Raising argument strength using negative evidence: A constraint on models of induction

Both intuitively, and according to similarity-based theories of induction, relevant evidence raises argument strength when it is positive and lowers it when it is negative. In three experiments, we tested the hypothesis that argument strength can actually increase when negative evidence is introduced. Two kinds of argument were compared through forced choice or sequential evaluation: single positive arguments (e.g., “Shostakovich’s music causes alpha waves in the brain; therefore, Bach’s music causes alpha waves in the brain”) and double mixed arguments (e.g., “Shostakovich’s music causes alpha waves in the brain, X’s music DOES NOT; therefore, Bach’s music causes alpha waves in the brain”). Negative evidence in the second premise lowered credence when it applied to an item X from the same subcategory (e.g., Haydn) and raised it when it applied to a different subcategory (e.g., AC/DC). The results constitute a new constraint on models of induction

Neural network generated parametrizations of deeply virtual Compton form factors

We have generated a parametrization of the Compton form factor (CFF) H based on data from deeply virtual Compton scattering (DVCS) using neural networks. This approach offers an essentially model-independent fitting procedure, which provides realistic uncertainties. Furthermore, it facilitates propagation of uncertainties from experimental data to CFFs. We assumed dominance of the CFF H and used HERMES data on DVCS off unpolarized protons. We predict the beam charge-spin asymmetry for a proton at the kinematics of the COMPASS II experiment.Comment: 16 pages, 5 figure

Highway increases concentrations of toxic metals in giant panda habitat

The Qinling panda subspecies (Ailuropoda melanoleuca qinlingensis) is highly endangered with fewer than 350 individuals inhabiting the Qinling Mountains. Previous studies have indicated that giant pandas are exposed to heavy metals, and a possible source is vehicle emission. The concentrations of Cu, Zn, Mn, Pb, Cr, Ni, Cd, Hg, and As in soil samples collected from sites along a major highway bisecting the panda's habitat were analyzed to investigate whether the highway was an important source of metal contamination. There were 11 sites along a 30-km stretch of the 108th National Highway, and at each site, soil samples were taken at four distances from the highway (0, 50, 100, and 300 m) and at three soil depths (0, 5, 10 cm). Concentrations of all metals except As exceeded background levels, and concentrations of Cu, Zn, Mn, Pb, and Cd decreased significantly with increasing distance from the highway. Geo-accumulation index indicated that topsoil next to the highway was moderately contaminated with Pb and Zn, whereas topsoil up to 300 m away from the highway was extremely contaminated with Cd. The potential ecological risk index demonstrated that this area was in a high degree of ecological hazards, which were also due to serious Cd contamination. And, the hazard quotient indicated that Cd, Pb, and Mn especially Cd could pose the health risk to giant pandas. Multivariate analyses demonstrated that the highway was the main source of Cd, Pb, and Zn and also put some influence on Mn. The study has confirmed that traffic does contaminate roadside soils and poses a potential threat to the health of pandas. This should not be ignored when the conservation and management of pandas is considered