pH Sensitive surfactants from lysine: assessment of their cytotoxicity and environmental behavior

The toxicity and environmental behavior of new pH-sensitive surfactants from lysine are presented. Three different chemical structures are studied: surfactants with one amino acid and one alkyl chain, surfactants with two amino acids on the polar head and one alkyl chain, and gemini surfactants. The pH sensitivity of these compounds can be tuned by modifying their chemical structures. Cytotoxicity has been evaluated using erythrocytes and fibroblast cells. The toxic effects against these cells depend on the hydrophobicity of the molecules as well as their cationic charge density. The effect of hydrophobicity and cationic charge density on toxicity is different for each type of cells. For erythrocytes, the toxicity increases as hydrophobicity and charge density increases. Nevertheless, for fibroblasts cationic charge density affects cytotoxicity in the opposite way: the higher charge density, the lower the toxicity. The effect of the pH on hemolysis has been evaluated in detail. The aquatic toxicity was established using Daphnia magna. All surfactants yielded EC50 values considerably higher than that reported for cationic surfactants based on quaternary ammonium groups. Finally, their biodegradability was evaluated using the CO2 headspace test (ISO 14593). These lysine derivatives showed high levels of biodegradation under aerobic conditions and can be classified as"readily biodegradable compounds".

Analytic behavior of the QED polarizability function at finite temperature

We revisit the analytical properties of the static quasi-photon polarizability function for an electron gas at finite temperature, in connection with the existence of Friedel oscillations in the potential created by an impurity. In contrast with the zero temperature case, where the polarizability is an analytical function, except for the two branch cuts which are responsible for Friedel oscillations, at finite temperature the corresponding function is non analytical, in spite of becoming continuous everywhere on the complex plane. This effect produces, as a result, the survival of the oscillatory behavior of the potential. We calculate the potential at large distances, and relate the calculation to the non-analytical properties of the polarizability.

Chaotic dynamics and team effectiveness: evidence from professional basketball

Considering teams as complex adaptive systems (CAS) this study deals with changes in team effectiveness over time in a specific context: professional basketball. The sample comprised 23 basketball teams whose outcomes were analysed over a 12-year period according to two objective measures. The results reveal that all the teams showed chaotic dynamics, one of the key characteristics of CAS. A relationship was also found between teams showing low-dimensional chaotic dynamics and better outcomes, supporting the idea of healthy variability in organizational behaviour. The stability of the squad was likewise found to influence team outcomes, although it was not associated with the chaotic dynamics in team effectiveness. It is concluded that studying teams as CAS enables fluctuations in team effectiveness to be explained, and that the techniques derived from nonlinear dynamical systems, developed specifically for the study of CAS, are useful for this purpose.

Spatial behavior in groups: an agent-based approach

We present an agent-based model with the aim of studying how macro-level dynamics of spatial distances among interacting individuals in a closed space emerge from micro-level dyadic and local interactions. Our agents moved on a lattice (referred to as a room) using a model implemented in a computer program called P-Space in order to minimize their dissatisfaction, defined as a function of the discrepancy between the real distance and the ideal, or desired, distance between agents. Ideal distances evolved in accordance with the agent's personal and social space, which changed throughout the dynamics of the interactions among the agents. In the first set of simulations we studied the effects of the parameters of the function that generated ideal distances, and in a second set we explored how group macrolevel behavior depended on model parameters and other variables. We learned that certain parameter values yielded consistent patterns in the agents' personal and social spaces, which in turn led to avoidance and approaching behaviors in the agents. We also found that the spatial behavior of the group of agents as a whole was influenced by the values of the model parameters, as well as by other variables such as the number of agents. Our work demonstrates that the bottom-up approach is a useful way of explaining macro-level spatial behavior. The proposed model is also shown to be a powerful tool for simulating the spatial behavior of groups of interacting individuals.