapsed neutrinoenergy spectrum. Geo-neutrinos can be detected in JUNO with a rate of ~400events per year, significantly improving the statistics of existing geoneutrinosamples. The JUNO detector is sensitive to several exotic searches, e.g. protondecay via the $p\to K^++\bar\nu$ decay channel. The JUNO detector will providea unique facility to address many outstanding crucial questions in particle andastrophysics. It holds the great potential for further advancing our quest tounderstanding the fundamental properties of neutrinos, one of the buildingblocks of our Universe