Naturalistic decision-making studies of intelligence analysis have generally focused on information search, collection, and synthesis processes, deemphasizing the initial "problem formulation" phase, in which analysts interpret and contextualize the information request to determine which information to collect. We present the results of two studies focusing on this phase. In the first study, we performed a cognitive task analysis via semistructured interviews with 22 active-duty U.S. Army intelligence analysts to uncover factors that arise in operational environments that complicate problem formulation. The factors discovered (e.g., vague and/or overly narrow intelligence requests) led to a second study probing 6 active-duty U.S. Army intelligence analysts' cognitive strategies with a "think-aloud" protocol as they interpreted and evaluated representative information requests. The study revealed that analysts actively interpret and contextualize an information request. The analysts reframed and broadened the request so that they could respond meaningfully to the underlying intent, then used contextual cues and metainformation to determine the most useful collectors and how effectively the request could be answered in the time allotted. We discuss these results and their implications for both the cognitive modeling of intelligence analysis and the development of training and decision aids for more effective framing and contextualization of information requests.

Shortened version of the title: Dietary intake and its relationship to BMIDisclosure statements: This research received no specific grant from any funding agency, commercial or not-for-profit sectors. Acknowledgments:We are grateful to all the families who took part in this study, to the midwives for their help in recruiting them, the paediatricians and health visitors and to the Born in Bradford team which included interviewers, data managers, laboratory staff, clerical workers, research scientists, volunteers and managers Conflict of interest:The authors declare no conflict of interest. Authors PS and MB had some financial support from an NIHR CLAHRC implementation grant and/or an NIHR applied programme grant (RP-PG-0407-10044) for the submitted work, but have had no financial relationships with any organisations that might have an interest in the submitted work in the previous 3 years and no other relationships or activities that could appear to have influenced the submitted work.Authorship: All authors contributed to the interpretation of the results ad write-up and have read and approved the final version. MB and PS designed the research, trained the data collection staff, provided oversight in data collection, interpreted results and supported the manuscript preparation. SM conducted the analysis, interpreted the data and led the writing of the manuscript. SB provided oversight to the analysis, contributed to data interpretation and reviewed the manuscript. Subjects: Infants at age 12 months (n 722; 44% White British, 56% Pakistani), 18 months (n 779; 10 44% White British, 56% Pakistani) and 36 months (n 845; 45% White British, 55% Pakistani). Ethical Standards 11Results: Diet at age 12 months was not associated with BMI z-score at age 36 months. Higher

Cyber Network degradation and exploitation can covertly turn an organization's technological strength into an operational weakness. It has become increasingly imperative, therefore, for an organization's personnel to have an awareness of the state of the Cyber Network that they use to carry out their mission. Recent high-level government initiatives along with hacking and exploitation in the commercial realm highlight this need for general Cyber Situational Awareness (SA). While much of the attention in both the military and commercial cyber security communities is on abrupt and blunt attacks on the network, the most insidious cyber threat to organizations are subtle and persistent attacks leading to compromised databases, processing algorithms, and displays. We recently began an effort developing software tools to support the Cyber SA of users at varying levels of responsibility and expertise (i.e., not just the network administrators). This paper presents our approach and preliminary findings from a CTA we conducted with an operational Subject Matter Expert to uncover the situational awareness requirements of such a tool. Results from our analysis indicate a list of preliminary categories of these requirements, as well as specific questions that will drive the design and development of our SA tool.

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Modern intelligence analysis has evolved due to the focus on Irregular Warfare (IW) and the proliferation of network-centric environments. Given the ubiquity of those two themes in modern intelligence analysis, this paper seeks to provide a detailed cognitive model of intelligence analysis for IW, the Mutual Support Function Model (MSFM), based on the original Support Function Model (SFM) for intelligence analysis from (Elm et al., 2005). In addition to the three functions of Down Collect, Conflict and Corroboration, and Hypothesis Exploration from the original SFM, the MSFM considers two additional functions, Information Needs Management and Decision Selection. In addition to presenting this theoretical model, this paper also presents a discussion of how the model may be applied to operational environments through the development of tools. We also discuss strategies for introducing associated technology to the work environment in a suitable manner.