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Controlling molecule-surface interactions is key for chemical applications ranging from catalysis to gas sensing. We present a framework for accelerating the search for the global minimum on potential surfaces, corresponding to stable adsorbate-surface structures. We present a technique using Bayesian inference that enables us to predict converged density functional theory potential energies with fewer self-consistent field iterations. We then discuss how this technique fits in with the Bayesian Active Site Calculator, which applies Bayesian optimization to the problem. We demonstrate the performance of our framework using a hematite (Fe2O3) surface and present the adsorption sites found by our global optimization method for various simple hydrocarbons on the rutile TiO2 (110) surface. [ABSTRACT FROM AUTHOR]

BackgroundMilitary service can lead to profound changes in identity, both in servicemen's perception of themselves and in their relationship to the world, but the significance of these changes for psychopathology is unclear. We investigated whether the extent and valence of identity change was related to the degree of military trauma exposure or to post-traumatic stress disorder (PTSD) and suicide attempts. We further sought to describe the nature of such changes using qualitative analysis.MethodA total of 153 veterans in receipt of a war pension for PTSD or physical disability were identified. Interviews established retrospectively DSM-IV diagnoses of PTSD and reports of suicidal ideation or behaviour since enlistment were examined.ResultsTrauma exposure alone was unrelated to any measure of identity change. By contrast, PTSD was associated with a relationship to the world that had changed in a negative direction. It was also associated with a changed perception of self, which could be either positive or negative. After controlling for trauma exposure and PTSD, suicidal behaviours were associated with more negative perceptions of the world. These perceptions of the world included disillusionment about human nature and a more specific rejection of civilian life.ConclusionsPTSD and suicidal behaviours in veterans seem not to be associated with significantly more negative views of the self but rather with more alienation from civilian life. This has serious consequences for engaging veterans in National Health Service (NHS) mental health services and for the provision of effective treatment. [ABSTRACT FROM PUBLISHER]

Abstract: Many data analysis problems require robust tools for discerning between states or classes in the data. In this paper we consider situations in which the decision boundaries between classes are potentially non-linear and subject to “concept drift” and hence static classifiers fail. The applications for which we present results are characterized by the requirement that robust online decisions be made and by the fact that target labels may be missing, so there is very often no feedback regarding the system''s performance. The inherent non-stationarity in the data is tracked using a non-linear dynamic classifier, the parameters of which evolve under an extended Kalman filter framework, derived using a sequential Bayesian-learning paradigm. The method is extended to take into account missing and incorrectly labeled targets and to actively request target labels. The method is shown to work well in simulation as well as when applied to sequential decision problems in medical signal analysis. [Copyright &y& Elsevier]

This work evaluated the National Research Council (NRC) dairy model (2001) predictions of rumen undegradable (RUP) and degradable (RDP) protein compared with measured postruminal non-ammonia, nonmicrobial (NANMN) and microbial N flows. Models were evaluated using the root mean squared prediction error (RMSPE) as a percent of the observed mean, mean and slope biases as percentages of mean squared prediction error (MSPE), and concordance correlation coefficient (CCC). The NRC (2001) over-estimated NANMN by 18% and under-estimated microbial N by 14%. Both responses had large mean biases (19% and 20% of MSPE, respectively), and NANMN had a slope bias (22% of MSPE). The NRC NANMN estimate had high RMSPE (46% of observed mean) and low CCC (0.37); updating feed library A, B, and C protein fractions and degradation rate (Kd) estimates with newer literature only marginally improved fit. The re-fit NRC models for NANMN and microbial N had CCC of 0.89 and 0.94, respectively. When compared with a prediction of NANMN as a static mean fraction of N intake, the re-derived NRC approach did not have improved fit. A protein system of intermediate complexity was derived in an attempt to estimate NANMN with improved fit compared with the static mean NANMN model. In this system, postruminal appearance of A, B, and C protein fractions were predicted in a feed-type specific manner rather than from estimated passage and degradation rates. In a comparison to independent data achieved through cross-validation, the new protein system improved RMSPE (34 vs. 36% of observed mean) and CCC (0.42 vs. 0.30) compared with the static mean NANMN model. When the NRC microbial N equation was re-derived, the RDP term dropped from the model. Consequently, 2 new microbial protein equations were formulated, both used a saturating (increasing at a decreasing rate) form: one saturated with respect to TDN and the other saturated over increasing intakes of rumen degraded starch and NDF. Both equations expressed maximal microbial N production as a linear function of RDP intake. The function relating microbial N to intake of rumen degradable carbohydrate improved RMSPE (24 vs. 28% of the observed mean) and CCC (0.63 vs 0.30) compared with the re-derived NRC model. The newly derived equations showed modest improvements in model fit and improved capacity to account for known biological effects; however, substantial variability in NANMN and microbial N estimates remained unexplained. [ABSTRACT FROM AUTHOR]

Evaluation of ration balancing systems such as the National Research Council (NRC) Nutrient Requirements series is important for improving predictions of animal nutrient requirements and advancing feeding strategies. This work used a literature data set (n = 550) to evaluate predictions of total-tract digested neutral detergent fiber (NDF), fatty acid (FA), crude protein (CP), and nonfiber carbohydrate (NFC) estimated by the NRC (2001) dairy model. Mean biases suggested that the NRC (2001) lactating cow model overestimated true FA and CP digestibility by 26 and 7%, respectively, and under-predicted NDF digestibility by 16%. All NRC (2001) estimates had notable mean and slope biases and large root mean squared prediction error (RMSPE), and concordance (CCC) ranged from poor to good. Predicting NDF digestibility with independent equations for legumes, corn silage, other forages, and nonforage feeds improved CCC (0.85 vs. 0.76) compared with the re-derived NRC (2001) equation form (NRC equation with parameter estimates re-derived against this data set). Separate FA digestion coefficients were derived for different fat supplements (animal fats, oils, and other fat types) and for the basal diet. This equation returned improved (from 0.76 to 0.94) CCC compared with the re-derived NRC (2001) equation form. Unique CP digestibility equations were derived for forages, animal protein feeds, plant protein feeds, and other feeds, which improved CCC compared with the re-derived NRC (2001) equation form (0.74 to 0.85). New NFC digestibility coefficients were derived for grain-specific starch digestibilities, with residual organic matter assumed to be 98% digestible. A Monte Carlo cross-validation was performed to evaluate repeatability of model fit. In this procedure, data were randomly subsetted 500 times into derivation (60%) and evaluation (40%) data sets, and equations were derived using the derivation data and then evaluated against the independent evaluation data. Models derived with random study effects demonstrated poor repeatability of fit in independent evaluation. Similar equations derived without random study effects showed improved fit against independent data and little evidence of biased parameter estimates associated with failure to include study effects. The equations derived in this analysis provide interesting insight into how NDF, starch, FA, and CP digestibilities are affected by intake, feed type, and diet composition. [ABSTRACT FROM AUTHOR]

The 750-keV H+ Cockcroft-Walton at LANSCE will be replaced with a recently fabricated 4-rod Radio Frequency Quadrupole (RFQ) with injection energy of 35 keV. The existing duoplasmatron source extraction optics need to be modified to produce up to 35 mA of H+ current with an emittance <0.02 π-cm-mrad (rms, norm) for injection into the RFQ. Parts for the new source have been fabricated and assembly is in process. We will use the existing duoplasmatron source with a newly designed extraction system and low energy beam transport (LEBT) for beam injection into the RFQ. In addition to source modifications, we need a new LEBT for transport and matching into the RFQ. The LEBT uses two magnetic solenoids with enough drift space between them to accommodate diagnostics and a beam deflector. The LEBT is designed to work over a range of space-charge neutralized currents and emittances. The LEBT is optimized in the sense that it minimizes the beam size in both solenoids for a point design of a given neutralized current and emittance. Special attention has been given to estimating emittance growth due to source extraction optics and solenoid aberrations. Examples of source-to-RFQ matching and emittance growth (due to both non-linear space charge and solenoid aberrations) are presented over a range of currents and emittances about the design point. A mechanical layout drawing will be presented along with the status of the source and LEBT, design, and fabrication. [ABSTRACT FROM AUTHOR]