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

Sustainable Sources of Biomass for Bioremediation of Heavy Metals in Waste Water Derived from Coal-Fired Power Generation

Biosorption of heavy metals using dried algal biomass has been extensively described but rarely implemented. We contend this is because available algal biomass is a valuable product with a ready market. Therefore, we considered an alternative and practical approach to algal bioremediation in which algae were cultured directly in the waste water stream. We cultured three species of algae with and without nutrient addition in water that was contaminated with heavy metals from an Ash Dam associated with coal-fired power generation and tested metal uptake and bioremediation potential. All species achieved high concentrations of heavy metals (to 8% dry mass). Two key elements, V and As, reached concentrations in the biomass of 1543 mg.kg−1 DW and 137 mg.kg−1 DW. Growth rates were reduced by more than half in neat Ash Dam water than when nutrients were supplied in excess. Growth rate and bioconcentration were positively correlated for most elements, but some elements (e.g. Cd, Zn) were concentrated more when growth rates were lower, indicating the potential to tailor bioremediation depending on the pollutant. The cosmopolitan nature of the macroalgae studied, and their ability to grow and concentrate a suite of heavy metals from industrial wastes, highlights a clear benefit in the practical application of waste water bioremediation

Why do we treat adolescent idiopathic scoliosis? What we want to obtain and to avoid for our patients. SOSORT 2005 Consensus paper

BACKGROUND: Medicine is a scientific art: once science is not clear, choices are made according to individual and collective beliefs that should be better understood. This is particularly true in a field like adolescent idiopathic scoliosis, where currently does not exist definitive scientific evidence on the efficacy either of conservative or of surgical treatments. AIM OF THE STUDY: To verify the philosophical choices on the final outcome of a group of people believing and engaged in a conservative treatment of idiopathic scoliosis. METHODS: We performed a multifaceted study that included a bibliometric analysis, a questionnaire, and a careful Consensus reaching procedure between experts in the conservative treatment of scoliosis (SOSORT members). RESULTS: The Consensus reaching procedure has shown to be useful: answers changed in a statistically significant way, and 9 new outcome criteria were included. The most important final outcomes were considered Aesthetics (100%), Quality of life and Disability (more than 90%), while more than 80% of preferences went to Back Pain, Psychological well-being, Progression in adulthood, Breathing function, Scoliosis Cobb degrees (radiographic lateral flexion), Needs of further treatments in adulthood. DISCUSSION: In the literature prevail outcome criteria driven by the contingent treatment needs or the possibility to have measurement systems (even if it seems that usual clinical and radiographic methods are given much more importance than more complex Disability or Quality of Life instruments). SOSORT members give importance to a wide range of outcome criteria, in which clinical and radiographic issues have the lowest importance. CONCLUSION: We treat our patients for what they need for their future (Breathing function, Needs of further treatments in adulthood, Progression in adulthood), and their present too (Aesthetics, Disability, Quality of life). Technical matters, such as rib hump or radiographic lateral alignment and rotation, but not lateral flexion, are secondary outcomes and only instrumental to previously reported primary outcomes. We advocate a multidimensional, comprehensive evaluation of scoliosis patients, to gather all necessary data for a complete therapeutic approach, that goes beyond x-rays to reach the person and the family

Automated Discovery of Food Webs from Ecological Data Using Logic-Based Machine Learning

Networks of trophic links (food webs) are used to describe and understand mechanistic routes for translocation of energy (biomass) between species. However, a relatively low proportion of ecosystems have been studied using food web approaches due to difficulties in making observations on large numbers of species. In this paper we demonstrate that Machine Learning of food webs, using a logic-based approach called A/ILP, can generate plausible and testable food webs from field sample data. Our example data come from a national-scale Vortis suction sampling of invertebrates from arable fields in Great Britain. We found that 45 invertebrate species or taxa, representing approximately 25% of the sample and about 74% of the invertebrate individuals included in the learning, were hypothesized to be linked. As might be expected, detritivore Collembola were consistently the most important prey. Generalist and omnivorous carabid beetles were hypothesized to be the dominant predators of the system. We were, however, surprised by the importance of carabid larvae suggested by the machine learning as predators of a wide variety of prey. High probability links were hypothesized for widespread, potentially destabilizing, intra-guild predation; predictions that could be experimentally tested. Many of the high probability links in the model have already been observed or suggested for this system, supporting our contention that A/ILP learning can produce plausible food webs from sample data, independent of our preconceptions about “who eats whom.” Well-characterised links in the literature correspond with links ascribed with high probability through A/ILP. We believe that this very general Machine Learning approach has great power and could be used to extend and test our current theories of agricultural ecosystem dynamics and function. In particular, we believe it could be used to support the development of a wider theory of ecosystem responses to environmental change

α1A-Adrenergic Receptor Induces Activation of Extracellular Signal-Regulated Kinase 1/2 through Endocytic Pathway

G protein-coupled receptors (GPCRs) activate mitogen-activated protein kinases through a number of distinct pathways in cells. Increasing evidence has suggested that endosomal signaling has an important role in receptor signal transduction. Here we investigated the involvement of endocytosis in α1A-adrenergic receptor (α1A-AR)-induced activation of extracellular signal-regulated kinase 1/2 (ERK1/2). Agonist-mediated endocytic traffic of α1A-AR was assessed by real-time imaging of living, stably transfected human embryonic kidney 293A cells (HEK-293A). α1A-AR was internalized dynamically in cells with agonist stimulation, and actin filaments regulated the initial trafficking of α1A-AR. α1A-AR-induced activation of ERK1/2 but not p38 MAPK was sensitive to disruption of endocytosis, as demonstrated by 4°C chilling, dynamin mutation and treatment with cytochalasin D (actin depolymerizing agent). Activation of protein kinase C (PKC) and C-Raf by α1A-AR was not affected by 4°C chilling or cytochalasin D treatment. U73122 (a phospholipase C [PLC] inhibitor) and Ro 31–8220 (a PKC inhibitor) inhibited α1B-AR- but not α1A-AR-induced ERK1/2 activation. These data suggest that the endocytic pathway is involved in α1A-AR-induced ERK1/2 activation, which is independent of Gq/PLC/PKC signaling

Identification of Novel Inhibitors of Dietary Lipid Absorption Using Zebrafish

Pharmacological inhibition of dietary lipid absorption induces favorable changes in serum lipoprotein levels in patients that are at risk for cardiovascular disease and is considered an adjuvant or alternative treatment with HMG-CoA reductase inhibitors (statins). Here we demonstrate the feasibility of identifying novel inhibitors of intestinal lipid absorption using the zebrafish system. A pilot screen of an unbiased chemical library identified novel compounds that inhibited processing of fluorescent lipid analogues in live zebrafish larvae. Secondary assays identified those compounds suitable for testing in mammals and provided insight into mechanism of action, which for several compounds could be distinguished from ezetimibe, a drug used to inhibit cholesterol absorption in humans that broadly inhibited lipid absorption in zebrafish larvae. These findings support the utility of zebrafish screening assays to identify novel compounds that target complex physiological processes

Human papillomavirus genotype distribution and cervical squamous intraepithelial lesions among high-risk women with and without HIV-1 infection in Burkina Faso

Human papillomavirus (HPV) infection and cervical squamous intraepithelial lesions (SILs) were studied in 379 high-risk women. Human papillomavirus DNA was detected in 238 of 360 (66.1%) of the beta-globin-positive cervical samples, and 467 HPV isolates belonging to 35 types were identified. Multiple (2–7 types) HPV infections were observed in 52.9% of HPV-infected women. The most prevalent HPV types were HPV-52 (14.7%), HPV-35 (9.4%), HPV-58 (9.4%), HPV-51 (8.6%), HPV-16 (7.8%), HPV-31 (7.5%), HPV-53 (6.7%), and HPV-18 (6.4%). Human immunodeficiency virus type 1 (HIV-1) seroprevalence was 36.0%. Human papillomavirus prevalence was significantly higher in HIV-1-infected women (87 vs 54%, prevalence ratio (PR)=1.61, 95% confidence interval (CI): 1.4–1.8). High-risk HPV types (71 vs 40%, PR=1.79, 95% CI: 1.5–2.2), in particular HPV-16+18 (22 vs 9%, PR=2.35, 95% CI: 1.4–4.0), and multiple HPV infections (56 vs 23%, PR=2.45, 95% CI: 1.8–3.3) were more prevalent in HIV-1-infected women. High-grade SIL (HSIL) was identified in 3.8% of the women. Human immunodeficiency virus type 1 infection was strongly associated with presence of HSIL (adjusted odds ratio=17.0; 95% CI 2.2–134.1, P=0.007) after controlling for high-risk HPV infection and other risk factors for HSIL. Nine of 14 (63%) HSIL cases were associated with HPV-16 or HPV-18 infection, and might have been prevented by an effective HPV-16/18 vaccine

In Silico Simulation of Corticosteroids Effect on an NFkB- Dependent Physicochemical Model of Systemic Inflammation

During the onset of an inflammatory response signaling pathways are activated for "translating" extracellular signals into intracellular responses converging to the activation of nuclear factor (NF)-kB, a central transcription factor in driving the inflammatory response. An inadequate control of its transcriptional activity is associated with the culmination of a hyper-inflammatory response making it a desired therapeutic target. Predicated upon the nature of the response, a systems level analysis might provide rational leads for the development of strategies that promote the resolution of the response.A physicochemical host response model is proposed to integrate biological information in the form of kinetic rules and signaling cascades with pharmacokinetic models of drug action for the modulation of the response. The unifying hypothesis is that the response is triggered by the activation of the NFkB signaling module and corticosteroids serve as a template for assessing anti-inflammatory strategies. The proposed in silico model is evaluated through its ability to predict and modulate uncontrolled responses. The pre-exposure of the system to hypercortisolemia, i.e. 6 hr before or simultaneously with the infectious challenge "reprograms" the dynamics of the host towards a balanced inflammatory response. However, if such an intervention occurs long before the inflammatory insult a symptomatic effect is observed instead of a protective relief while a steroid infusion after inducing inflammation requires much higher drug doses.We propose a reversed engineered inflammation model that seeks to describe how the system responds to a multitude of external signals. Timing of intervention and dosage regimes appears to be key determinants for the protective or symptomatic effect of exogenous corticosteroids. Such results lie in qualitative agreement with in vivo human studies exposed both to LPS and corticosteroids under various time intervals thus improving our understanding of how interacting modules generate a behavior