Surface Warfare Center Contributions for Addressing Warfare System Development Challenges and Goals

Proceedings Paper (for Acquisition Research Program)The size, interdependencies, and complexity of Navy software intensive warfare systems are continuing to rapidly increase. Numerous studies and reports indicate that the majority of DoD/Navy warfare system development efforts are failing to consistently successfully deliver high quality software systems on schedule and within budget. This paper provides several examples of successful development efforts that utilized Naval Surface Warfare Center (WC) in-house expertise to successfully deliver open architecture (OA)''based multi-system and multi-platform capable software systems with reusable components. This paper also provides insight into how government in-house software expertise can be utilized to mitigate many of the documented software system acquisition challenges that prevent the successful development and delivery of high quality software systems on schedule and within budget.Acquisition Research ProgramApproved for public release; distribution is unlimited

The Grizzly, February 9, 1999

Asper Notches 100th Win • Grand Opening for New Bookstore • Faculty Vote to Require Independent Learning Experience • Middle States Grades Ursinus • Spanish Department: Smaller Staff + Higher Enrollment = Big Headaches • Community Service Making a Difference at Ursinus • Opinion: Overcoming Immaturity the Key to Ending Permit Theft; Reader Response; U.S. Sells Out Integrity for Intelligence in Iraq; Free Will an Important Responsibility; Why Gephardt Will Settle for Speaker • The Classical Critic: Bravo Pindell! • Swimming Falls to Swarthmore • Gymnastics Edged by Courtland • Women\u27s Basketball Still in Playoff Hunt • Men\u27s Basketball First in Conference • Ursinus Wrestling Takes Muhlenberg and Gettysburg to the Mathttps://digitalcommons.ursinus.edu/grizzlynews/1433/thumbnail.jp

The Grizzly, November 2, 1999

Is Safety an Issue on Campus? • Payne Stewart, Golfer, Dies in Plane Crash • A First for National French Week • Summer Business Internship Opportunities • Hobson Hall: Home Sweet Home • Opinion: The Effectiveness of College in the Preparation of Students for the World; Gun Control has to be Enacted for Everyone\u27s Safety: A Response; Paying Back the US Dues to the UN • Always Unique, Ben Folds Five Rocks Philadelphia as Part of 1999 Tour • Vecchio, Duncan Power Bears Offense as Bears Rout Mules • Soccer Splits Pair with Fords, Green Terror • Flag Football: APO Downs 2-Time Champion Delta Pi in Double-OT • Junior Vecchio Awarded CC Offensive Football Player of the Week • Tough End to Tough Hockey Season • Volleyball Finishes Best Season Ever • Bears Defense Roars to Big Winhttps://digitalcommons.ursinus.edu/grizzlynews/1450/thumbnail.jp

What controls global fire? Evaluating emergent relationships in satellite observations and global vegetation models using machine learning

Fire is a major disturbance agent in terrestrial ecosystems. The occurrence and spread of wildfires is controlled by the interplay of human activities, weather conditions, and the conditions of vegetation and litter fuels. Most state-of-the-art global ecosystem models represent such controls to simulate fire effects on vegetation dynamics and global carbon cycling. However, global fire models poorly reproduce the observed dynamics and variability of fire burned area. Here we aim to identify and evaluate functional responses of global burned area to environmental and human controls. We use several global satellite, climate, and socioeconomic datasets, and simulations from the Fire Model Inter-comparison Project (FireMIP) [1] to predict the observed or modelled burned area with the random forest machine-learning algorithm. We then derive from the trained random forests individual conditional expectation curves [2], which represent emergent functional responses of burned area to controlling factors. These functional responses allow us to compare data- and model-derived sensitivities. FireMIP models mostly represent the emergent responses to climate variables but show diverse responses to human population, land cover, and vegetation. The models especially underestimate the emergent strong increase of burned area with increasing precedent plant productivity in many semi-arid ecosystems. The results suggest that FireMIP models misrepresent the links between plant productivity, biomass allocation, litter turnover, and fuel production. Additionally, the good performance of data-driven modelling approaches [3] suggests to develop hybrid global fire models to better represent and predict the role of fire dynamics for ecosystem functioning and vegetation-climate interactions. REFERENCES: 1. Rabin, S.S., Melton, J.R., Lasslop, G., Bachelet, D., Forrest, M., Hantson, S., Kaplan, J.O., Li, F., Mangeon, S., Ward, D.S., Yue, C., Arora, V.K., Hickler, T., Kloster, S., Knorr, W., Nieradzik, L., Spessa, A., Folberth, G.A., Sheehan, T., Voulgarakis, A., Kelley, D.I., Prentice, I.C., Sitch, S., Harrison, S., Arneth, A., 2017. The Fire Modeling Intercomparison Project (FireMIP), phase 1: experimental and analytical protocols with detailed model descriptions. Geosci Model Dev 10, 1175–1197. https://doi.org/10.5194/gmd-10-1175-2017 2. Goldstein, A., Kapelner, A., Bleich, J., Pitkin, E., 2013. Peeking Inside the Black Box: Visualizing Statistical Learning with Plots of Individual Conditional Expectation. ArXiv13096392 Stat. 3. Forkel, M., Dorigo, W., Lasslop, G., Teubner, I., Chuvieco, E., Thonicke, K., 2017. A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1). Geosci Model Dev 10, 4443–4476. https://doi.org/10.5194/gmd-10-4443-201

Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

Genetic variation at CYP3A is associated with age at menarche and breast cancer risk : a case-control study

Abstract Introduction We have previously shown that a tag single nucleotide polymorphism (rs10235235), which maps to the CYP3A locus (7q22.1), was associated with a reduction in premenopausal urinary estrone glucuronide levels and a modest reduction in risk of breast cancer in women age ≤50 years. Methods We further investigated the association of rs10235235 with breast cancer risk in a large case control study of 47,346 cases and 47,570 controls from 52 studies participating in the Breast Cancer Association Consortium. Genotyping of rs10235235 was conducted using a custom Illumina Infinium array. Stratified analyses were conducted to determine whether this association was modified by age at diagnosis, ethnicity, age at menarche or tumor characteristics. Results We confirmed the association of rs10235235 with breast cancer risk for women of European ancestry but found no evidence that this association differed with age at diagnosis. Heterozygote and homozygote odds ratios (ORs) were OR = 0.98 (95% CI 0.94, 1.01; P = 0.2) and OR = 0.80 (95% CI 0.69, 0.93; P = 0.004), respectively (P trend = 0.02). There was no evidence of effect modification by tumor characteristics. rs10235235 was, however, associated with age at menarche in controls (P trend = 0.005) but not cases (P trend = 0.97). Consequently the association between rs10235235 and breast cancer risk differed according to age at menarche (P het = 0.02); the rare allele of rs10235235 was associated with a reduction in breast cancer risk for women who had their menarche age ≥15 years (ORhet = 0.84, 95% CI 0.75, 0.94; ORhom = 0.81, 95% CI 0.51, 1.30; P trend = 0.002) but not for those who had their menarche age ≤11 years (ORhet = 1.06, 95% CI 0.95, 1.19, ORhom = 1.07, 95% CI 0.67, 1.72; P trend = 0.29). Conclusions To our knowledge rs10235235 is the first single nucleotide polymorphism to be associated with both breast cancer risk and age at menarche consistent with the well-documented association between later age at menarche and a reduction in breast cancer risk. These associations are likely mediated via an effect on circulating hormone levels

Enabling Software Acquisition Improvement: Government and Industry Software Development Team Acquisition Model

Proceedings Paper (for Acquisition Research Program)The growth, complexity, and reliance on software (SW) as part of the Department of Defense and Navy (DoD/Navy) warfare systems is continuing to increase. This increase in SW complexity and reliance has been accompanied by an increase in well documented SW intensive system acquisition cost, schedule and technical performance failures. The DoD/Navy is not consistently performing as a smart buyer of software intensive systems. The government and private industry have not been successful in applying the latest software methodologies and technologies nor consistently providing high quality and reliable systems that are delivered on schedule and within budget. The typical acquisition approach utilized over the past several decades of relying primarily on private industry for architecting, designing and implementing SW intensive systems has resulted in the loss of government in-house applied SW expertise necessary to achieve truly open architected systems and systems-of-systems. The key enablers for improving SW intensive system acquisition are the reconstitution and utilization of government in-house software subject matter experts (SMES) that can lead and work with industry SW engineers as part of an integrated SW Development Team.Naval Postgraduate School Acquisition Research ProgramApproved for public release; distribution is unlimited

Enabling Software Acquisition Improvement: Government and Industry Software development Teams

Symposium Presentation (for Acquisition Research Program)Symposium PresentationNaval Postgraduate School Acquisition Research ProgramApproved for public release; distribution is unlimited

Software Intensive Systems Acquisition [video]

Meyer Institute Guest Speaker PresentationMay 28, 2014, Joe Heil, Software Intensive Systems Acquisitio