Influence Diagram Use With Respect to Technology Planning and Investment

Influence diagrams are relatively simple, but powerful, tools for assessing the impact of choices or resource allocations on goals or requirements. They are very general and can be used on a wide range of problems. They can be used for any problem that has defined goals, a set of factors that influence the goals or the other factors, and a set of inputs. Influence diagrams show the relationship among a set of results and the attributes that influence them and the inputs that influence the attributes. If the results are goals or requirements of a program, then the influence diagram can be used to examine how the requirements are affected by changes to technology investment. This paper uses an example to show how to construct and interpret influence diagrams, how to assign weights to the inputs and attributes, how to assign weights to the transfer functions (influences), and how to calculate the resulting influences of the inputs on the results. A study is also presented as an example of how using influence diagrams can help in technology planning and investment. The Space Propulsion Synergy Team (SPST) used this technique to examine the impact of R&D spending on the Life Cycle Cost (LCC) of a space transportation system. The question addressed was the effect on the recurring and the non-recurring portions of LCC of the proportion of R&D resources spent to impact technology objectives versus the proportion spent to impact operational dependability objectives. The goals, attributes, and the inputs were established. All of the linkages (influences) were determined. The weighting of each of the attributes and each of the linkages was determined. Finally the inputs were varied and the impacts on the LCC determined and are presented. The paper discusses how each of these was accomplished both for credibility and as an example for future studies using influence diagrams for technology planning and investment planning

The Functional Breakdown Structure (FBS) and Its Relationship to Life Cycle Cost

The Functional Breakdown Structure (FBS) is a structured, modular breakdown of every function that must be addressed to perform a generic mission. It is also usable for any subset of the mission. Unlike a Work Breakdown Structure (WBS), the FBS is a function-oriented tree, not a product-oriented tree. The FBS details not products, but operations or activities that should be performed. The FBS is not tied to any particular architectural implementation because it is a listing of the needed functions, not the elements, of the architecture. The FBS for Space Transportation Systems provides a universal hierarchy of required functions, which include ground and space operations as well as infrastructure - it provides total visibility of the entire mission. By approaching the systems engineering problem from the functional view, instead of the element or hardware view, the SPST has created an exhaustive list of potential requirements which the architecture designers can use to evaluate the completeness of their designs. This is a new approach that will provide full accountability of all functions required to perform the planned mission. It serves as a giant check list to be sure that no functions are omitted, especially in the early architectural design phase. A significant characteristic of a FBS is that if architecture options are compared using this approach, then any missing or redundant elements of each option will be ' identified. Consequently, valid Life Cycle Costs (LCC) comparisons can be made. For example, one architecture option might not need a particular function while another option does. One option may have individual elements to perform each of three functions while another option needs only one element to perform the three functions. Once an architecture has been selected, the FBS will serve as a guide in development of the work breakdown structure, provide visibility of those technologies that need to be further developed to perform required functions, and help identify the personnel skills required to develop and operate the architecture. It also wifi allow the systems engineering activities to totally integrate each discipline to the maximum extent possible and optimize at the total system level, thus avoiding optimizing at the element level (stove-piping). In addition, it furnishes a framework that wifi help prevent over or under specifying requirements because all functions are identified and all elements are aligned to functions

Polydispersity Effects in Colloid-Polymer Mixtures

We study phase separation and transient gelation in a mixture consisting of polydisperse colloids and non-adsorbing polymers, where the ratio of the average size of the polymer to that of the colloid is approximately 0.063. Unlike what has been reported previously for mixtures with somewhat lower colloid polydispersity, the addition of polymers does not expand the fluid-solid coexistence region. Instead, we find a region of fluid-solid coexistence which has an approximately constant width but an unexpected re-entrant shape. We detect the presence of a metastable gas-liquid binodal, which gives rise to two-stepped crystallization kinetics that can be rationalized as the effect of fractionation. Finally, we find that the separation into multiple coexisting solid phases at high colloid volume fractions predicted by equilibrium statistical mechanics is kinetically suppressed before the system reaches dynamical arrest.Comment: 11 pages, 5 figure

Projected free energies for polydisperse phase equilibria

A `polydisperse' system has an infinite number of conserved densities. We give a rational procedure for projecting its infinite-dimensional free energy surface onto a subspace comprising a finite number of linear combinations of densities (`moments'), in which the phase behavior is then found as usual. If the excess free energy of the system depends only on the moments used, exact cloud, shadow and spinodal curves result; two- and multi-phase regions are approximate, but refinable indefinitely by adding extra moments. The approach is computationally robust and gives new geometrical insights into the thermodynamics of polydispersity.Comment: 4 pages, REVTeX, uses multicol.sty and epsf.sty, 1 postscript figure include

Reactive Oxygen Species, SUMOylation, and Endothelial Inflammation

Although the exact mechanism through which NADPH oxidases (Nox's) generate reactive oxygen species (ROS) is still not completely understood, it is widely considered that ROS accumulation is the cause of oxidative stress in endothelial cells. Increasing pieces of evidence strongly indicate the role for ROS in endothelial inflammation and dysfunction and subsequent development of atherosclerotic plaques, which are causes of various pathological cardiac events. An overview for a causative relationship between ROS and endothelial inflammation will be provided in this review. Particularly, a crucial role for specific protein SUMOylation in endothelial inflammation will be presented. Given that SUMOylation of specific proteins leads to increased endothelial inflammation, targeting specific SUMOylated proteins may be an elegant, effective strategy to control inflammation. In addition, the involvement of ROS production in increasing the risk of recurrent coronary events in a sub-group of non-diabetic, post-infarction patients with elevated levels of HDL-cholesterol will be presented with the emphasis that elevated HDL-cholesterol under certain inflammatory conditions can lead to increased incidence of cardiovascular events

Dietary Salt Intake and Mortality in Patients With Type 2 Diabetes

OBJECTIVE: Many guidelines recommend that patients with type 2 diabetes should aim to reduce their intake of salt. However, the precise relationship between dietary salt intake and mortality in patients with type 2 diabetes has not been previously explored. RESEARCH DESIGN AND METHODS: Six hundred and thirty-eight patients attending a single diabetes clinic were followed in a prospective cohort study. Baseline sodium excretion was estimated from 24-h urinary collections (24hU(Na)). The predictors of all-cause and cardiovascular mortality were determined by Cox regression and competing risk modeling, respectively. RESULTS: The mean baseline 24hU(Na) was 184 ± 73 mmol/24 h, which remained consistent throughout the follow-up (intraindividual coefficient of variation [CV] 23 ± 11%). Over a median of 9.9 years, there were 175 deaths, 75 (43%) of which were secondary to cardiovascular events. All-cause mortality was inversely associated with 24hU(Na), after adjusting for other baseline risk factors (P < 0.001). For every 100 mmol rise in 24hU(Na), all-cause mortality was 28% lower (95% CI 6-45%, P = 0.02). After adjusting for the competing risk of noncardiovascular death and other predictors, 24hU(Na) was also significantly associated with cardiovascular mortality (sub-hazard ratio 0.65 [95% CI 0.44-0.95]; P = 0.03). CONCLUSIONS: In patients with type 2 diabetes, lower 24-h urinary sodium excretion was paradoxically associated with increased all-cause and cardiovascular mortality. Interventional studies are necessary to determine if dietary salt has a causative role in determining adverse outcomes in patients with type 2 diabetes and the appropriateness of guidelines advocating salt restriction in this setting

Predicting phase equilibria in polydisperse systems

Many materials containing colloids or polymers are polydisperse: They comprise particles with properties (such as particle diameter, charge, or polymer chain length) that depend continuously on one or several parameters. This review focusses on the theoretical prediction of phase equilibria in polydisperse systems; the presence of an effectively infinite number of distinguishable particle species makes this a highly nontrivial task. I first describe qualitatively some of the novel features of polydisperse phase behaviour, and outline a theoretical framework within which they can be explored. Current techniques for predicting polydisperse phase equilibria are then reviewed. I also discuss applications to some simple model systems including homopolymers and random copolymers, spherical colloids and colloid-polymer mixtures, and liquid crystals formed from rod- and plate-like colloidal particles; the results surveyed give an idea of the rich phenomenology of polydisperse phase behaviour. Extensions to the study of polydispersity effects on interfacial behaviour and phase separation kinetics are outlined briefly.Comment: 48 pages, invited topical review for Journal of Physics: Condensed Matter; uses Institute of Physics style file iopart.cls (included

Relations between lipoprotein(a) concentrations, LPA genetic variants, and the risk of mortality in patients with established coronary heart disease: a molecular and genetic association study

Background: Lipoprotein(a) concentrations in plasma are associated with cardiovascular risk in the general population. Whether lipoprotein(a) concentrations or LPA genetic variants predict long-term mortality in patients with established coronary heart disease remains less clear. Methods: We obtained data from 3313 patients with established coronary heart disease in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. We tested associations of tertiles of lipoprotein(a) concentration in plasma and two LPA single-nucleotide polymorphisms ([SNPs] rs10455872 and rs3798220) with all-cause mortality and cardiovascular mortality by Cox regression analysis and with severity of disease by generalised linear modelling, with and without adjustment for age, sex, diabetes diagnosis, systolic blood pressure, BMI, smoking status, estimated glomerular filtration rate, LDL-cholesterol concentration, and use of lipid-lowering therapy. Results for plasma lipoprotein(a) concentrations were validated in five independent studies involving 10 195 patients with established coronary heart disease. Results for genetic associations were replicated through large-scale collaborative analysis in the GENIUS-CHD consortium, comprising 106 353 patients with established coronary heart disease and 19 332 deaths in 22 studies or cohorts. Findings: The median follow-up was 9·9 years. Increased severity of coronary heart disease was associated with lipoprotein(a) concentrations in plasma in the highest tertile (adjusted hazard radio [HR] 1·44, 95% CI 1·14–1·83) and the presence of either LPA SNP (1·88, 1·40–2·53). No associations were found in LURIC with all-cause mortality (highest tertile of lipoprotein(a) concentration in plasma 0·95, 0·81–1·11 and either LPA SNP 1·10, 0·92–1·31) or cardiovascular mortality (0·99, 0·81–1·2 and 1·13, 0·90–1·40, respectively) or in the validation studies. Interpretation: In patients with prevalent coronary heart disease, lipoprotein(a) concentrations and genetic variants showed no associations with mortality. We conclude that these variables are not useful risk factors to measure to predict progression to death after coronary heart disease is established. Funding: Seventh Framework Programme for Research and Technical Development (AtheroRemo and RiskyCAD), INTERREG IV Oberrhein Programme, Deutsche Nierenstiftung, Else-Kroener Fresenius Foundation, Deutsche Stiftung für Herzforschung, Deutsche Forschungsgemeinschaft, Saarland University, German Federal Ministry of Education and Research, Willy Robert Pitzer Foundation, and Waldburg-Zeil Clinics Isny

Power to identify a genetic predictor of antihypertensive drug response using different methods to measure blood pressure response

<p>Abstract</p> <p>Background</p> <p>To determine whether office, home, ambulatory daytime and nighttime blood pressure (BP) responses to antihypertensive drug therapy measure the same signal and which method provides greatest power to identify genetic predictors of BP response.</p> <p>Methods</p> <p>We analyzed office, home, ambulatory daytime and nighttime BP responses in hypertensive adults randomized to atenolol (N = 242) or hydrochlorothiazide (N = 257) in the Pharmacogenomic Evaluation of Antihypertensive Responses Study. Since different measured BP responses may have different predictors, we tested the "same signal" model by using linear regression methods to determine whether known predictors of BP response depend on the method of BP measurement. We estimated signal-to-noise ratios and compared power to identify a genetic polymorphism predicting BP response measured by each method separately and by weighted averages of multiple methods.</p> <p>Results</p> <p>After adjustment for pretreatment BP level, known predictors of BP response including plasma renin activity, race, and sex were independent of the method of BP measurement. Signal-to-noise ratios were more than 2-fold greater for home and ambulatory daytime BP responses than for office and ambulatory nighttime BP responses and up to 11-fold greater for weighted averages of all four methods. Power to identify a genetic polymorphism predicting BP response was directly related to the signal-to-noise ratio and, therefore, greatest with the weighted averages.</p> <p>Conclusion</p> <p>Since different methods of measuring BP response to antihypertensive drug therapy measure the same signal, weighted averages of the BP responses measured by multiple methods minimize measurement error and optimize power to identify genetic predictors of BP response.</p