Ultra-fast two-photon microscope for population neuronal voltage imaging

Understanding the complexity of neural networks in vivo requires simultaneous recordings of neuronal populations with action potential resolution. Genetically-encoded voltage indicators (GEVIs) that feature fast dynamics provide direct and reliable optical readouts of neural activity. The fast dynamic of spike-evoked GEVI responses necessitates the development of kilohertz-rate two-photon (2P) imaging systems. Existing high-speed 2P microscopes scan restricted field of views (FOVs), limiting the number of simultaneously imaged neurons. The dissertation describes the development of an Ultra-Fast 2-Photon (UF2P) microscope which is capable of full-frame high-speed imaging of a 400 x 400 µm^2 FOV of up to ~300 µm deep in mouse cortex at a kilohertz scan rate. A combination of temporal and spatial multiplexing was applied in the system to generate eight parallel beams. A 920 nm-wavelength, 31.25 MHz repetition rate laser was used to deliver laser pulses that were temporally multiplexed into four interleaved beamlets. Emitted photons were de-multiplexed through digital temporal gating. Each beamlet was spatially multiplexed into beams that were spaced 200 µm apart at sample to avoid crosstalk introduced by light scattering in deep tissue. Photons from spatially multiplexed beams were resolved by the multi-anode photomultiplier tube. The UF2P microscope was applied along with novel positive-going voltage indicators with improved spike detection (SpikeyGi and SpikeyGi2) for in vivo voltage imaging in mouse cortex and a self-supervised denoising algorithm model (DeepVID) was trained for reducing shot noise in low photon-flux condition. Through combining all techniques above, simultaneous high-speed, deep-tissue imaging of more than one hundred densely-labeled neurons was achieved in awake behaving mice for over an hour with minimal effects on photobleaching, thermal effects, and photodamage during this period of time. The system demonstrates the capability for sustained voltage imaging across large neuronal populations

Mitigating Initialization Bias in Transportation Modeling Applications

Traffic simulation model is a useful tool to evaluate real world transportation solutions in a risk free environment. Traffic simulation model requires some form of initialization before their outputs can be considered meaningful. Models are typically initialized in a particular, often “empty” state and therefore must be “warmed-up” for an unknown amount of simulation time before reaching a “quasi-steady-state” representative of the systems’ performance. The portion of the output series influenced by the arbitrary initialization is referred to as the initial transient and is a widely recognized problem in other areas, but less emphasized in the transportation application. After reviewing methods of accounting for the initial transient bias, this paper selects and evaluates three techniques; two popular methods from the general simulation field, Welch’s and MSER method, and one from the current state of the practice in the transportation application, Volume Balancing. VISSIM models were created to compare the selected methods. After presenting the results of each method, advantages and criticisms of each are discussed as well as issues that arose during the implementation. It is hoped that this paper informs the current practice in transportation application as to how to account for the initial transient in order to continue facilitating meaningful and reliable results

On the Use of Queueing Petri Nets for Modeling and Performance Analysis of Distributed Systems

Predictive performance models are used increasingly throughout the phases of the software engineering lifecycle of distributed systems. However, as systems grow in size and complex-ity, building models that accurately capture the different aspects of their behavior becomes a more and more challenging task. The challenge stems from the limited model expressivenes

Development and Testing of a Reconfigurable Gasoline Engine Control Module

A dynamometer laboratory may typically face the following issues on a daily basis: the lack/availability of a calibration, software limiters, hardware failure codes/modes, hardware/software level incompatibilities and the time/knowledge required to troubleshoot these issues. A Reconfigurable Engine Controller (REC), which provides freedom to operate the engine under any condition, eliminates many of these issues. The result is an accelerated engine development process which includes engine mapping and/or testing new algorithms before implementation on production hardware. A REC can provide a flexible tailored controller to suit the needs of the individual testing application. This research used the dSPACE MicroAutoBox and RapidPro hardware and software with MATLAB/Simulink (the coding tool) to successfully develop and test a REC under a series of steady state engine operating conditions. Proportional Integral Derivative (PID) controllers were also successfully implemented for the throttle body position, lambda sensor heating and fuel pulse width modulation. The data collected from a combustion analysis system along with the production engine controller and the REC parameters was used to validate the new controller. The results indicated that the system performance was similar to that of the production controller

Model based control for a modern automotive diesel engine

The dynamic performance of a turbocharged diesel engine during transient operation has been studied. For appropriate analysis of data obtained from engine transient operation, four alternative automated filtering methods were implemented on the cycle-by-cycle in-cylinder pressure. The techniques to process instantaneous emission data and align the transient data from different analyzers were developed. In the experimental study, the effects of engine speed and EGR have been investigated through load increase tests at a constant engine speed with different EGR calibrations. Based on the experimental results, a real-time diesel engine model was developed by Simulink. The model is capable of simulating the main engine parameters. It included the air path mode], combustion model and dynamic emission behavior model. The model can run as a real-time simulator for engine control strategy development. . An advanced fast predictive contro] approach was proposed and validated in a HIL simulation platform. The model predictive control was developed for EGR and VGT control. The oxygen concentration oriented control was designed and implemented in the real-time model. Compared with PID control, MPC presents a good tracking performance of reference values with a shorter response time. The results in HIL proved the real-time capability of the control strategy

State-of-the-Art Review : a user's guide to the brave new world of designing simulation experiments

Many simulation practitioners can get more from their analyses by using the statistical theory on design of experiments (DOE) developed specifically for exploring computer models. We discuss a toolkit of designs for simulators with limited DOE expertise who want to select a design and an appropriate analysis for their experiments. Furthermore, we provide a research agenda listing problems in the design of simulation experiments¿as opposed to real-world experiments¿that require more investigation. We consider three types of practical problems: (1) developing a basic understanding of a particular simulation model or system, (2) finding robust decisions or policies as opposed to so-called optimal solutions, and (3) comparing the merits of various decisions or policies. Our discussion emphasizes aspects that are typical for simulation, such as having many more factors than in real-world experiments, and the sequential nature of the data collection. Because the same problem type may be addressed through different design types, we discuss quality attributes of designs, such as the ease of design construction, the flexibility for analysis, and efficiency considerations. Moreover, the selection of the design type depends on the metamodel (response surface) that the analysts tentatively assume; for example, complicated metamodels require more simulation runs. We present several procedures to validate the metamodel estimated from a specific design, and we summarize a case study illustrating several of our major themes. We conclude with a discussion of areas that merit more work to achieve the potential benefits¿either via new research or incorporation into standard simulation or statistical packages

Analysis, modeling and control of standard and alternative combustion strategies in a diesel engine

Research on compression ignited engines from combustion control point of view assumes an important role since this technology is being demonstrated lacks in the accomplishment of the evolving emissions standards to more stringent targets. The nature of combustion, in particular, seems not to be able to overcome some crucial trade-offs in emission and efficiency management. This work is aimed at investigating some key points on the way a diesel engine is conventionally run, such as noise control, nitrogen oxides modeling and closed loop methodologies to handle combustion. At the same time a great effort is spent in understanding the most important aspects of reactivity-controlled compression ignition (RCCI) combustion, which in the scenario of low temperature combustions is the one, theoretically speaking, to provide the most extended applicability throughout the engine operating field. Investigation on RCCI combustion has the main objective to offer a work-around to the previously cited trade-offs. Since literature provides several examples of how this kind of injection strategy is advantageous to the predetermined goals, this work tries to focus on how it can be controlled, because combustion stability remains the most critical issue