23 research outputs found
A Process for the Creation of T-MATS Propulsion System Models from NPSS Data
A modular thermodynamic simulation package called the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) has been developed for the creation of dynamic simulations. The T-MATS software is designed as a plug-in for Simulink(Registered TradeMark) and allows a developer to create system simulations of thermodynamic plants (such as gas turbines) and controllers in a single tool. Creation of such simulations can be accomplished by matching data from actual systems, or by matching data from steady state models and inserting appropriate dynamics, such as the rotor and actuator dynamics for an aircraft engine. This paper summarizes the process for creating T-MATS turbo-machinery simulations using data and input files obtained from a steady state model created in the Numerical Propulsion System Simulation (NPSS). The NPSS is a thermodynamic simulation environment that is commonly used for steady state gas turbine performance analysis. Completion of all the steps involved in the process results in a good match between T-MATS and NPSS at several steady state operating points. Additionally, the T-MATS model extended to run dynamically provides the possibility of simulating and evaluating closed loop responses
Lung adenocarcinoma promotion by air pollutants
A complete understanding of how exposure to environmental substances promotes cancer formation is lacking. More than 70 years ago, tumorigenesis was proposed to occur in a two-step process: an initiating step that induces mutations in healthy cells, followed by a promoter step that triggers cancer development1. Here we propose that environmental particulate matter measuring ≤2.5 μm (PM2.5), known to be associated with lung cancer risk, promotes lung cancer by acting on cells that harbour pre-existing oncogenic mutations in healthy lung tissue. Focusing on EGFR-driven lung cancer, which is more common in never-smokers or light smokers, we found a significant association between PM2.5 levels and the incidence of lung cancer for 32,957 EGFR-driven lung cancer cases in four within-country cohorts. Functional mouse models revealed that air pollutants cause an influx of macrophages into the lung and release of interleukin-1β. This process results in a progenitor-like cell state within EGFR mutant lung alveolar type II epithelial cells that fuels tumorigenesis. Ultradeep mutational profiling of histologically normal lung tissue from 295 individuals across 3 clinical cohorts revealed oncogenic EGFR and KRAS driver mutations in 18% and 53% of healthy tissue samples, respectively. These findings collectively support a tumour-promoting role for PM2.5 air pollutants and provide impetus for public health policy initiatives to address air pollution to reduce disease burden
Social-ecological and regional adaption of agrobiodiversity management across a global set of research regions
To examine management options for biodiversity in agricultural landscapes, eight research regions were classified into social-ecological domains, using a dataset of indicators of livelihood resources, i.e., capital assets. Potential interventions for biodiversity-based agriculture were then compared among landscapes and domains. The approach combined literature review with expert judgment by researchers working in each landscape. Each landscape was described for land use, rural livelihoods and attitudes of social actors toward biodiversity and intensification of agriculture. Principal components analysis of 40 indicators of natural, human, social, financial and physical capital for the eight landscapes showed a loss of biodiversity associated with high-input agricultural intensification. High levels of natural capital (e.g. indicators of wildland biodiversity conservation and agrobiodiversity for human needs) were positively associated with indicators of human capital, including knowledge of the flora and fauna and knowledge sharing among farmers. Three social-ecological domains were identified across the eight landscapes (Tropical Agriculture-Forest Matrix, Tropical Degrading Agroecosystem, and Temperate High-Input Commodity Agriculture) using hierarchical clustering of the indicator values. Each domain shared a set of interventions for biodiversity-based agriculture and ecological intensification that could also increase food security in the impoverished landscapes. Implementation of interventions differed greatly among the landscapes, e.g. financial capital for new farming practices in the Intensive Agriculture domain vs. developing market value chains in the other domains. This exploratory study suggests that indicators of knowledge systems should receive greater emphasis in the monitoring of biodiversity and ecosystem services, and that inventories of assets at the landscape level can inform adaptive management of agrobiodiversity-based intervention