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This paper addresses security and risk management of hardware and embedded systems across several applications. There are three companies involved in the research. First is an energy technology company that aims to leverage electric- vehicle batteries through vehicle to grid (V2G) services in order to provide energy storage for electric grids. Second is a defense contracting company that provides acquisition support for the DOD's conventional prompt global strike program (CPGS). These systems need protections in their production and supply chains, as well as throughout their system life cycles. Third is a company that deals with trust and security in advanced logistics systems generally. The rise of interconnected devices has led to growth in systems security issues such as privacy, authentication, and secure storage of data. A risk analysis via scenario-based preferences is aided by a literature review and industry experts. The analysis is divided into various sections of Criteria, Initiatives, C-I Assessment, Emergent Conditions (EC), Criteria-Scenario (C-S) relevance and EC Grouping. System success criteria, research initiatives, and risks to the system are compiled. In the C-I Assessment, a rating is assigned to signify the degree to which criteria are addressed by initiatives, including research and development, government programs, industry resources, security countermeasures, education and training, etc. To understand risks of emergent conditions, a list of Potential Scenarios is developed across innovations, environments, missions, populations and workforce behaviors, obsolescence, adversaries, etc. The C-S Relevance rates how the scenarios affect the relevance of the success criteria, including cost, schedule, security, return on investment, and cascading effects. The Emergent Condition Grouping (ECG) collates the emergent conditions with the scenarios. The generated results focus on ranking Initiatives based on their ability to negate the effects of Emergent Conditions, as well as producing a disruption score to compare a Potential Scenario's impacts to the ranking of Initiatives. The results presented in this paper are applicable to the testing and evaluation of security and risk for a variety of embedded smart devices and should be of interest to developers, owners, and operators of critical infrastructure systems. 

We present a gravitational lensing and X-ray analysis of a massive galaxy cluster and its surroundings. The core of MACS J0717.5+3745 ($M(R\lt 1\, {\rm Mpc})\sim$ $2 \times 10^{15}\, \, {\rm M}_{\odot }$, $z$ = 0.54) is already known to contain four merging components. We show that this is surrounded by at least seven additional substructures with masses ranging $3.8{-}6.5\times 10^{13}\, \, {\rm M}_{\odot }$, at projected radii 1.6–4.9 Mpc. We compare MACS J0717 to mock lensing and X-ray observations of similarly rich clusters in cosmological simulations. The low gas fraction of substructures predicted by simulations turns out to match our observed values of 1–$4{{\ \rm per\ cent}}$. Comparing our data to three similar simulated haloes, we infer a typical growth rate and substructure infall velocity. That suggests MACS J0717 could evolve into a system similar to, but more massive than, Abell 2744 by $z$ = 0.31, and into a ∼ $10^{16}\, \, {\rm M}_{\odot }$ supercluster by $z$ = 0. The radial distribution of infalling substructure suggests that merger events are strongly episodic; however, we find that the smooth accretion of surrounding material remains the main source of mass growth even for such massive clusters.