A global method for coupling transport with chemistry in heterogeneous porous media

Modeling reactive transport in porous media, using a local chemical equilibrium assumption, leads to a system of advection-diffusion PDE's coupled with algebraic equations. When solving this coupled system, the algebraic equations have to be solved at each grid point for each chemical species and at each time step. This leads to a coupled non-linear system. In this paper a global solution approach that enables to keep the software codes for transport and chemistry distinct is proposed. The method applies the Newton-Krylov framework to the formulation for reactive transport used in operator splitting. The method is formulated in terms of total mobile and total fixed concentrations and uses the chemical solver as a black box, as it only requires that on be able to solve chemical equilibrium problems (and compute derivatives), without having to know the solution method. An additional advantage of the Newton-Krylov method is that the Jacobian is only needed as an operator in a Jacobian matrix times vector product. The proposed method is tested on the MoMaS reactive transport benchmark.Comment: Computational Geosciences (2009) http://www.springerlink.com/content/933p55085742m203/?p=db14bb8c399b49979ba8389a3cae1b0f&pi=1

Do Dispersing Monkeys Follow Kin? Evidence from Gray-cheeked Mangabeys (Lophocebus albigena)

Among social vertebrates, immigrants may incur a substantial fitness cost when they attempt to join a new group. Dispersers could reduce that cost, or increase their probability of mating via coalition formation, by immigrating into groups containing first- or second-degree relatives. We here examine whether dispersing males tend to move into groups containing fathers or brothers in gray-cheeked mangabeys (Lophocebus albigena) in Kibale National Park, Uganda. We sampled blood from 21 subadult and adult male mangabeys in 7 social groups and genotyped them at 17 microsatellite loci. Twelve genotyped males dispersed to groups containing other genotyped adult males during the study; in only 1 case did the group contain a probable male relative. Contrary to the prediction that dispersing males would follow kin, relatively few adult male dyads were likely first- or second-degree relatives; opportunities for kin-biased dispersal by mangabeys appear to be rare. During 4 yr of observation, adult brothers shared a group only once, and for only 6 wk. Mean relatedness among adult males sharing a group was lower than that among males in different groups. Randomization tests indicate that closely related males share groups no more often than expected by chance, although these tests had limited power. We suggest that the demographic conditions that allow kin-biased dispersal to evolve do not occur in mangabeys, may be unusual among primates, and are worth further attention

WNP: A Novel Algorithm for Gene Products Annotation from Weighted Functional Networks

Predicting the biological function of all the genes of an organism is one of the fundamental goals of computational system biology. In the last decade, high-throughput experimental methods for studying the functional interactions between gene products (GPs) have been combined with computational approaches based on Bayesian networks for data integration. The result of these computational approaches is an interaction network with weighted links representing connectivity likelihood between two functionally related GPs. The weighted network generated by these computational approaches can be used to predict annotations for functionally uncharacterized GPs. Here we introduce Weighted Network Predictor (WNP), a novel algorithm for function prediction of biologically uncharacterized GPs. Tests conducted on simulated data show that WNP outperforms other 5 state-of-the-art methods in terms of both specificity and sensitivity and that it is able to better exploit and propagate the functional and topological information of the network. We apply our method to Saccharomyces cerevisiae yeast and Arabidopsis thaliana networks and we predict Gene Ontology function for about 500 and 10000 uncharacterized GPs respectively

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Environmental and genetic influences on early attachment

Attachment theory predicts and subsequent empirical research has amply demonstrated that individual variations in patterns of early attachment behaviour are primarily influenced by differences in sensitive responsiveness of caregivers. However, meta-analyses have shown that parenting behaviour accounts for about one third of the variance in attachment security or disorganisation. The exclusively environmental explanation has been challenged by results demonstrating some, albeit inconclusive, evidence of the effect of infant temperament. In this paper, after reviewing briefly the well-demonstrated familial and wider environmental influences, the evidence is reviewed for genetic and gene-environment interaction effects on developing early attachment relationships. Studies investigating the interaction of genes of monoamine neurotransmission with parenting environment in the course of early relationship development suggest that children's differential susceptibility to the rearing environment depends partly on genetic differences. In addition to the overview of environmental and genetic contributions to infant attachment, and especially to disorganised attachment relevant to mental health issues, the few existing studies of gene-attachment interaction effects on development of childhood behavioural problems are also reviewed. A short account of the most important methodological problems to be overcome in molecular genetic studies of psychological and psychiatric phenotypes is also given. Finally, animal research focusing on brain-structural aspects related to early care and the new, conceptually important direction of studying environmental programming of early development through epigenetic modification of gene functioning is examined in brief

The pedunculopontine tegmental nucleus and the nucleus basalis magnocellularis: Do both have a role in sustained attention?

It is well established that nucleus basalis magnocellularis (NbM) lesions impair performance on tests of sustained attention. Previous work from this laboratory has also demonstrated that pedunculopontine tegmental nucleus (PPTg) lesioned rats make more omissions on a test of sustained attention, suggesting that it might also play a role in mediating this function. However, the results of the PPTg study were open to alternative interpretation. We aimed to resolve this by conducting a detailed analysis of the effects of damage to each brain region in the same sustained attention task used in our previous work. Rats were trained in the task before surgery and post-surgical testing examined performance in response to unpredictable light signals of 1500 ms and 4000 ms duration. Data for PPTg lesioned rats were compared to control rats, and rats with 192 IgG saporin infusions centred on the NbM. In addition to operant data, video data of rats' performance during the task were also analysed

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment