Manufacturing Metallic Parts with Designed Mesostructure via Three-Dimensional Printing of Metal Oxide Powder

Cellular materials, metallic bodies with gaseous voids, are a promising class of materials that offer high strength accompanied by a relatively low mass. In this paper, the authors investigate the use of ThreeDimensional Printing (3DP) to manufacture metallic cellular materials by selectively printing binder into a bed of metal oxide ceramic powder. The resulting green part undergoes a thermal chemical post-process in order to convert it to metal. As a result of their investigation, the authors are able to create cellular materials made of maraging steel that feature wall sizes as small as 400 µm and angled trusses and channels that are 1 mm in diameter.Mechanical Engineerin

Fuzzy ART: An Adaptive Resonance Algorithm for Rapid, Stable Classification of Analog Patterns

The Fuzzy ART system introduced herein incorporates computations from fuzzy set theory into ART 1. For example, the intersection (n) operator used in ART 1 learning is replaced by the MIN operator (A) of fuzzy set theory. Fuzzy ART reduces to ART 1 in response to binary input vectors, but can also learn stable categories in response to analog input vectors. In particular, the MIN operator reduces to the intersection operator in the binary case. Learning is stable because all adaptive weights can only decrease in time. A preprocessing step, called complement coding, uses on-cell and off-cell responses to prevent category proliferation. Complement coding normalizes input vectors while preserving the amplitudes of individual feature activations.Air Force Office of Scientific Research (90-0175, 90-0128); Army Research Office (DAAL-03-88-K0088); BP (89-A-1204); Defense Advanced Research Projects Agency (90-0083); National Science Foundation (IRI-90-00530

A Neural Network Realization of Fuzzy ART

A neural network realization of the fuzzy Adaptive Resonance Theory (ART) algorithm is described. Fuzzy ART is capable of rapid stable learning of recognition categories in response to arbitrary sequences of analog or binary input patterns. Fuzzy ART incorporates computations from fuzzy set theory into the ART 1 neural network, which learns to categorize only binary input patterns, thus enabling the network to learn both analog and binary input patterns. In the neural network realization of fuzzy ART, signal transduction obeys a path capacity rule. Category choice is determined by a combination of bottom-up signals and learned category biases. Top-down signals impose upper bounds on feature node activations.British Petroleum (89-A-1204); Defense Advanced Research Projects Agency (90-0083); National Science Foundation (IRI 90-00530); Office of Naval Research (N00014-91-J-4100); Air Force Office of Scientific Research (90-0175

Is the US Population Behaving Healthier?

In the past few decades, some measures of population risk have improved, while others have deteriorated. Understanding the health of the population requires integrating these different trends. We compare the risk factor profile of the population in the early 1970s with that of the population in the early 2000s and consider the impact of a continuation of recent trends. Despite substantial increases in obesity in the past three decades, the overall population risk profile is healthier now than it was formerly. For the population aged 25-74, the 10 year probability of death fell from 9.8 percent in 1971-75 to 8.4 percent in 1999-2002. Among the population aged 55-74, the 10 year risk of death fell from 25.7 percent to 21.7 percent. The largest contributors to these changes were the reduction in smoking and better control of blood pressure. Increased obesity increased risk, but not by as large a quantitative amount. In the future, however, increased obesity may play a larger role than continued reductions in smoking. We estimate that a continuation of trends over the past three decades to the next three decades might offset about a third of the behavioral improvements witnessed in recent years.

Fuzzy ARTMAP: A Neural Network Architecture for Incremental Supervised Learning of Analog Multidimensional Maps

A new neural network architecture is introduced for incremental supervised learning of recognition categories and multidimensional maps in response to arbitrary sequences of analog or binary input vectors. The architecture, called Fuzzy ARTMAP, achieves a synthesis of fuzzy logic and Adaptive Resonance Theory (ART) neural networks by exploiting a close formal similarity between the computations of fuzzy subsethood and ART category choice, resonance, and learning. Fuzzy ARTMAP also realizes a new Minimax Learning Rule that conjointly minimizes predictive error and maximizes code compression, or generalization. This is achieved by a match tracking process that increases the ART vigilance parameter by the minimum amount needed to correct a predictive error. As a result, the system automatically learns a minimal number of recognition categories, or "hidden units", to met accuracy criteria. Category proliferation is prevented by normalizing input vectors at a preprocessing stage. A normalization procedure called complement coding leads to a symmetric theory in which the MIN operator (Λ) and the MAX operator (v) of fuzzy logic play complementary roles. Complement coding uses on-cells and off-cells to represent the input pattern, and preserves individual feature amplitudes while normalizing the total on-cell/off-cell vector. Learning is stable because all adaptive weights can only decrease in time. Decreasing weights correspond to increasing sizes of category "boxes". Smaller vigilance values lead to larger category boxes. Improved prediction is achieved by training the system several times using different orderings of the input set. This voting strategy can also be used to assign probability estimates to competing predictions given small, noisy, or incomplete training sets. Four classes of simulations illustrate Fuzzy ARTMAP performance as compared to benchmark back propagation and genetic algorithm systems. These simulations include (i) finding points inside vs. outside a circle; (ii) learning to tell two spirals apart; (iii) incremental approximation of a piecewise continuous function; and (iv) a letter recognition database. The Fuzzy ARTMAP system is also compared to Salzberg's NGE system and to Simpson's FMMC system.British Petroleum (89-A-1204); Defense Advanced Research Projects Agency (90-0083); National Science Foundation (IRI 90-00530); Office of Naval Research (N00014-91-J-4100); Air Force Office of Scientific Research (90-0175

A Proposed Method for Monitoring U.S. Population Health: Linking Symptoms, Impairments, and Health Ratings

We propose a method of quantifying non-fatal health on a 0-1 QALY scale that details the impact of specific symptoms and impairments and is not based on ratings of counterfactual scenarios. Measures of general health status are regressed on health impairments and symptoms in different domains, using ordered probit and ordinary least squares regression. This yields estimates of their effects analogous to disutility weights, and accounts for complex non-additive relationships. Health measures used include self-rated health status on a 5-point scale, EuroQol 5D (EQ-5D) scores, and ratings of current health using a 0-100 rating scale and a time-tradeoff. Data are from the nationally representative Medical Expenditure Panel Survey (MEPS) year 2002 (N=34,615), with validation in an independent sample from MEPS 2000 (N=21,067) and among 1420 adults age 45-89 in the Beaver Dam Health Outcomes Study. Decrement weights for symptoms and impairments are used to derive estimates of overall health-related quality of life, laying the groundwork for a detailed national summary measure of health. To purchase a copy of the earlier version of this paper, please contact the Working Papers department directly at (617) 588 1405.

Value of Medical Innovation in the United States: 1960-2000

Background: The increased use of medical therapies has led to increased medical costs. To provide insight into the value of this increased spending, we compared gains in life expectancy with the increased costs of care from 1960 through 2000. Methods: We estimated life expectancy in 1960, 1970, 1980, 1990, and 2000 for four age groups. To control for the influence of nonmedical factors on survival, we assumed in our base-case analysis that 50 percent of the gains were due to medical care. We compared the adjusted increases in life expectancy with the lifetime cost of medical care in the same years. Results: From 1960 through 2000, the life expectancy for newborns increased by 6.97 years, lifetime medical spending adjusted for inflation increased by approximately $69,000, and the cost per year of life gained was$19,900. The cost increased from $7,400 per year of life gained in the 1970s to$36,300 in the 1990s. The average cost per year of life gained in 1960–2000 was approximately $31,600 at 15 years of age,$53,700 at 45 years of age, and $84,700 at 65 years of age. At 65 years of age, costs rose more rapidly than did life expectancy: the cost per year of life gained was$121,000 between 1980 and 1990 and $145,000 between 1990 and 2000. Conclusions: On average, the increases in medical spending since 1960 have provided reasonable value. However, the spending increases in medical care for the elderly since 1980 are associated with a high cost per year of life gained. The national focus on the rise in medical spending should be balanced by attention to the health benefits of this increased spending.Economic

Forecasting the Effects of Obesity and Smoking on U.S. Life Expectancy

Background: While increases in obesity over the past 30 years have adversely affected population health, there have been concomitant improvements due to reductions in smoking. Better understanding of the joint effects of these trends on longevity and quality of life will help policymakers target resources more efficiently. Methods: For each year from 2005 to 2020, we forecast life expectancy and qualityadjusted life expectancy for a representative 18 year old, assuming a continuation of past trends in smoking from the National Health Interview Survey (1978-79, 1990-91 and 2004-06), and past trends in body-mass index (BMI) from the National Health and Nutrition Examination Survey (1971-75, 1998-1994, and 2003-06). The 2003 Medical Expenditure Panel Survey was used to examine the effects of smoking and BMI on health-related quality of life. Results: The negative effects of increasing BMI overwhelmed the positive effects of declines in smoking in multiple scenarios. In the base case, increases in the remaining life expectancy of a typical 18 year old are held back by 0.71 years or 0.91 quality-adjusted years between 2005 and 2020. If all U.S. adults became normal weight non-smokers by 2020, LE is forecast to increase by 3.76 life years or 5.16 quality-adjusted years. Conclusions: If past obesity trends continue unchecked, the negative impact on U.S. population health is forecast to overtake the positive effect from declining smoking rates, which could erode the pattern of steady gains in health experienced since early in the 20th century.Economic