Complex Formation Between Polyelectrolytes and Ionic Surfactants

The interaction between polyelectrolyte and ionic surfactant is of great importance in different areas of chemistry and biology. In this paper we present a theory of polyelectrolyte ionic-surfactant solutions. The new theory successfully explains the cooperative transition observed experimentally, in which the condensed counterions are replaced by ionic-surfactants. The transition is found to occur at surfactant densities much lower than those for a similar transition in non-ionic polymer-surfactant solutions. Possible application of DNA surfactant complex formation to polynucleotide delivery systems is also mentioned.Comment: 5 pages, latex, 3 figure

First order risk assessment for nanoparticle inhalation exposure during injection molding of polypropylene composites and production of tungsten-carbide-cobalt fine powder based upon pulmonary inflammation and surface area dose

AbstractInhalation exposure to low toxicity and biodurable particles has shown to induce polymorphonuclear neutrophilia (PMN) in the lungs, which is a strong indicator for lung inflammation. Recently, Schmid and Stoeger (2016; http://dx.doi.org/10.1016/j.jaerosci.2015.12.006) reviewed mice and rat intratracheal instillation studies and assessed the relation between particles dry powder BET surface area dose and PMN influx for granular biodurable particles (GBPs) and transition metal oxides. In this study, we measured workers alveolar lung deposited surface area (LDSA) concentrations (μm2 cm−3) during injection molding of polypropylene (PP) car bumpers and production of tungsten-carbide-cobalt (WCCo) fine grade powder using diffusion chargers. First order risk assessment was performed by comparing the doses calculated from measured LDSA concentrations during an 8-h work day with the NOEL1/100, the one hundredth of no observed effect level, assigned for GBPs (0.11cm2g−1) and transition metal oxide particles (9×10−3cm2g−1). During the injection molding of PP car bumpers, LDSA concentrations varied from 23 to 39.8μm2cm−3. During 8-h exposure PP, particle doses were at a maximum of 1.4×10−3cm2g−1, which was a factor 100 lower compared to the NOEL1/100 assigned for GBPs. In the WCCo fine powder production plant, the LDSA concentrations were below 18.7μm2cm−3, which corresponds to the 8-h dose of 2.7×10−3cm2g−1. This is 3 times lower than the NOEL1/100 assigned for transition metal oxide particles. The LDSA concentrations were generally low compared to urban background levels of 44.2μm2cm−3 in European cities

First order risk assessment for nanoparticle inhalation exposure during injection molding of polypropylene composites and production of tungsten-carbide-cobalt fine powder based upon pulmonary inflammation and surface area dose

AbstractInhalation exposure to low toxicity and biodurable particles has shown to induce polymorphonuclear neutrophilia (PMN) in the lungs, which is a strong indicator for lung inflammation. Recently, Schmid and Stoeger (2016; http://dx.doi.org/10.1016/j.jaerosci.2015.12.006) reviewed mice and rat intratracheal instillation studies and assessed the relation between particles dry powder BET surface area dose and PMN influx for granular biodurable particles (GBPs) and transition metal oxides. In this study, we measured workers alveolar lung deposited surface area (LDSA) concentrations (μm2 cm−3) during injection molding of polypropylene (PP) car bumpers and production of tungsten-carbide-cobalt (WCCo) fine grade powder using diffusion chargers. First order risk assessment was performed by comparing the doses calculated from measured LDSA concentrations during an 8-h work day with the NOEL1/100, the one hundredth of no observed effect level, assigned for GBPs (0.11cm2g−1) and transition metal oxide particles (9×10−3cm2g−1). During the injection molding of PP car bumpers, LDSA concentrations varied from 23 to 39.8μm2cm−3. During 8-h exposure PP, particle doses were at a maximum of 1.4×10−3cm2g−1, which was a factor 100 lower compared to the NOEL1/100 assigned for GBPs. In the WCCo fine powder production plant, the LDSA concentrations were below 18.7μm2cm−3, which corresponds to the 8-h dose of 2.7×10−3cm2g−1. This is 3 times lower than the NOEL1/100 assigned for transition metal oxide particles. The LDSA concentrations were generally low compared to urban background levels of 44.2μm2cm−3 in European cities

On the fluid-fluid phase separation in charged-stabilized colloidal suspensions

We develop a thermodynamic description of particles held at a fixed surface potential. This system is of particular interest in view of the continuing controversy over the possibility of a fluid-fluid phase separation in aqueous colloidal suspensions with monovalent counterions. The condition of fixed surface potential allows in a natural way to account for the colloidal charge renormalization. In a first approach, we assess the importance of the so called ``volume terms'', and find that in the absence of salt, charge renormalization is sufficient to stabilize suspension against a fluid-fluid phase separation. Presence of salt, on the other hand, is found to lead to an instability. A very strong dependence on the approximations used, however, puts the reality of this phase transition in a serious doubt. To further understand the nature of the instability we next study a Jellium-like approximation, which does not lead to a phase separation and produces a relatively accurate analytical equation of state for a deionized suspensions of highly charged colloidal spheres. A critical analysis of various theories of strongly asymmetric electrolytes is presented to asses their reliability as compared to the Monte Carlo simulations

MDL Convergence Speed for Bernoulli Sequences

The Minimum Description Length principle for online sequence estimation/prediction in a proper learning setup is studied. If the underlying model class is discrete, then the total expected square loss is a particularly interesting performance measure: (a) this quantity is finitely bounded, implying convergence with probability one, and (b) it additionally specifies the convergence speed. For MDL, in general one can only have loss bounds which are finite but exponentially larger than those for Bayes mixtures. We show that this is even the case if the model class contains only Bernoulli distributions. We derive a new upper bound on the prediction error for countable Bernoulli classes. This implies a small bound (comparable to the one for Bayes mixtures) for certain important model classes. We discuss the application to Machine Learning tasks such as classification and hypothesis testing, and generalization to countable classes of i.i.d. models.Comment: 28 page