Equivalence of the Parke-Taylor and the Fadin-Kuraev-Lipatov amplitudes in the high-energy limit

We give a unified description of tree-level multigluon amplitudes in the high-energy limit. We represent the Parke-Taylor amplitudes and the Fadin-Kuraev-Lipatov amplitudes in terms of color configurations that are ordered in rapidity on a two-sided plot. We show that for the helicity configurations they have in common the Parke-Taylor amplitudes and the Fadin-Kuraev-Lipatov amplitudes coincide.Comment: LaTeX, 24 pages (including 4 tar-compressed uuencoded figures

A REAL TIME MONITORING MODEL OF THE CALCIUM CARBONATE FOULING INDUCTION PERIOD BASED ON THE CONDUCTANCE TITRATION

A new method has been developed to monitor the calcium carbonate fouling induction period (CCFIP) in real time. Based on the conductance titration, this paper investigated the forming process of CCFIP by a staticdynamic combined simulation experiment unit. With the help of titration analysis (that is titrimetry), an accurate definition of CCFIP and the corresponding real time monitoring model were built up. The investigation results show that the proposed model applies not only to measure the CCFIP in real time, but also applies to an investigation of the influence of various factors on the CCFIP

Efficient Feature Selection and Multiclass Classification with Integrated Instance and Model Based Learning

Multiclass classification and feature (variable) selections are commonly encountered in many biological and medical applications. However, extending binary classification approaches to multiclass problems is not trivial. Instance-based methods such as the K nearest neighbor (KNN) can naturally extend to multiclass problems and usually perform well with unbalanced data, but suffer from the curse of dimensionality. Their performance is degraded when applied to high dimensional data. On the other hand, model-based methods such as logistic regression require the decomposition of the multiclass problem into several binary problems with one-vs.-one or one-vs.-rest schemes. Even though they can be applied to high dimensional data with L1 or Lp penalized methods, such approaches can only select independent features and the features selected with different binary problems are usually different. They also produce unbalanced classification problems with one vs. the rest scheme even if the original multiclass problem is balanced

Impact of temporal upscaling and chemical transport model horizontal resolution on reducing ozone exposure misclassification

We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error

Anharmonic force fields of perchloric acid, HClO4_4, and perchloric anhydride, Cl2_2O7_7. An extreme case of inner polarization

DFT (density functional theory) anharmonic force fields with basis sets near the Kohn-Sham limit have been obtained for perchloric acid, HClO$_4$, and perchloric anhydride, Cl$_2$O$_7$. Calculated fundamental frequencies are in very good agreement with available experimental data. Some reassignments in the vibrational spectra of Cl$_2$O$_7$ are proposed based on our calculations. HClO$_4$ and Cl$_2$O$_7$ are particularly severe examples of the `inner polarization' phenomenon. The polarization consistent basis sets pc-1 and pc-2 (as well as their augmented counterparts) should be supplemented with two (preferably three) and one (preferably two) high-exponent $d$ functions, respectively, on second-row atoms. Complete anharmonic force fields are available as electronic supporting information.Comment: J. Mol. Struct., in press (special issue); Electronic Supporting Information at http://theochem.weizmann.ac.il/web/papers/Cl2O7.htm

Scattering phases in quantum dots: an analysis based on lattice models

The properties of scattering phases in quantum dots are analyzed with the help of lattice models. We first derive the expressions relating the different scattering phases and the dot Green functions. We analyze in detail the Friedel sum rule and discuss the deviation of the phase of the transmission amplitude from the Friedel phase at the zeroes of the transmission. The occurrence of such zeroes is related to the parity of the isolated dot levels. A statistical analysis of the isolated dot wave-functions reveals the absence of significant correlations in the parity for large disorder and the appearance, for weak disorder, of certain dot states which are strongly coupled to the leads. It is shown that large differences in the coupling to the leads give rise to an anomalous charging of the dot levels. A mechanism for the phase lapse observed experimentally based on this property is discussed and illustrated with model calculations.Comment: 18 pages, 9 figures. to appear in Physical Review

A Purcell-enabled monolayer semiconductor free-space optical modulator

Dephasing and non-radiative decay processes limit the performance of a wide variety of quantum devices at room temperature. Here we illustrate a general pathway to notably reduce the detrimental impact of these undesired effects through photonic design of the device electrodes. Our design facilitates a large Purcell enhancement that speeds up competing, desired radiative decay while also enabling convenient electrical gating and charge injection functions. We demonstrate the concept with a free-space optical modulator based on an atomically thin semiconductor. By engineering the plasmonic response of a nanopatterned silver gate pad, we successfully enhance the radiative decay rate of excitons in a tungsten disulfide monolayer by one order of magnitude to create record-high modulation efficiencies for this class of materials at room temperature. We experimentally observe a 10% reflectance change as well as 3 dB signal modulation, corresponding to a 20-fold enhancement compared with modulation using a suspended monolayer in vacuum. We also illustrate how dynamic control of light fields can be achieved with designer surface patterns. This research highlights the benefits of applying radiative decay engineering as a powerful tool in creating high-performance devices that complements substantial efforts to improve the quality of materials.</p

Enhanced specificity of Bacillus metataxonomics using a tuf-targeted amplicon sequencing approach

Microbial Biotechnolog

Self-diffusion in dense granular shear flows

Diffusivity is a key quantity in describing velocity fluctuations in granular materials. These fluctuations are the basis of many thermodynamic and hydrodynamic models which aim to provide a statistical description of granular systems. We present experimental results on diffusivity in dense, granular shear in a 2D Couette geometry. We find that self-diffusivities are proportional to the local shear rate with diffusivities along the mean flow approximately twice as large as those in the perpendicular direction. The magnitude of the diffusivity is D \approx \dot\gamma a^2 where a is the particle radius. However, the gradient in shear rate, coupling to the mean flow, and drag at the moving boundary lead to particle displacements that can appear sub- or super-diffusive. In particular, diffusion appears superdiffusive along the mean flow direction due to Taylor dispersion effects and subdiffusive along the perpendicular direction due to the gradient in shear rate. The anisotropic force network leads to an additional anisotropy in the diffusivity that is a property of dense systems with no obvious analog in rapid flows. Specifically, the diffusivity is supressed along the direction of the strong force network. A simple random walk simulation reproduces the key features of the data, such as the apparent superdiffusive and subdiffusive behavior arising from the mean flow, confirming the underlying diffusive motion. The additional anisotropy is not observed in the simulation since the strong force network is not included. Examples of correlated motion, such as transient vortices, and Levy flights are also observed. Although correlated motion creates velocity fields qualitatively different from Brownian motion and can introduce non-diffusive effects, on average the system appears simply diffusive.Comment: 13 pages, 20 figures (accepted to Phys. Rev. E