Transforming the U.S. Armed Forces

The U.S. armed forces themselves have embraced—at least rhetorically—the need to transform so as to meet the demands of information-age warfare. Nevertheless, in each service, efforts at trans- formation have faced opposition from traditionalists who perceive threats in new ways of war

Avoiding Trivia: The Role of Strategic Planning in American Foreign Policy

Students of American national security policy, particularly those without the benefit of firsthand policy-making experience, frequently under- or over- estimate the difficulty of formulating and implementing strategy in the U.S. government. As a result, observers tend either to portray senior policy makers as dolts or incompetents or to engage in a sort of strategic nihilism holding that it is impossible to develop sound strategy in this day and age

The Limits of Transformation

In the shadow of the recent Iraq war, it is easy to accept that “growth and diffusion of stealth, precision, and information technology” has truly heralded the long-awaited revolution in military affairs. American leaders—from the President to the Pentagon military and civilian leadership—have called for dramatic transformation of each of the services to fit this revolution. In many ways, this is a far harder task.https://digital-commons.usnwc.edu/usnwc-newport-papers/1015/thumbnail.jp

Improving quality indicator report cards through Bayesian modeling

<p>Abstract</p> <p>Background</p> <p>The National Database for Nursing Quality Indicators^®(NDNQI^®) was established in 1998 to assist hospitals in monitoring indicators of nursing quality (eg, falls and pressure ulcers). Hospitals participating in NDNQI transmit data from nursing units to an NDNQI data repository. Data are summarized and published in reports that allow participating facilities to compare the results for their units with those from other units across the nation. A disadvantage of this reporting scheme is that the sampling variability is not explicit. For example, suppose a small nursing unit that has 2 out of 10 (rate of 20%) patients with pressure ulcers. Should the nursing unit immediately undertake a quality improvement plan because of the rate difference from the national average (7%)?</p> <p>Methods</p> <p>In this paper, we propose approximating 95% credible intervals (CrIs) for unit-level data using statistical models that account for the variability in unit rates for report cards.</p> <p>Results</p> <p>Bayesian CrIs communicate the level of uncertainty of estimates more clearly to decision makers than other significance tests.</p> <p>Conclusion</p> <p>A benefit of this approach is that nursing units would be better able to distinguish problematic or beneficial trends from fluctuations likely due to chance.</p

The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests

Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand level, and remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a "SQLite" relational database or "ASCII" flat file version (at https://doi.org/10.5880/PIK.2020.006/; Reyer et al., 2020). The data policies of the individual contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R package (https://CRAN.R- project.org/package=ProfoundData; Silveyra Gonzalez et al., 2020), which provides basic functions to explore, plot and extract the data for model set-up, calibration and evaluation.Peer reviewe