Phenanthrene removal in unsaturated soils treated by electrokinetics with different surfactants—Triton X-100 and rhamnolipid

In this study, the remediation performance of electrokinetic (EK) technology integrated with different surfactants for removing phenanthrene from unsaturated soils was investigated. A synthetic surfactant (Triton X-100) and a biosurfactant (rhamnolipid) were used to enhance phenanthrene solubility and removal efficiency during EK process. Results indicate that the electro-osmotic flow (EOF) rate in the rhamnolipid system is higher than that in Triton X-100. Using the EK technology for the removal of phenanthrene in the presence of rhamnolipid was more efficient than in the presence of Triton X-100. In addition to the transport mechanism of phenanthrene in EK system, the presence of rhamnolipid may promote microbial growth in the soil–water system and bring about biodegradation of phenanthrene. A diffusion–advection–sorption (DAS) model was solved by MATLAB, based on the linear sorption isotherm at the non-equilibrium condition, which is feasible to simulate the movement of phenanthrene during the EK + Triton X-100 treatment.     

Modified Boussinesq''s equations for nonuniform tire loading

Hypotheses from elasticity theory were used for modeling stress distribution in a semi-infinite-homogeneous medium when a point load was applied on its surface. A Concentration factor coefficient was introduced to adapt the equations to the characteristics of the investigated soil. An expression for continuous load distributions and variations in the geometry of the contact area between soil and tire were obtained by means of the superposition principle. Some simulations for different areas and load distributions are discussed and compared with field measurements.     

Updating beliefs about variables given new information on how those variables relate

Bayesian techniques specify how to update beliefs about a variable given information on that variable or related variables. In many cases, statistical analyses also provide information about the relationship between variables, but the Borel Paradox prohibits many natural ways of updating beliefs conditioned on information about a relationship. This paper presents a method by which beliefs can be updated without violating the Borel Paradox under certain circumstances. We apply our approach to relationships specified by a statistical model (i.e., regression), and relationships described by statistical simulation.     

Modeling the effect of external electric field and current on the stochastic dynamics of ATPase nano-biomolecular motors

The rotary motion of the F₀ part of the F₀F₁-ATPase motor that synthesizes the ATP molecules used by the intracellular stepping motors, such as kinesins, is modeled within a stochastically fluctuating medium via the application of the Langevin dynamics wherein the random intramembrane fluctuations are represented by a white noise. We have investigated the influence of an applied electric field and an applied electric current on this rotary motion, and the subsequent production rate of the ATP molecules. It is seen that the application of a field, or a current, changes both the elastic behavior of the cell membrane and the transmembrane potential. These changes in turn transform the dynamics of the F₀ part of the motor. We have found that at low fields, the role of transmembrane potential becomes significant in the production rate of the ATP molecules, whereas at high fields the changes induced in the surface tension of the membrane also contribute to the production rate of the ATP.