Modeling the Risk of Fire/Explosion Due to Oxidizer/Fuel Leaks in the Ares I Interstage

A significant flight hazard associated with liquid propellants, such as those used in the upper stage of NASA's new Ares I launch vehicle, is the possibility of leakage of hazardous fluids resulting in a catastrophic fire/explosion. The enclosed and vented interstage of the Ares I contains numerous oxidizer and fuel supply lines as well as ignition sources. The potential for fire/explosion due to leaks during ascent depends on the relative concentrations of hazardous and inert fluids within the interstage along with other variables such as pressure, temperature, leak rates, and fluid outgasing rates. This analysis improves on previous NASA Probabilistic Risk Assessment (PRA) estimates of the probability of deflagration, in which many of the variables pertinent to the problem were not explicitly modeled as a function of time. This paper presents the modeling methodology developed to analyze these risks

University Managed Technology Business Incubators: Asset or Liability?

University managed technology-based business incubators (UMTIs) have become increasingly popular. Some universities are forming private corporations and are encouraging professors/researchers to commercialize intellectual property (IP) based upon research conducted in their laboratories. The UMTI provides the infrastructure, access to high-tech laboratories, libraries, students and faculty, and a coalition of like-minded entrepreneurs. Universities face uncertainties when establishing UMTIs and need to minimize risk while maximizing benefits. This paper discusses results of a benchmarking study of eleven technology incubators and their risk mitigation policies. Experience with technology transfer and use of the UMTI as a living laboratory for students is presented

Refinement Modal Logic

In this paper we present {\em refinement modal logic}. A refinement is like a bisimulation, except that from the three relational requirements only `atoms' and `back' need to be satisfied. Our logic contains a new operator 'all' in addition to the standard modalities 'box' for each agent. The operator 'all' acts as a quantifier over the set of all refinements of a given model. As a variation on a bisimulation quantifier, this refinement operator or refinement quantifier 'all' can be seen as quantifying over a variable not occurring in the formula bound by it. The logic combines the simplicity of multi-agent modal logic with some powers of monadic second-order quantification. We present a sound and complete axiomatization of multi-agent refinement modal logic. We also present an extension of the logic to the modal mu-calculus, and an axiomatization for the single-agent version of this logic. Examples and applications are also discussed: to software verification and design (the set of agents can also be seen as a set of actions), and to dynamic epistemic logic. We further give detailed results on the complexity of satisfiability, and on succinctness

A Data-Driven Framework for Identifying Investment Opportunities in Private Equity

The core activity of a Private Equity (PE) firm is to invest into companies in order to provide the investors with profit, usually within 4-7 years. To invest into a company or not is typically done manually by looking at various performance indicators of the company and then making a decision often based on instinct. This process is rather unmanageable given the large number of companies to potentially invest. Moreover, as more data about company performance indicators becomes available and the number of different indicators one may want to consider increases, manual crawling and assessment of investment opportunities becomes inefficient and ultimately impossible. To address these issues, this paper proposes a framework for automated data-driven screening of investment opportunities and thus the recommendation of businesses to invest in. The framework draws on data from several sources to assess the financial and managerial position of a company, and then uses an explainable artificial intelligence (XAI) engine to suggest investment recommendations. The robustness of the model is validated using different AI algorithms, class imbalance-handling methods, and features extracted from the available data sources

Search-Related Suppression of Hippocampus and Default Network Activity during Associative Memory Retrieval

Episodic memory retrieval involves the coordinated interaction of several cognitive processing stages such as mental search, access to a memory store, associative re-encoding, and post-retrieval monitoring. The neural response during memory retrieval is an integration of signals from multiple regions that may subserve supportive cognitive control, attention, sensory association, encoding, or working memory functions. It is particularly challenging to dissociate contributions of these distinct components to brain responses in regions such as the hippocampus, which lies at the interface between overlapping memory encoding and retrieval, and “default” networks. In the present study, event-related functional magnetic resonance imaging (fMRI) and measures of memory performance were used to differentiate brain responses to memory search from subcomponents of episodic memory retrieval associated with successful recall. During the attempted retrieval of both poorly and strongly remembered word pair associates, the hemodynamic response was negatively deflected below baseline in anterior hippocampus and regions of the default network. Activations in anterior hippocampus were functionally distinct from those in posterior hippocampus and negatively correlated with response times. Thus, relative to the pre-stimulus period, the hippocampus shows reduced activity during intensive engagement in episodic memory search. Such deactivation was most salient during trials that engaged only pre-retrieval search processes in the absence of successful recollection or post-retrieval processing. Implications for interpretation of hippocampal fMRI responses during retrieval are discussed. A model is presented to interpret such activations as representing modulation of encoding-related activity, rather than retrieval-related activity. Engagement in intensive mental search may reduce neural and attentional resources that are otherwise tonically devoted to encoding an individual’s stream of experience into episodic memory

Indigenous free prior informed consent: a case for self determination in World Heritage nomination processes

Free prior informed consent is a critical concept in enacting the rights of Indige- nous People according to the United Nations Declaration on the Rights of Indig- enous Peoples. This paper outlines a case for the inclusion of free prior informed consent in World Heritage nomination processes and examines issues that are problematic when enacting free prior informed consent. Case research was used to analyse current issues in the potential nomination of certain areas of Cape York Peninsula, Australia. The authors’ reflexive engagement within this case offers insights into the praxis of developing a World Heritage nomina- tion consent process. The outcomes of this research were: preconditions need to be addressed to avoid self-exclusion by indigenous representative organisations; the nature of consent needs to account for issues of representation and Indige- nous ways of decision making; the power of veto needs to have formal recogni- tion in the nomination process; and prioritising self-determination within free prior informed consent ensures the intent of the United Nations Declaration on the Rights of Indigenous Peoples. The paper contributes to the human rights agenda of Indigenous People and conservation management processes by help- ing address the issues that will be raised during a World Heritage nomination process