Improvement to the Prediction of Fuel Cost Distributions Using ARIMA Model

Availability of a validated, realistic fuel cost model is a prerequisite to the development and validation of new optimization methods and control tools. This paper uses an autoregressive integrated moving average (ARIMA) model with historical fuel cost data in development of a three-step-ahead fuel cost distribution prediction. First, the data features of Form EIA-923 are explored and the natural gas fuel costs of Texas generating facilities are used to develop and validate the forecasting algorithm for the Texas example. Furthermore, the spot price associated with the natural gas hub in Texas is utilized to enhance the fuel cost prediction. The forecasted data is fit to a normal distribution and the Kullback-Leibler divergence is employed to evaluate the difference between the real fuel cost distributions and the estimated distributions. The comparative evaluation suggests the proposed forecasting algorithm is effective in general and is worth pursuing further.Comment: Accepted by IEEE PES 2018 General Meetin

Modified Poisson–Boltzmann theory for polyelectrolytes in monovalent salt solutions with finite-size ions

We present a soft-potential-enhanced Poisson–Boltzmann (SPB) theory to efficiently capture ion distributions and electrostatic potential around rodlike charged macromolecules. The SPB model is calibrated with a coarse-grained particle-based model for polyelectrolytes (PEs) in monovalent salt solutions as well as compared to a full atomistic molecular dynamics simulation with the explicit solvent. We demonstrate that our modification enables the SPB theory to accurately predict monovalent ion distributions around a rodlike PE in a wide range of ion and charge distribution conditions in the weak-coupling regime. These include excess salt concentrations up to 1M and ion sizes ranging from small ions, such as Na+ or Cl−, to softer and larger ions with a size comparable to the PE diameter. The work provides a simple way to implement an enhancement that effectively captures the influence of ion size and species into the PB theory in the context of PEs in aqueous salt solutions

Interaction between two polyelectrolytes in monovalent aqueous salt solutions

We use the recently developed soft-potential-enhanced Poisson–Boltzmann (SPB) theory to study the interaction between two parallel polyelectrolytes (PEs) in monovalent ionic solutions in the weak-coupling regime. The SPB theory is fitted to ion distributions from coarse-grained molecular dynamics (MD) simulations and benchmarked against all-atom MD modelling for poly(diallyldimethylammonium) (PDADMA). We show that the SPB theory is able to accurately capture the interactions between two PEs at distances beyond the PE radius. For PDADMA positional correlations between the charged groups lead to locally asymmetric PE charge and ion distributions. This gives rise to small deviations from the SPB prediction that appear as short-range oscillations in the potential of mean force. Our results suggest that the SPB theory can be an efficient way to model interactions in chemically specific complex PE systems. </p

Resolving Voltage–Time Dilemma Using an Atomic-Scale Lever of Subpicosecond Electron–Phonon Interaction

Nanoelectronic memory based on trapped charge need to be small and fast, but fundamentally it faces a voltage–time dilemma because the requirement of a high-energy barrier for data retention under zero/low electrical stimuli is incompatible with the demand of a low-energy barrier for fast switching under a modest programming voltage. One solution is to embed an atomic-level lever of localized electron–phonon interaction to autonomously reconfigure trap-site’s barrier in accordance to the electron-occupancy of the site. Here we demonstrate an atomically levered resistance-switching memory built on locally flexible amorphous nanometallic thin films: charge detrapping can be triggered by a mechanical force, the fastest one being a plasmonic Lorentz force induced by a nearby electron or positron bunch passing in 10^–13 s. The observation provided the first real-time evidence of an electron–phonon interaction in action, which enables nanometallic memory to turn on at a subpicosecond speed yet retain long-term memory, thus suitable for universal memory and other nanoelectron applications

Additional file 1 of Improving the diagnosis of active tuberculosis: a novel approach using magnetic particle-based chemiluminescence LAM assay

Supplementary Material

Forest plots of association between TPMT polymorphisms and AZA-induced overall ADRs (A), bone marrow toxicity (B), hepatotoxicity (C) and gastric intolerance (D).

<p>Total: total number of patients with or without ADRs. Events: number of patients with one or more mutant <i>TPMT</i> alleles (<i>TPMT</i>*3A, <i>TPMT</i>*3B and <i>TPMT</i>*3C) within the ADRs or no ADRs group.</p

Funnel plot of BMT subset.

<p>The dotted vertical line indicates the overall OR. S.E. = standard error, OR = odds ratio. Each circle represents an eligible study.</p

Flowchart describing the systematic literature search and study selection process.

<p>Flowchart describing the systematic literature search and study selection process.</p

Characteristics of 11 studies included in this meta-analysis^*.

<p>Characteristics of 11 studies included in this meta-analysis^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144234#t001fn001" target="_blank">*</a>}.</p

Forest plots of subgroup analysis according to ethnicity (A) and disease (B) in BMT subset.

<p>SLE: systematic lupus erythematosus. AIH: autoimmune hepatitis. RA: rheumatoid arthritis. Total: total number of patients with or without ADRs. Events: number of patients with one or more mutant <i>TPMT</i> alleles (<i>TPMT</i>*3A, <i>TPMT</i>*3B and <i>TPMT</i>*3C) within the ADRs or no ADRs group.</p