Analysis of Polychlorinated Biphenyl (PCB) Loading Trends in Lake Michigan

PCB concentrations in coregonid fishes (bloater chubs) collected from Lake Michigan between 1972 and 1980 are used to infer an historical loading trend for polychlorinated biphenyls (PCBs). A mass balance model was developed to describe the dynamics of PCBs by assuming that historical fish concentrations are proportional to concurrent water column concentrations of PCB. The validity of this assumption is strengthened, since the data represent a single species of fish (a pelagic feeder), a specific age class of that species, and a single laboratory performing the collections and analysis of the data. The results of model analysis indicate that PCB loading to Lake Michigan during the period of observation can be described by a linearly decreasing trend. The calibrated model also forecasts the response of selected fish species to various loading scenarios. Forecast results indicate that a continuously decreasing load will result in compliance with U.S. and Canadian guideline value for human consumption by 1987. However, should PCB loadings not continue to decrease, compliance with the proposed U.S. and extant Canadian guideline of 2.0 mg/kg is doubtful. Forecast accuracy may be improved by the availability of precise measurements of water:fish distribution coefficients.     

Unequal death in T helper cell (Th)1 and Th2 effectors: Th1, but not Th2, effectors undergo rapid Fas/FasL-mediated apoptosis

T helper cell (Th) 1, but not Th2, effectors undergo rapid Fas/Fas ligand (FasL)-mediated, activation-induced cell death upon restimulation with antigen. Unequal apoptosis is also observed without restimulation, after a longer lag period. Both effectors undergo delayed apoptosis induced by a non-Fas-mediated pathway. When Th1 and Th2 effectors are co-cultured, Th2 effectors survive preferentially, suggesting the responsible factor(s) is intrinsic to each population. Both Th1 and Th2 effectors express Fas and FasL, but only Th2 effectors express high levels of FAP-1, a Fas-associated phosphatase that may act to inhibit Fas signaling. The rapid death of Th1 effectors leading to selective Th2 survival provides a novel mechanism for differential regulation of the two subsets.     

Hybrid consensus theoretic classification

Hybrid classification methods based on consensus from several data sources are considered. Each data source is at first treated separately and modeled using statistical methods. Then weighting mechanisms are used to control the influence of each data source in the combined classification. The weights are optimized in order to improve the combined classification accuracies. Both linear and nonlinear optimization methods are considered and used in classification of two multisource remote sensing and geographic data sets. A nonlinear method which utilizes a neural network gives excellent experimental results. The hybrid statistical/neural method outperforms all other methods in terms of test accuracies in the experiments     

Influence of surface preparation on the rotating flexural fatigue of Mg-PSZ

Specimens of Mg-PSZ were given three different surface preparations prior to testing in rotating flexural fatigue. The preparation consisted of precise grinding with relatively coarse (55 to 80 m) diamond-impregnated wheels along axial and radial directions as well as by polishing. Only minor differences were noted in the strength-number of cycles to failure (S-N) data, with radial grinding being more deleterious. The data showed considerable scatter; however, from the results the stress corrosion exponents were typically between 65 and 92. Failure origins were often associated with the presence of flaws or pores near the surface.     

Comments on Samal and Henderson: “Parallel consistent labeling algorithms”

Samal and Henderson claim that any parallel algorithm for enforcing arc consistency in the worst case must have (na) sequential steps, wheren is the number of nodes, anda is the number of labels per node. We argue that Samal and Henderson's argument makes assumptions about how processors are used and give a counterexample that enforces arc consistency in a constant number of steps usingO(n[su2a²2^na) processors. It is possible that the lower bound holds for a polynomial number of processors; if such a lower bound were to be proven it would answer an important open question in theoretical computer science concerning the relation between the complexity classesP andNC. The strongest existing lower bound for the arc consistency problem states that it cannot be solved in polynomial log time unlessP=NC.     

Relation of transformation temperature to the fracture toughness of transformation-toughened ceramics

The stress induced tetragonal to monoclinic ZrO₂ martensitic transformation contribution to fracture toughness is described in terms of the required external strain energy and the thermo-dynamic stability of the constrained tetragonal phase. The strain energy, derived from an externally applied stress acting on the main crack, required to achieve transformation toughening is shown to be a function of the term (T - M _s) whereT is the test temperature andM _s is the martensite start temperature for the case ofT > M _s. Thus for a givenT (T > M _s), the transformation toughening component increases asM _s approachesT and for a fixedM _s, the toughness decreases asT increases. Experimental data for partially stabilized zirconia ceramics confirm these results and show that increasing tetragonal precipitate size is the primary feature which affects an increase inM _s. In the case ofT M _s, autotransformation occurs, resulting in decreasing toughness with decrease inT due to a continuous loss in the tetragonal phase content. A temperature region is thus obtained over which transformation toughening exhibits a maximum in its contribution. The temperatures over which this occurs then is shown to be dependent on theM _s temperature of the material.     

Digging Deep into the Data Mine with DataMiningGrid

The growing computerization in modern knowledge and technology sectors is generating huge volumes of electronically stored data. Data mining technology is often employed to make sense of these data. However, as modern data mining applications increase in complexity, so do their demands for resources. Grid computing is one of several emerging networked computing paradigms promising to meet the requirements of heterogeneous, large-scale and distributed data mining applications. Despite this promise, there are still too many issues to be resolved before grid technology is commonly applied to large-scale data mining tasks. To address some of these issues, we developed the DataMiningGrid system, which principally differs from similar systems by its ability to integrate a diverse set of programs and application scenarios within a single framework. The system's key features include high performance and scalability, sophisticated support for relevant standards, different user types, and flexible extensibility. The software is available as open source.