Aerosol characterization and lung deposition of synthesized TiO2 nanoparticles for murine inhalation studies

This study presents a novel exposure protocol for synthesized nanoparticles (NPs). NPs were synthesized in gas phase by thermal decomposition of metal alkoxide vapors in a laminar flow reactor. The exposure protocol was used to estimate the deposition fraction of titanium dioxide (TiO₂) NPs to mice lung. The experiments were conducted at aerosol mass concentrations of 0.8, 7.2, 10.0, and 28.5 mg m^?3. The means of aerosol geometric mobility diameter and aerodynamic diameter were 80 and 124 nm, and the geometric standard deviations were 1.8 and 1.7, respectively. The effective density of the particles was approximately from 1.5 to 1.7 g cm^?3. Particle concentration varied from 4 × 10⁵ cm^?3 at mass concentrations of 0.8 mg m^?3 to 12 × 10⁶ cm^?3 at 28.5 mg m^?3. Particle phase structures were 74% of anatase and 26% of brookite with respective crystallite sized of 41 and 6 nm. The brookite crystallites were approximately 100 times the size of the anatase crystallites. The TiO₂ particles were porous and highly agglomerated, with a mean primary particle size of 21 nm. The specific surface area of TiO₂ powder was 61 m² g^?1. We defined mice respiratory minute volume (RMV) value during exposure to TiO₂ aerosol. Both TiO₂ particulate matter and gaseous by-products affected respiratory parameters. The RMV values were used to quantify the deposition fraction of TiO₂ matter by using two different methods. According to individual samples, the deposition fraction was 8% on an average, and when defined from aerosol mass concentration series, it was 7%. These results show that the exposure protocol can be used to study toxicological effects of synthesized NPs.     

An interactive weight space reduction procedure for nonlinear multiple objective mathematical programming

To make a decision that is defined by multiple, conflicting objectives it is necessary to know the relative importance of the different objectives. In this paper we present an interactive method and the underlying theory for solving multiple objective mathematical programming problems defined by a convex feasible region and concave, continuously differentiable objective functions. The relative importance of the different objectives for a decision maker is elicited by using binary comparisons of objective function vectors. The method is cognitively easy to use and in test problems has rapidly converged to an optimal solution.     

Using box indices in supporting comparison in multiobjective optimization

Because of the conflicting nature of criteria or objectives, solving a multiobjective optimization problem typically requires interaction with a decision maker who can specify preference information related to the objectives in the problem in question. Due to the difficulties of dealing with multiple objectives, the way information is presented plays a very important role. Questions posed to the decision maker must be simple enough and information shown must be easy to understand. For this purpose, visualization and graphical representations can be useful and constitute one of the main tools used in the literature. In this paper, we propose to use box indices to represent information related to different solution alternatives of multiobjective optimization problems involving at least three objectives. Box indices are an intelligible and easy to handle way to represent data. They are based on evaluating the solutions in a natural and rough enough scale in order to let the decision maker easily recognize the main characteristics of a solution at a glance and to facilitate comparison of two or more solutions in an easily understandable way.     

Compressing spatio-temporal trajectories

A trajectory is a sequence of locations, each associated with a timestamp, describing the movement of a point. Trajectory data is becoming increasingly available and the size of recorded trajectories is getting larger. In this paper we study the problem of compressing planar trajectories such that the most common spatio-temporal queries can still be answered approximately after the compression has taken place. In the process, we develop an implementation of the Douglas–Peucker path-simplification algorithm which works efficiently even in the case where the polygonal path given as input is allowed to self-intersect. For a polygonal path of size n, the processing time is O(nlog^kn) for k=2 or k=3 depending on the type of simplification.     

3D printed plano-freeform optics for non-coherent discontinuous beam shaping

Optical Review - The design, fabrication, and characterization of freeform optics for LED-based complex target irradiance distribution are challenging. Here, we investigate a 3D printing technology...     

A comment on the early onset of semi-inclusive scaling in proton-proton collisions

The present experimental evidence for the scaling of multiplicity distributions predicted by Koba, Nielsen and Olesen is examined critically. Our results indicate that the approximate scaling observed experimentally is not necessarily connected with an “early” approach to the asymptotic limit. Some simple models are shown to predict an extremely slow approach to scaling. The possibility of distinguishing between “early” scaling ang the “quasi-scaling” exhibited by these models with experiments at ISR is discussed.     

Comparing Nonsmooth Nonconvex Bundle Methods in Solving Hemivariational Inequalities

Hemivariational inequalities can be considered as a generalization of variational inequalities. Their origin is in nonsmooth mechanics of solid, especially in nonmonotone contact problems. The solution of a hemivariational inequality proves to be a substationary point of some functional, and thus can be found by the nonsmooth and nonconvex optimization methods. We consider two type of bundle methods in order to solve hemivariational inequalities numerically: proximal bundle and bundle-Newton methods. Proximal bundle method is based on first order polyhedral approximation of the locally Lipschitz continuous objective function. To obtain better convergence rate bundle-Newton method contains also some second order information of the objective function in the form of approximate Hessian. Since the optimization problem arising in the hemivariational inequalities has a dominated quadratic part the second order method should be a good choice. The main question in the functioning of the methods is how remarkable is the advantage of the possible better convergence rate of bundle-Newton method when compared to the increased calculation demand.     

Simultaneous measurement of 2 and 3 spins in proton proton elastic scattering at 6 GeVc

The elastic cross section for proton proton scattering at 6 $\text{GeV}\text{c}$ was measured using a 70% polarized beam and a 75% polarized target at the Argonne ZGS. In the range $\text{P}{}_{\mathrm{\perp }}{}^2\text{= 0.5 → 2.0(}\text{GeV}\text{c}\text{)}{}^2$ we obtained small error measurements for the ↑↑, ↓↓ and ↑↓ initial spin states perpendicular to the scattering plane. At P_⊥² = 0.5 we also measured the recoil spin and found that the 5 different cross sections were very unequal.     

NAUTILUS method: An interactive technique in multiobjective optimization based on the nadir point

Most interactive methods developed for solving multiobjective optimization problems sequentially generate Pareto optimal or nondominated vectors and the decision maker must always allow impairment in at least one objective function to get a new solution. The NAUTILUS method proposed is based on the assumptions that past experiences affect decision makers’ hopes and that people do not react symmetrically to gains and losses. Therefore, some decision makers may prefer to start from the worst possible objective values and to improve every objective step by step according to their preferences. In NAUTILUS, starting from the nadir point, a solution is obtained at each iteration which dominates the previous one. Although only the last solution will be Pareto optimal, the decision maker never looses sight of the Pareto optimal set, and the search is oriented so that (s)he progressively focusses on the preferred part of the Pareto optimal set. Each new solution is obtained by minimizing an achievement scalarizing function including preferences about desired improvements in objective function values. NAUTILUS is specially suitable for avoiding undesired anchoring effects, for example in negotiation support problems, or just as a means of finding an initial Pareto optimal solution for any interactive procedure. An illustrative example demonstrates how this new method iterates.     

Melt‐compounded nanocomposites of titanium dioxide atomic‐layer‐deposition‐coated polyamide and polystyrene powders

Polyamide and polystyrene particles were coated with titanium dioxide films by atomic layer deposition (ALD) and then melt‐compounded to form polymer nanocomposites. The rheological properties of the ALD‐created nanocomposite materials were characterized with a melt flow indexer, a melt flow spiral mould, and a rotational rheometer. The results suggest that the melt flow properties of polyamide nanocomposites were markedly better than those of pure polyamide and polystyrene nanocomposites. Such behavior was shown to originate in an uncontrollable decrease in the polyamide molecular weight, likely affected by a high thin‐film impurity content, as shown in gel permeation chromatography (GPC) and scanning electron microscope (SEM) equipped with an energy‐dispersive spectrometer. Transmission electron microscope image showed that a thin film grew on both studied polymer particles, and that subsequent melt‐compounding was successful, producing well dispersed ribbon‐like titanium dioxide with the titanium dioxide filler content ranging from 0.06 to 1.12 wt%. Even though we used nanofillers with a high aspect ratio, they had only a minor effect on the tensile and flexural properties of the polystyrene nanocomposites. The mechanical behavior of polyamide nanocomposites was more complex because of the molecular weight degradation. Our approach here to form polymeric nanocomposites is one way to tailor ceramic nanofillers and form homogenous polymer nanocomposites with minimal work‐related risks in handling powder form nanofillers. However, further research is needed to gauge the commercial potential of ALD‐created nanocomposite materials. Copyright © 2011 John Wiley & Sons, Ltd.