Improving Navy recruiting with data farming

Proceedings of the 2016 Winter Simulation Conference T. M. K. Roeder, P. I. Frazier, R. Szechtman, E. Zhou, T. Huschka, and S. E. Chick, eds.Secretary of the Navy Ray Mabus states that people provide “the Navy and Marine Corps’ greatest edge” (Mabus, 2015). To help recruit and manage this dynamic workforce of more than 300,000 active duty Sailors, the Navy uses mathematical models and simulation to assess the potential impacts and risks of changes to force structure, budgets, policies, and the economy. One important model is the Planned Re-source Optimization (PRO) model. PRO is currently being used to inform recruiting resourcing decisions. The decisions may involve, for example, advertising, enlistment bonuses, number of production recruiters, etc. A limitation of PRO is the lack of an interface to facilitate extensive experimentation. This paper summarizes an effort underway to enhance the analytic utility of the PRO model by embedding it in a data farming environment. This enhanced tool is called the “Planned Resource Optimization Model with Ex-perimental Design” (PROM-WED)

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Improving Navy recruiting with the new Planned Resource Optimization Model with Experimental Design (PROM-WED)

The Navy spends over $300 million per year to recruit approximately 35,000 new active duty enlisted Sailors. The Navy has historically used a non-linear optimization model, the Planned Resource Optimization (PRO) model, to help inform decisions on the allocation of those recruiting resources. Input variables to the PRO model include economic influences and policy factors. The result is a recommended allocation of resources for advertisements, recruiters, enlistment bonuses, and education incentives. The PRO model's primary limitations are (1) potential deviations of input variables are not taken into consideration, and (2) extensive experimentation is not feasible. Realistically, input variables to the PRO model fluctuate, are unpredictable, and can interact with other variables to influence the recruiting environment and affect the optimal allocation of recruiting resources. This paper describes the Planned Resource Optimization Model with Experimental Design (PROM-WED), a tool that alleviates the limitations and enhances the analytic utility of the legacy PRO model. PROM-WED embeds the legacy PRO model within a data farming environment. PROM-WED's graphical user interface and decision support capability provide decision makers with robust insights into variable interactions and uncertainties to better inform their recruiting resourcing decisions.http://archive.org/details/improvingnavyrec1094552992Outstanding ThesisLieutenant, United States NavyApproved for public release; distribution is unlimited

Toward a contingency model of strategic risk taking

Includes bibliographical references (p. 20-25)

Autosomal dominant mitochondrial membrane protein-associated neurodegeneration (MPAN)

Background Mitochondrial membrane protein-associated neurodegeneration (MPAN) is caused by pathogenic sequence variants in C19orf12. Autosomal recessive inheritance has been demonstrated. We present evidence of autosomal dominant MPAN and propose a mechanism to explain these cases. Methods Two large families with apparently dominant MPAN were investigated; additional singleton cases of MPAN were identified. Gene sequencing and multiplex ligation-dependent probe amplification were used to characterize the causative sequence variants in C19orf12. Post-mortem brain from affected subjects was examined. Results In two multi-generation non-consanguineous families, we identified different nonsense sequence variations in C19orf12 that segregate with the MPAN phenotype. Brain pathology was similar to that of autosomal recessive MPAN. We additionally identified a preponderance of cases with single heterozygous pathogenic sequence variants, including two with de novo changes. Conclusions We present three lines of clinical evidence to demonstrate that MPAN can manifest as a result of only one pathogenic C19orf12 sequence variant. We propose that truncated C19orf12 proteins, resulting from nonsense variants in the final exon in our autosomal dominant cohort, impair function of the normal protein produced from the non-mutated allele via a dominant negative mechanism and cause loss of function. These findings impact the clinical diagnostic evaluation and counseling