Optical excitation thermography for twill / plain weaves and stitched fabric dry carbon fibre preform inspection

Carbon fibres have become the natural choice as reinforcements for polymer composite materials (PMCs). The non-destructive inspection of dry carbon fibre preforms has the potential to increase the reproducibility and reduce the cost of PMC manufacturing, by identifying defects in dry multilayer preforms prior to resin injection. However, use of optical excitation thermography for inspecting dry carbon fibre preforms that constitute the structural reinforcement precursor in the manufacturing of PMCs is poorly documented in the open literature. In this work, optical excitation thermography was used for inspecting six dry multilayer carbon fibre preforms featuring different textile structures, thicknesses and defects, for the first time. Advanced image processing techniques were used in processing the thermographic data for comparative purposes. In particular, partial least square thermography, as a recently proposed technique, was studied in detail. Finally, the performance of different thermography techniques was analysed in terms of: 1) summarizing the capabilities of image diagnosis/processing techniques by signal-to-noise ratio analysis, and 2) identifying the monitoring modalities most suitable to industrial manufacturing

Meta-All: a system for managing metabolic pathway information

BACKGROUND: Many attempts are being made to understand biological subjects at a systems level. A major resource for these approaches are biological databases, storing manifold information about DNA, RNA and protein sequences including their functional and structural motifs, molecular markers, mRNA expression levels, metabolite concentrations, protein-protein interactions, phenotypic traits or taxonomic relationships. The use of these databases is often hampered by the fact that they are designed for special application areas and thus lack universality. Databases on metabolic pathways, which provide an increasingly important foundation for many analyses of biochemical processes at a systems level, are no exception from the rule. Data stored in central databases such as KEGG, BRENDA or SABIO-RK is often limited to read-only access. If experimentalists want to store their own data, possibly still under investigation, there are two possibilities. They can either develop their own information system for managing that own data, which is very time-consuming and costly, or they can try to store their data in existing systems, which is often restricted. Hence, an out-of-the-box information system for managing metabolic pathway data is needed. RESULTS: We have designed META-ALL, an information system that allows the management of metabolic pathways, including reaction kinetics, detailed locations, environmental factors and taxonomic information. Data can be stored together with quality tags and in different parallel versions. META-ALL uses Oracle DBMS and Oracle Application Express. We provide the META-ALL information system for download and use. In this paper, we describe the database structure and give information about the tools for submitting and accessing the data. As a first application of META-ALL, we show how the information contained in a detailed kinetic model can be stored and accessed. CONCLUSION: META-ALL is a system for managing information about metabolic pathways. It facilitates the handling of pathway-related data and is designed to help biochemists and molecular biologists in their daily research. It is available on the Web at and can be downloaded free of charge and installed locally

Cognitive behavioural therapy in elderly type 2 diabetes patients with minor depression or mild major depression: study protocol of a randomized controlled trial (MIND-DIA)

<p>Abstract</p> <p>Background</p> <p>The global prevalence of diabetes among adults will be 6.4% in 2010 and will increase to 7.7% by 2030. Diabetes doubles the odds of depression, and 9% of patients with diabetes are affected by depressive disorders. When subclinical depression is included, the proportion of patients who have clinically relevant depressive symptoms increases to 26%. In patients aged over 65 years, the interaction of diabetes and depression has predicted increased mortality, complications, disability, and earlier occurrence of all of these adverse outcomes. These deleterious effects were observed even in minor depression, where the risk of mortality within 7 years was 4.9 times higher compared with diabetes patients who did not have depressive symptoms. In this paper we describe the design and methods of the Minor Depression and Diabetes trial, a clinical trial within the 'Competence Network for Diabetes mellitus', which is funded by the German Federal Ministry of Education and Research.</p> <p>Methods/Design</p> <p>Patients' inclusion criteria are: Type 2 diabetes mellitus, 65 to 85 years of age, 3 to 6 depressive symptoms (minor depression or mild major depression). Our aim is to compare the efficacy of diabetes-specific cognitive behavioural therapy adapted for the elderly vs. intensified treatment as usual vs. a guided self-help intervention regarding improvement of health related quality of life as the primary outcome. The trial will be conducted as a multicentre, open, observer-blinded, parallel group (3 groups) randomized controlled trial. Patients will be randomized to one of the three treatment conditions. After 12 weeks of open-label therapy in all treatment conditions, both group interventions will be reduced to one session per month during the one-year long-term phase of the trial. At the one-year follow-up, all groups will be re-examined regarding the primary and secondary parameters, for example reduction of depressive symptoms, prevention of moderate/severe major depression, improvement of glycaemic control, mortality, and cost effectiveness. Depending on additional funding, the sample will be continuously observed as a prospective cohort; the primary outcome will be changed to mortality for all subsequent follow-up measurements.</p> <p>Trial registration</p> <p>Current Controlled Trials Register (ISRCTN58007098).</p

Corrigendum to "Transverse extension of partons in the proton probed in the sea-quark range by measuring the DVCS cross section" [Phys. Lett. B 793 (2019) 188]

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Model-independent search for the presence of new physics in events including H → γγ with s \sqrt{s} = 13 TeV pp data recorded by the ATLAS detector at the LHC

Abstract A model-independent search for new physics leading to final states containing a Higgs boson, with a mass of 125.09 GeV, decaying to a pair of photons is performed with 139 fb−1 of s $$\sqrt{s}$$ = 13 TeV pp collision data recorded by the ATLAS detector at the Large Hadron Collider at CERN. This search examines 22 final states categorized by the objects that are produced in association with the Higgs boson. These objects include isolated electrons or muons, hadronically decaying τ-leptons, additional photons, missing transverse momentum, and hadronic jets, as well as jets that are tagged as containing a b-hadron. No significant excesses above Standard Model expectations are observed and limits on the production cross section at 95% confidence level are set. Detector efficiencies are reported for all 22 signal regions, which can be used to convert detector-level cross-section limits reported in this paper to particle-level cross-section constraints

The ALICE experiment at the CERN LHC

ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC which focuses on QCD, the strong-interaction sector of the Standard Model. It is designed to address the physics of strongly interacting matter and the quark-gluon plasma at extreme values of energy density and temperature in nucleus-nucleus collisions. Besides running with Pb ions, the physics programme includes collisions with lighter ions, lower energy running and dedicated proton-nucleus runs. ALICE will also take data with proton beams at the top LHC energy to collect reference data for the heavy-ion programme and to address several QCD topics for which ALICE is complementary to the other LHC detectors. The ALICE detector has been built by a collaboration including currently over 1000 physicists and engineers from 105 Institutes in 30 countries. Its overall dimensions are 161626 m3 with a total weight of approximately 10 000 t. The experiment consists of 18 different detector systems each with its own specific technology choice and design constraints, driven both by the physics requirements and the experimental conditions expected at LHC. The most stringent design constraint is to cope with the extreme particle multiplicity anticipated in central Pb-Pb collisions. The different subsystems were optimized to provide high-momentum resolution as well as excellent Particle Identification (PID) over a broad range in momentum, up to the highest multiplicities predicted for LHC. This will allow for comprehensive studies of hadrons, electrons, muons, and photons produced in the collision of heavy nuclei. Most detector systems are scheduled to be installed and ready for data taking by mid-2008 when the LHC is scheduled to start operation, with the exception of parts of the Photon Spectrometer (PHOS), Transition Radiation Detector (TRD) and Electro Magnetic Calorimeter (EMCal). These detectors will be completed for the high-luminosity ion run expected in 2010. This paper describes in detail the detector components as installed for the first data taking in the summer of 2008