Manipulating the momentum state of a condensate by sequences of standing wave pulses

We analyze the effects of sequences of standing wave pulses on a Bose-Einstein condensate (BEC). Experimental observations are in good agreement with a numerical simulation based on the band structure theory in the optical lattice. We also demonstrate that a coherent control method based on such sequences of pulses is very efficient for experimentally designing specific momentum states.Comment: 6 pages; 5 figures; submitted to PR

Neutrino Emission From Direct Urca Processes in Pion Condensed Quark Matter

We study neutrino emission from direct Urca processes in pion condensed quark matter. In compact stars with high baryon density, the emission is dominated by the gapless modes of the pion condensation which leads to an enhanced emissivity. While for massless quarks the enhancement is not remarkable, the emissivity is significantly larger and the cooling of the condensed matter is considerably faster than that in normal quark matter when the mass difference between $u$- and $d$-quarks is sizable.Comment: 12 pages,6 figures, published versio

On Strong Convergence to Equilibrium for the Boltzmann Equation with Soft Potentials

The paper concerns $L^1$- convergence to equilibrium for weak solutions of the spatially homogeneous Boltzmann Equation for soft potentials (-4\le \gm<0), with and without angular cutoff. We prove the time-averaged $L^1$-convergence to equilibrium for all weak solutions whose initial data have finite entropy and finite moments up to order greater than 2+|\gm|. For the usual $L^1$-convergence we prove that the convergence rate can be controlled from below by the initial energy tails, and hence, for initial data with long energy tails, the convergence can be arbitrarily slow. We also show that under the integrable angular cutoff on the collision kernel with -1\le \gm<0, there are algebraic upper and lower bounds on the rate of $L^1$-convergence to equilibrium. Our methods of proof are based on entropy inequalities and moment estimates.Comment: This version contains a strengthened theorem 3, on rate of convergence, considerably relaxing the hypotheses on the initial data, and introducing a new method for avoiding use of poitwise lower bounds in applications of entropy production to convergence problem

A Regional GSI-Based Ensemble Kalman Filter Data Assimilation System for the Rapid Refresh Configuration: Testing at Reduced Resolution

Abstract A regional ensemble Kalman filter (EnKF) system is established for potential Rapid Refresh (RAP) operational application. The system borrows data processing and observation operators from the gridpoint statistical interpolation (GSI), and precalculates observation priors using the GSI. The ensemble square root Kalman filter (EnSRF) algorithm is used, which updates both the state vector and observation priors. All conventional observations that are used in the operational RAP GSI are assimilated. To minimize computational costs, the EnKF is run at ⅓ of the operational RAP resolution or about 40-km grid spacing, and its performance is compared to the GSI using the same datasets and resolution. Short-range (up to 18 h, the RAP forecast length) forecasts are verified against soundings, surface observations, and precipitation data. Experiments are run with 3-hourly assimilation cycles over a 9-day convectively active retrospective period from spring 2010. The EnKF performance was improved by extensive tuning, including the use of height-dependent covariance localization scales and adaptive covariance inflation. When multiple physics parameterization schemes are employed by the EnKF, forecast errors are further reduced, especially for relative humidity and temperature at the upper levels and for surface variables. The best EnKF configuration produces lower forecast errors than the parallel GSI run. Gilbert skill scores of precipitation forecasts on the 13-km RAP grid initialized from the 3-hourly EnKF analyses are consistently better than those from GSI analyses.</jats:p

Aurintricarboxylic Acid Is a Potent Inhibitor of Influenza A and B Virus Neuraminidases

Background: Influenza viruses cause serious infections that can be prevented or treated using vaccines or antiviral agents, respectively. While vaccines are effective, they have a number of limitations, and influenza strains resistant to currently available anti-influenza drugs are increasingly isolated. This necessitates the exploration of novel anti-influenza therapies. Methodology/Principal Findings: We investigated the potential of aurintricarboxylic acid (ATA), a potent inhibitor of nucleic acid processing enzymes, to protect Madin-Darby canine kidney cells from influenza infection. We found, by neutral red assay, that ATA was protective, and by RT-PCR and ELISA, respectively, confirmed that ATA reduced viral replication and release. Furthermore, while pre-treating cells with ATA failed to inhibit viral replication, pre-incubation of virus with ATA effectively reduced viral titers, suggesting that ATA may elicit its inhibitory effects by directly interacting with the virus. Electron microscopy revealed that ATA induced viral aggregation at the cell surface, prompting us to determine if ATA could inhibit neuraminidase. ATA was found to compromise the activities of virus-derived and recombinant neuraminidase. Moreover, an oseltamivir-resistant H1N1 strain with H274Y was also found to be sensitive to ATA. Finally, we observed additive protective value when infected cells were simultaneously treated with ATA and amantadine hydrochloride, an antiinfluenza drug that inhibits M2-ion channels of influenza A virus. Conclusions/Significance: Collectively, these data suggest that ATA is a potent anti-influenza agent by directly inhibiting th

A Multidimensional Connectomics- and Radiomics-Based Advanced Machine-Learning Framework to Distinguish Radiation Necrosis from True Progression in Brain Metastases

We introduce tumor connectomics, a novel MRI-based complex graph theory framework that describes the intricate network of relationships within the tumor and surrounding tissue, and combine this with multiparametric radiomics (mpRad) in a machine-learning approach to distinguish radiation necrosis (RN) from true progression (TP). Pathologically confirmed cases of RN vs. TP in brain metastases treated with SRS were included from a single institution. The region of interest was manually segmented as the single largest diameter of the T1 post-contrast (T1C) lesion plus the corresponding area of T2 FLAIR hyperintensity. There were 40 mpRad features and 6 connectomics features extracted, as well as 5 clinical and treatment factors. We developed an Integrated Radiomics Informatics System (IRIS) based on an Isomap support vector machine (IsoSVM) model to distinguish TP from RN using leave-one-out cross-validation. Class imbalance was resolved with differential misclassification weighting during model training using the IRIS. In total, 135 lesions in 110 patients were analyzed, including 43 cases (31.9%) of pathologically proven RN and 92 cases (68.1%) of TP. The top-performing connectomics features were three centrality measures of degree, betweenness, and eigenvector centralities. Combining these with the 10 top-performing mpRad features, an optimized IsoSVM model was able to produce a sensitivity of 0.87, specificity of 0.84, AUC-ROC of 0.89 (95% CI: 0.82-0.94), and AUC-PR of 0.94 (95% CI: 0.87-0.97)

Mechanistic insights into NO-H2 reaction over Pt/boron-doped graphene catalyst

This work presents a systematical experimental and density functional theory (DFT) studies to reveal the mechanism of NO reduction by H 2 reaction over platinum nanoparticles (NPs) deposited on boron-doped graphene (denoted as Pt/BG) catalyst. Both characterizations and DFT calculations identified boron (in Pt/BG) as an additional NO adsorption site other than the widely recognized Pt NPs. Moreover, BG led to a decrease of Pt NPs size in Pt/BG, which facilitated hydrogen spillover. The mathematical and physical criteria of the Langmuir-Hinshelwood dual-site kinetic model over the Pt/BG were satisfied, indicating that adsorbed NO on boron (in Pt/BG) was further activated by H-spillover. On the other hand, Pt/graphene (Pt/Gr) demonstrated a typical Langmuir-Hinshelwood single-site mechanism where Pt NPs solely served as active sites for NO adsorption. This work helps understand NO-H 2 reaction over Pt/BG and Pt/Gr catalysts in a closely mechanistic view and provides new insights into roles of active sites for improving the design of catalysts for NO abatement

Precession modulates the poleward expansion of atmospheric circulation to the Arctic Ocean

Under sustained global warming, Arctic climate is projected to become more responsive to changes in North Pacific meridional heat transport as a result of teleconnections between low and high latitudes, but the underlying mechanisms remain poorly understood. Here, we reconstruct subarctic humidity changes over the past 400 kyr to investigate the role of low-to-high latitude interactions in regulating Arctic hydroclimate. Our reconstruction is based on precipitation-driven sediment input variations in the Subarctic North Pacific (SANP), which reveal a strong precessional cycle in subarctic humidity under the relatively low eccentricity variations that dominated the past four glacial-interglacial cycles. Combined with climate model simulations, we highlight that precession drives meridional shifts in the northern rim of the North Pacific Subtropical Gyre (NPSG) and modulates the efficiency of heat and water vapor transfer to the SANP and Arctic regions. Our findings suggest that projections of a northward shift of the NPSG in response to future global warming will lead to wetter conditions in the Arctic Ocean and enhanced sea-ice loss