Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a solution requires transforming scientific missions into an optimized robust 'operational' constellation that addresses the needs of decision makers, scientific investigators and global users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent (2014) rulebased decision engine modeling runs that targeted optimizing the intended NPOESS architecture, becomes a surrogate for global operational climate monitoring architecture(s). This rule-based systems tools provide valuable insight for Global climate architectures, through the comparison and evaluation of alternatives considered and the exhaustive range of trade space explored. A representative optimization of Global ECV's (essential climate variables) climate monitoring architecture(s) is explored and described in some detail with thoughts on appropriate rule-based valuations. The optimization tools(s) suggest and support global collaboration pathways and hopefully elicit responses from the audience and climate science shareholders.
In this paper, we investigate how technical complexity affects the decision to collaborate or combine. First, we discuss a model that mimics the system architecting process that was used on the National Polar Orbiting Environmental Satellite System (NPOESS). Next, we present a metric that can be used to assess technical complexity and risk during the early system architecting phase of a program. We combine our technical complexity metric and additional measures of lifecycle cost and requirement satisfaction to evaluate a large tradespace of joint and single-agency, single-mission system architectures that we generate with our NPOESS model. Finally, we illustrate how agencies' decisions to collaborate and combine depend highly on agency preference, on the cost of collaboration, and on the final system architecture that is selected.
Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a long term solution requires transforming scientific missions into an optimized robust 'operational' constellation that addresses the collective needs of policy makers, scientific communities and global academic users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent rule-based expert system (RBES) optimization modeling of the intended NPOESS architecture becomes a surrogate for global operational climate monitoring architecture(s). These rulebased systems tools provide valuable insight for global climate architectures, by comparison/evaluation of alternatives and the sheer range of trade space explored. Optimization of climate monitoring architecture(s) for a partial list of ECV (essential climate variables) is explored and described in detail with dialogue on appropriate rule-based valuations. These optimization tool(s) suggest global collaboration advantages and elicit responses from the audience and climate science community. This paper will focus on recent research exploring joint requirement implications of the high profile NPOESS architecture and extends the research and tools to optimization for a climate centric case study. This reflects work from SPIE RS Conferences 2013 and 2014, abridged for simplification30, 32. First, the heavily securitized NPOESS architecture; inspired the recent research question - was Complexity (as a cost/risk factor) overlooked when considering the benefits of aggregating different missions into a single platform. Now years later a complete reversal; should agencies considering Disaggregation as the answer. We'll discuss what some academic research suggests. Second, using the GCOS requirements of earth climate observations via ECV (essential climate variables) many collected from space-based sensors; and accepting their definitions of global coverages intended to ensure the needs of major global and international organizations (UNFCCC and IPCC) are met as a core objective. Consider how new optimization tools like rule-based engines (RBES) offer alternative methods of evaluating collaborative architectures and constellations? What would the trade space of optimized operational climate monitoring architectures of ECV look like? Third, using the RBES tool kit (2014) demonstrate with application to a climate centric rule-based decision engine - optimizing architectural trades of earth observation satellite systems, allowing comparison(s) to existing architectures and gaining insights for global collaborative architectures. How difficult is it to pull together an optimized climate case study - utilizing for example 12 climate based instruments on multiple existing platforms and nominal handful of orbits; for best cost and performance benefits against the collection requirements of representative set of ECV. How much effort and resources would an organization expect to invest to realize these analysis and utility benefits?
This paper defines a framework to represent organizational and technical architectures and to quantitatively assess the complexity mechanisms within them. The framework is then applied to the case of the NPOESS program and used to illustrate the relationship between complexity, cost growth, and the concept of jointness.
Under the United States Arms Export Control Act, the International Traffic in Arms Regulations (ITAR) control the export of technologies that are specified as defense articles on the United States Munitions List (USML). The Directorate of Defense Trade Controls (DDTC) within the Department of State (DoS) interprets and enforces these regulations in an effort to safeguard national security by denying advanced military technology to potential competitors.
Abstract ID 94446Poster Board 167 In more than 90% of uveal melanoma cases, the oncogenic driver is an activating glutamine to leucine or proline mutation at residue 209 of the α subunit of G proteins Gq or G11 (Gαq/11QL or Gαq/11QP). Up to 50% of patients experience untreatable metastases. YM-254890 is a promising inhibitor of constitutively active (CA) Gαq/11, though its mechanism of action is not well understood. Evidence supports that although Gαq/11 has 2 sites of palmitoylation that allow for association with the plasma membrane (PM), these proteins are still found in subcellular locations. We have shown that more strongly targeting GαqQL to membranes by adding an N-terminal myristoylation site renders it insensitive to YM. To further understand how PM-restricted GαqQL loses sensitivity to YM inhibition of signaling, we have generated additional membrane targeting mutants of GαqQL. Although palmitoylation at cysteines 9 and 10 of GαqQL is essential for signaling, preventing palmitoylation by mutating both cysteines 9 and 10 to serines in the context of myristoylated GαqQL does not reduce signaling, as assayed by TEAD- and SRE-dependent luciferase reporter assays in HEK293 q/11 knockout cells. Moreover, signaling by this myristoylated, palmitoylation-deficient GαqQL mutant remains insensitive to YM, indicating that introduction of a single site for myristoylation, in the absence of any palmitoylation, is sufficient to render GαqQL resistant to YM. In addition to the importance of membrane localization for YM inhibition, we are investigating the role of other effector proteins, such as Gαq chaperone Ric8A, in facilitating YM inhibition or resistance. Increasing amounts of Ric8A decrease YM-sensitivity of an otherwise sensitive αqQL. Interestingly, we have also shown that loss of Ric8A confers YM-sensitivity to an otherwise resistant myristoylated GαqQL without abolishing signaling. TEAD and SRE luciferase assays, in addition to effector pulldowns, have revealed that these effects are not due to loss of expression of αq. These experiments reveal insights into the mechanism of YM inhibition, by considering both the impact of αqQL cellular localization and novel aspects of αq cellular regulation by effectors.
