The role of microvesicles in systemic inflammatory signalling in acute respiratory distress syndrome

Patients with acute respiratory distress syndrome (ARDS) have an unacceptably high mortality surpassing 40%. Most patients with ARDS die from multi-organ failure rather than respiratory failure, presumably due to systemic propagation of inflammation between the lungs and peripheral organs. Numerous systemic inflammatory mediators have been identified as potential therapeutic targets for ARDS. However, few specific therapies have been successfully developed and treatment remains primarily limited to supportive care. Microvesicles (MVs) are tiny particles released from cells during cell activation and stress. MVs represent a unique form of inter-cellular communication through their ability to act as ‘biological ferries’ carrying inflammatory mediators as their cargoes in a packaged, lipid-encapsulated environment resistant to neutralisation in the systemic circulation. We hypothesised that leukocyte-derived MVs play a critical role in systemic inflammatory signalling in ARDS. Through initially focusing on periphery-to-lung signalling, we developed an in vitro bioassay of pulmonary microvascular inflammation and investigated the bioactivity of neutrophil-derived MVs. We found that inflammatory neutrophil-derived MVs induced significant acute pulmonary microvascular inflammation, in a peripheral blood mononuclear cell-dependent manner. We then focused on lung-to-periphery signalling through developing a novel human in vitro model of ventilator-induced pulmonary microvascular inflammation. We found, for the first time, that pathological cyclic stretch induced acute leukocyte activation and release of leukocyte-derived MVs. We developed methodology to separate MV subtypes from the mixed total MV population generated, and demonstrated that these stretch-induced leukocyte-derived MVs are capable of inducing remote organ endothelial injury. Finally, we investigated circulating MV profiles in plasma samples of patients with ARDS. We found significantly increased baseline neutrophil- and endothelial-derived MV levels in patients with hyperinflammatory ARDS. Our findings suggest MVs play a crucial role in the early phase of ARDS pathophysiology and could represent a paradigm shift in our understanding of systemic inflammatory signalling in ARDS.Open Acces

Experimental analysis of computer system dependability

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance

Design and Implementation of Model Predictive Control Strategies for Improved Power Plant Cycling

Design and Implementation of Model Predictive Control Strategies for Improved Power Plant Cycling Xin He With the increasing focus on renewable energy sources, traditional power plants such as coal-fired power plants will have to cycle their load to accommodate the penetration of renewables into the power grid. Significant overshooting and oscillatory performance may occur during cycling operations if classical feedback control strategies are employed for plantwide control. To minimize the impact when power plants are operating away from their designed conditions, model-based optimal control strategies would need to be developed for improved power plant performance during cycling. In this thesis, model predictive control (MPC) strategies are designed and implemented for improved power plant cycling. The MPC strategies addressed correspond to a dynamic matrix control (DMC)-based linear MPC, a classical sequential quadratic programming (SQP)-based nonlinear MPC, a direct transcription-based nonlinear MPC and a proposed modified SQP-based nonlinear MPC. The proposed modified SQP algorithm is based on the backtracking line search framework, which employs a group of relaxed step acceptance conditions for faster convergence. The numerical results for motivating examples, which are selected from literature problem sets, served as proof of concept to verify that the proposed modified SQP has the potential for implementation on high-dimensional systems. To illustrate the tracking performance and computational efficiency of the developed MPC strategies, three processes of different dimensionalities are addressed. The first process is an integrated gasification combined cycling power plant with a water-gas shift membrane reactor (IGCC-MR), which is represented by a first-principles and simplified systems-level nonlinear model in MATLAB. For this application, a setpoint tracking scenario simulating a step increase in power demand, a disturbance rejection scenario simulating a coal feed quality change, and a trajectory tracking scenario simulating a wind power penetration into the power grid are presented. The second application is an aqueous monoethanolamine (MEA)-based carbon capture process as part of a supercritical pulverized coal-fired (SCPC) power plant, whose model is built in Aspen Plus Dynamics. For this system, disturbance rejection scenarios considering a ramp decrease in the flue gas flow rate as well as wind power penetration, and a scenario considering a combination of disturbance rejection and setpoint tracking are addressed. The third process is the entire SCPC power plant with MEA-based carbon capture (SCPC-MEA), which simulation is also built in Aspen Plus Dynamics. Trajectory tracking and disturbance rejection scenarios associated with wind and solar power penetrations are presented for this process. The MPC implementations on the three processes for the different scenarios addressed are successful. The closed-loop results show that the proposed modified SQP-based nonlinear MPC enhances the tracking performance by up to 96% when compared to the DMC-based linear MPC in terms of integral squared error results. The novel approach also improves the MPC computational efficiency by 20% when compared to classical SQP-based and direct transcription-based nonlinear MPCs

Distribution and characteristics of gas hydrates in shallow sediments of pockmarks and seepage sites

Cold seeps are regions where fluid migrates from deep subsurface and escapes to the water column through the sea floor. Such fluids are usually rich in low molecular weight hydrocarbons, mainly methane, with small amount of other gases, such as carbon dioxide and hydrogen sulfide. In areas of water depth greater than 300-600m, gas hydrate could form depending on the bottom water temperature and geothermal gradients. Formation and decomposition of gas hydrate potentially change the properties of marine sediment. Therefore, in order to understand the evolution and morphological changes of marine cold seeps, it is important to know the distribution of gas hydrate in shallow sediment. Gas enclathrated in hydrate also contains important information and is helpful to understand the source of the gas. One aim of the thesis is to understand the distribution of gas hydrate within the sediment of a pockmark field at the Nigerian continental margin by using infrared thermal scanning and pore water chloride concentration. Both methods show similar hydrate distribution with different resolutions. By using coring information, the seismic profiles obtained in 2008 were calibrated to show the overview of free gas accumulation and hydrate distribution in the whole pockmark field. Elevated geothermal gradients were observed in the center of a pockmark where gas flares in the water column were imaged by hydroacoustic method, indicating the pockmark was active. The interaction among the fluid flow, hydrate formation and dissolution, and the thermal regime governs the formation and evolution of the pockmarks in this area. Knowledge of gas composition and crystal structure of natural gas hydrates is important for determining the stability of hydrate, which is a key factor to understand the fate of methane gas bubbles and hydrate bulks in the water column and the size of the hydrate reservoir in marine sediment. Methane is the dominant gas of hydrate samples recovered from pockmarks at the Nigerian continental margin, indicating that the gas is mainly biogenic. Besides methane, hydrogen sulfide and carbon dioxide were also detected using both Raman spectroscopy and gas chromatography. The thickness of gas hydrate stability zone (GHSZ) increases significantly due to the existence of hydrogen sulfide and carbon dioxide although their contents are relatively low. Hydrogen sulfide containing hydrate has only been discovered at Hydrate Ridge and Niger delta. It is a big surprise to observe hydrogen sulfide within the samples from Nigerian continental margin. In order to know whether such type of hydrate is restricted only in specific areas, we did additional Raman spectroscopy analysis on the hydrate samples recovered at cold seeps from different areas, including the Black Sea and the Makran continental margin. Results show that both samples contain hydrogen sulfide. Therefore, we infer that hydrogen sulfide containing hydrate is not restricted to certain area, but widely occurs within seepage sites where intensive upward methane flux exists and sustains high activity of anaerobic methane oxidation that produces hydrogen sulfide. Sudden release of hydrogen sulfide from hydrate due to changes of the ambient condition might dramatically affect the distribution of chemosynthetic community

An algorithm to schedule water delivery in pressurized irrigation networks

This study presents a deterministic constrained optimisation algorithm developed for using in a pressurized irrigation network. In irrigation networks —or water networks supplied by a head tank— utility managers can fully adapt the delivery times to suit their needs. The program provides a strategy for scheduling water delivery at a constant flow rate (opening and closing of hydrants, units, and subunits) to minimise energy consumption. This technique improves on earlier approaches by employing a deterministic method with little computing time. This method has been tested in the University of Alicante pressurized irrigation network, where decision-makers have identified the need to diminish the energy expenditure for watering University’s gardens.This work was supported by the research project “DESENREDA” through the 2021 call “Estancias de movilidad en el extranjero Jose Castillejo” of the Ministerio de Universidades (CAS21/00085) and for the project “Hi-Edu Carbon” Erasmus Plus Programme, Key Action KA22021, action type (2021-1-SK01-KA220-HED-000023274

A Framework for Executable Systems Modeling

Systems Modeling Language (SysML), like its parent language, the Unified Modeling Language (UML), consists of a number of independently derived model languages (i.e. state charts, activity models etc.) which have been co-opted into a single modeling framework. This, together with the lack of an overarching meta-model that supports uniform semantics across the various diagram types, has resulted in a large unwieldy and informal language schema. Additionally, SysML does not offer a built in framework for managing time and the scheduling of time based events in a simulation. In response to these challenges, a number of auxiliary standards have been offered by the Object Management Group (OMG); most pertinent here are the foundational UML subset (fUML), Action language for fUML (Alf), and the UML profile for Modeling and Analysis of Real Time and Embedded Systems (MARTE). However, there remains a lack of a similar treatment of SysML tailored towards precise and formal modeling in the systems engineering domain. This work addresses this gap by offering refined semantics for SysML akin to fUML and MARTE standards, aimed at primarily supporting the development of time based simulation models typically applied for model verification and validation in systems engineering. The result of this work offers an Executable Systems Modeling Language (ESysML) and a prototype modeling tool that serves as an implementation test bed for the ESysML language. Additionally a model development process is offered to guide user appropriation of the provided framework for model building