8 research outputs found
063 A single pre-hospital enoxaparine protocole for all STEMI admitted to ICU: One year experience and one year follow-up in Haut LĂ©vĂŞque cardiological hospital
Recommended from our members
On flames established with air jet in cross flow of fuel-rich combustion products
Advances in combustor technologies are driving aircraft gas turbine engines to operate at higher pressures, temperatures and equivalence ratios. A viable approach for protecting the combustor from the high-temperature environment is to inject air through the holes drilled on the surfaces. However, it is possible that the air intended for cooling purposes may react with fuel-rich combustion products and may increase heat flux. Air Force Research Laboratory (AFRL) has developed an experimental rig for studying the flames formed between the injected cold air and the cross flow of combustion products. Laser-based OH measurements revealed an upstream shift for the flames when the air injection velocity was increased and downstream shift when the fuel content in the cross flow was increased. As conventional understanding of the flame stability does not explain such shifts in flame anchoring location, a time-dependent, detailed-chemistry computational-fluid-dynamics model is used for identifying the mechanisms that are responsible. Combustion of propane fuel with air is modeled using a chemical-kinetics mechanism involving 52 species and 544 reactions. Calculations reveled that the flames in the film-cooling experiment are formed through autoignition process. Simulations have reproduced the various flame characteristics observed in the experiments. Numerical results are used for explaining the non-intuitive shifts in flame anchoring location to the changes in blowing ratio and equivalence ratio. The higher diffusive mass transfer rate of hydrogen in comparison to the local heat transport enhances H₂–O₂ mixing compared to thermal dissipation rate, which, in turn, affects the autoignition process. While increasing the blowing ratio abates the differences resulting from non-equal mass and heat transport rates, higher concentrations of hydrogen in the fuel-rich cross flows accelerate those differences.KEYWORDS: Autoignition, Diffusion flame, Film-cooling, Preferential diffusion, Jet-in-cross-flowThis is the publisher’s final pdf. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/fue
Impact of an Upstream Film-Cooling Row on Mitigation of Secondary Combustion in a Fuel Rich Environment
Recommended from our members
Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction
Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community
Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction
Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community
Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction
Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community