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  1. Ellis, K ; Ferrell, W ; Knapp, J. (Ed.)
    Despite being a very popular topic and researched by several scientists, the entire 3D bioprinting process is still subjected to several challenges like geometric fidelity, mechanical complexities, cell viability, and proliferation. Rheological investigations along with the proper design of experiments help to explore the physical and mechanical properties of biomaterials and 3D printed scaffolds that are directly associated with their geometric fidelity. To ensure post-printed structural integrity, viscosity thickeners and crosslinkers were used in this research. Mixtures of Carboxymethyl Cellulose (CMC, viscosity enhancer), Alginate, and CaCl2 and CaSO4 (crosslinkers) were prepared at various concentrations maintaining minimum solid content. For each composition, a set of rheological tests was performed in form of flow, thixotropic, amplitude, and frequency tests. This research presents an overview of controlling the rheological properties of various bio-inks that are viscosity enhancer and pre-crosslinkers dependent, which opens doors to looking at 3D bioprinting in a very different way. 
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  2. Ellis, K ; Ferrell, W ; Knapp, J. (Ed.)
    Three-dimensional bio-printing is a rapidly growing field attempting to recreate functional tissues for medical and pharmaceutical purposes. Development of functional tissues and organs requires the ability to achieve large full-scale scaffolds that mimic human organs. It is difficult to achieve large scaffolds that can support themselves without damaging printed cells in the process. The high viscosity needed to support large prints requires high amounts of pressure that diminishes cell viability and proliferation. By working with the rheological, mechanical, and microstructural properties of different compositions, a set of biomaterial compositions was identified to have high structural integrity and shape fidelity without needing a harmful amount of pressure to extrude. Various large scale-scaffolds were fabricated (up to 3.0 cm, 74 layers) using those hybrid hydrogels ensuring geometric fidelity. This effort can ensure to fabricate large scaffolds using 3D bio-printing processes ensuring proper internal and external geometries. 
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  3. Ellis, K. ; Ferrell, W. ; Knapp, J. (Ed.)
    The mass transportation distance rank histogram (MTDRh) was developed to assess the reliability of any given scenario generation process for a two-stage, risk-neutral stochastic program. Reliability is defined loosely as goodness of fit between the generated scenario sets and corresponding observed values over a collection of historical instances. This graphical tool can diagnose over- or under-dispersion and/or bias in the scenario sets and support hypothesis testing of scenario reliability. If the risk-averse objective is instead to minimize CVaR of cost, the only important, or effective, scenarios are those that produce cost in the upper tail of the distribution at the optimal solution. We describe a procedure to adapt the MTDRh for use in assessing the reliability of scenarios relative to the upper tail of the cost distribution. This adaptation relies on a conditional probability distribution derived in the context of assessing the effectiveness of scenarios. For a risk-averse newsvendor formulation, we conduct simulation studies to systematically explore the ability of the CVaR-adapted MTDRh to diagnose different ways that scenario sets may fail to capture the upper tail of the cost distribution near optimality. We conjecture that, as with the MTDRh and its predecessor minimum spanning tree rank histogram, the nature of the mismatch between scenarios and observations can be observed according to the non-flat shape of the rank histogram. On the other hand, scenario generation methods can be calibrated according to uniform distribution goodness of fit to the distribution of ranks. 
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  4. Ellis, K ; Ferrell, W ; Knapp, J (Ed.)
  5. Ellis, K. ; Ferrell, W. ; Knapp J. (Ed.)
    Trauma care services are a vital part of all healthcare-based networks as timely accessibility is important for citizens. Trauma care access is even more relevant when unexpected events such as the COVID-19 pandemic overload the capacity of hospitals. Research literature has highlighted that access to trauma care is not equal for all populations, especially when comparing rural and urban groups. In this research we present a decision-making model for the expansion of a trauma hospital network by considering the demand for services of rural communities. The decision making model provides recommendations in terms of where to place additional aeromedical facilities and where to locate additional trauma hospitals. A case study is presented for the state of Texas, where a sensitivity analysis was conducted to consider changes in demand, cost, and the total number of facilities allowed in the network. The results show that the location of new facilities is sensitive to the expected service demand and the maximum number of facilities allowed in the network. 
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  6. Ellis, K ; Ferrell, W. ; Knapp, J. (Ed.)
    Failure identification and prediction in a power system are essential components that are prerequisites for optimizing the maintenance of the system. The incidences of power system failures have increased dramatically in recent times due to the uncertainties inherent in the advent of both man-made and natural disasters. This problem is further exacerbated due to the increasing demand for higher operational efficiency in power systems. Currently, there is a paucity of studies that predict and identify failure in a distribution power system. In this paper, we propose an integrated methodology for selecting the optimal maintenance plan based on predicting and identifying failure modes with the aid of Hidden Markov Models (HMM) and a probabilistic decision-making tool. While the model parameters of previous studies were determined utilizing observable prior knowledge, the use of HMM offers a different approach especially in the absence of such observable prior distributions. Thus, we determine the status of health of a power system by using an HMM to capture the relationship between unobservable degradation state and observed parameters. The preliminary outcome is instructive for the management of power systems especially in response to fortifying the system against aging and degradation. 
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  7. Ellis, K. ; Ferrell, W. ; Knapp, J. (Ed.)
    There is no doubt that there is an increase in the penetration of electrical energy into the operation of high-speed railway systems (HSR). This is even more pronounced with the increasing trends in smart electric multiple units (EMU). The operational speed serves as a metric for punctuality and safety, as well as a critical element to maintain the balance between energy supply and consumption. The speed-based regenerative energy from EMU’s braking mode could be utilized in the restoration of system operation in the aftermath of a failure. This paper optimizes the system resiliency with respect to the operational speed for the purpose of restoration by minimizing the total cost of implementing recovery measures. By simultaneously valuating the dual-impact of any given fault on the speed deterioration level from the railway operation systems (ROS) side and the power supply and demand unbalance level from the railway power systems (RPS) side, this process develops an adaptive two-dimension risk assessment scheme for prioritizing the handling of different operational zones that are cascaded in the system. With the aid of an integrated speed-based resilience cost model, we determine the optimal resilience time, speed modification plan, and energy allocation strategy. The outcome from implementing this routine in a real-world HSR offers a pioneering decision-making strategy and perspective on optimizing the resilience of an integrated system. 
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