ART 2-A: An Adaptive Resonance Algorithm for Rapid Category Learning and Recognition

This article introduces ART 2-A, an efficient algorithm that emulates the self-organizing pattern recognition and hypothesis testing properties of the ART 2 neural network architecture, but at a speed two to three orders of magnitude faster. Analysis and simulations show how the ART 2-A systems correspond to ART 2 dynamics at both the fast-learn limit and at intermediate learning rates. Intermediate learning rates permit fast commitment of category nodes but slow recoding, analogous to properties of word frequency effects, encoding specificity effects, and episodic memory. Better noise tolerance is hereby achieved without a loss of learning stability. The ART 2 and ART 2-A systems are contrasted with the leader algorithm. The speed of ART 2-A makes practical the use of ART 2 modules in large-scale neural computation.BP (89-A-1204); Defense Advanced Research Projects Agency (90-0083); National Science Foundation (IRI-90-00530); Air Force Office of Scientific Research (90-0175, 90-0128); Army Research Office (DAAL-03-88-K0088

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

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

Hospitalization Rates for Coronary Heart Disease in Relation to Residence Near Areas Contaminated with Persistent Organic Pollutants and Other Pollutants

Exposure to environmental pollutants may contribute to the development of coronary heart disease (CHD). We determined the ZIP codes containing or abutting each of the approximately 900 hazardous waste sites in New York and identified the major contaminants in each. Three categories of ZIP codes were then distinguished: those containing or abutting sites contaminated with persistent organic pollutants (POPs), those containing only other types of wastes (“other waste”), and those not containing any identified hazardous waste site (“clean”). Effects of residence in each of these ZIP codes on CHD and acute myocardial infarction (AMI) hospital discharge rates were assessed with a negative binomial model, adjusting for age, sex, race, income, and health insurance coverage. Patients living in ZIP codes contaminated with POPs had a statistically significant 15.0% elevation in CHD hospital discharge rates and a 20.0% elevation in AMI discharge rates compared with clean ZIP codes. In neither of the comparisons were rates in other-waste sites significantly greater than in clean sites. In a subset of POP ZIP codes along the Hudson River, where average income is higher and there is less smoking, better diet, and more exercise, the rate of hospitalization for CHD was 35.8% greater and for AMI 39.1% greater than in clean sites. Although the cross-sectional design of the study prevents definite conclusions on causal inference, the results indirectly support the hypothesis that living near a POP-contaminated site constitutes a risk of exposure and of development of CHD and AMI

The dust, planetesimals and planets of HD 38529

HD 38529 is a post-main sequence G8III/IV star (3.5 Gyr old) with a planetary system consisting of at least two planets having Msin(i) of 0.8 MJup and 12.2 MJup, semimajor axes of 0.13 AU and 3.74 AU, and eccentricities of 0.25 and 0.35, respectively. Spitzer observations show that HD 38529 has an excess emission above the stellar photosphere, with a signal-to-noise ratio (S/N) at 70 micron of 4.7, a small excess at 33 micron (S/N=2.6) and no excess <30 micron. We discuss the distribution of the potential dust-producing planetesimals from the study of the dynamical perturbations of the two known planets, considering in particular the effect of secular resonances. We identify three dynamically stable niches at 0.4-0.8 AU, 20-50 AU and beyond 60 AU. We model the spectral energy distribution of HD 38529 to find out which of these niches show signs of harboring dust-producing plantesimals. The secular analysis, together with the SED modeling resuls, suggest that the planetesimals responsible for most of the dust emission are likely located within 20-50 AU, a configuration that resembles that of the Jovian planets + Kuiper Belt in our Solar System. Finally, we place upper limits (8E-6 lunar masses of 10 micron particles) to the amount of dust that could be located in the dynamically stable region that exists between the two planets (0.25--0.75 AU).Comment: 23 pages, including 1 table and 5 figures. Accepted for publication in Ap

Debris Disks of Members of the Blanco 1 Open Cluster

We have used the Spitzer Space Telescope to obtain Multiband Imaging Photometer for Spitzer (MIPS) 24 um photometry for 37 members of the ~100 Myr old open cluster Blanco 1. For the brightest 25 of these stars (where we have 3sigma uncertainties less than 15%), we find significant mid-IR excesses for eight stars, corresponding to a debris disk detection frequency of about 32%. The stars with excesses include two A stars, four F dwarfs and two G dwarfs. The most significant linkage between 24 um excess and any other stellar property for our Blanco 1 sample of stars is with binarity. Blanco 1 members that are photometric binaries show few or no detected 24 um excesses whereas a quarter of the apparently single Blanco 1 members do have excesses. We have examined the MIPS data for two other clusters of similar age to Blanco 1 -- NGC 2547 and the Pleiades. The AFGK photometric binary star members of both of these clusters also show a much lower frequency of 24 um excesses compared to stars that lie near the single-star main sequence. We provide a new determination of the relation between V-Ks color and Ks-[24] color for main sequence photospheres based on Hyades members observed with MIPS. As a result of our analysis of the Hyades data, we identify three low mass Hyades members as candidates for having debris disks near the MIPS detection limit.Comment: Accepted to Ap

Risk-Based Consumption Advice for Farmed Atlantic and Wild Pacific Salmon Contaminated with Dioxins and Dioxin-like Compounds

We reported recently that several organic contaminants occurred at elevated concentrations in farmed Atlantic salmon compared with concentrations of the same contaminants in wild Pacific salmon [Hites et al. Science 303:226–229 (2004)]. We also found that polychlorinated biphenyls (PCBs), toxaphene, dieldrin, dioxins, and polybrominated diphenyl ethers occurred at higher concentrations in European farm-raised salmon than in farmed salmon from North and South America. Health risks (based on a quantitative cancer risk assessment) associated with consumption of farmed salmon contaminated with PCBs, toxaphene, and dieldrin were higher than risks associated with exposure to the same contaminants in wild salmon. Here we present information on cancer and noncancer health risks of exposure to dioxins in farmed and wild salmon. The analysis is based on a tolerable intake level for dioxin-like compounds established by the World Health Organization and on risk estimates for human exposure to dioxins developed by the U.S. Environmental Protection Agency. Consumption of farmed salmon at relatively low frequencies results in elevated exposure to dioxins and dioxin-like compounds with commensurate elevation in estimates of health risk

Validation of methods for converting the original Disease Activity Score (DAS) to the DAS28

© The Author(s) 2018.The Disease Activity Score (DAS) is integral in tailoring the clinical management of rheumatoid arthritis (RA) patients and is an important measure in clinical research. Different versions have been developed over the years to improve reliability and ease of use. Combining the original DAS and the newer DAS28 data in both contemporary and historical studies is important for both primary and secondary data analyses. As such, a methodologically robust means of converting the old DAS to the new DAS28 measure would be invaluable. Using data from The Early RA Study (ERAS), a sub-sample of patients with both DAS and DAS28 data were used to develop new regression imputation formulas using the total DAS score (univariate), and using the separate components of the DAS score (multivariate). DAS were transformed to DAS28 using an existing formula quoted in the literature, and the newly developed formulas. Bland and Altman plots were used to compare the transformed DAS with the recorded DAS28 to ascertain levels of agreement. The current transformation formula tended to overestimate the true DAS28 score, particularly at the higher end of the scale. A formula which uses all separate components of the DAS was found to estimate the scores with a higher level of precision. A new formula is proposed that can be used by other early RA cohorts to convert the original DAS to DAS28.Peer reviewedFinal Published versio