Is exposure to secondhand smoke associated with cognitive parameters of children and adolescents?—a systematic literature review

PURPOSE: Despite the known association of second hand smoke (SHS) with increased risk of ill health and mortality, the effects of SHS exposure on cognitive functioning in children and adolescents are unclear. Through a critical review of the literature we sought to determine whether a relationship exists between these variables. METHODS: The authors systematically reviewed articles (dated 1989–2012) that investigated the association between SHS exposure (including in utero due to SHS exposure by pregnant women) and performance on neurocognitive and academic tests. Eligible studies were identified from searches of Web of Knowledge, MEDLINE, Science Direct, Google Scholar, CINAHL, EMBASE, Zetoc, and Clinicaltrials.gov. RESULTS: Fifteen articles were identified, of which 12 showed inverse relationships between SHS and cognitive parameters. Prenatal SHS exposure was inversely associated with neurodevelopmental outcomes in young children, whereas postnatal SHS exposure was associated with poor academic achievement and neurocognitive performance in older children and adolescents. Furthermore, SHS exposure was associated with an increased risk of neurodevelopmental delay. CONCLUSIONS: Recommendations should be made to the public to avoid sources of SHS and future research should investigate interactions between SHS exposure and other risk factors for delayed neurodevelopment and poor cognitive performance

Aggregation and Interfacial Behavior of Charged Surfactants in Ionic Liquids

Room-temperature ionic liquids (ILs) exhibit a unique set of properties, leading to opportunities for numerous applications such as green solvents, batteries and lubricants. Their properties can be greatly tuned and controlled by addition of surfactants. It is therefore critical to obtain a better understanding of the aggregation and interfacial behavior of surfactants within ILs. Firstly, the phase diagram and aggregation isotherms of surfactants in several distinct ILs were investigated by solubility and tensiometry. A connection between solubility of the surfactant and the physical properties of the underlying ionic liquid was established. We found that the interfacial energy was crucial in determining aggregation behavior while electrostatic interactions could be largely ignored. This finding could provide the general prediction of solubility and the first indication of how to choose ILs with desired properties. Secondly, this study was extended to include mixtures of cationic and anionic surfactants where our data further demonstrated near-complete charge screening. The critical micelle concentration (CMC) and mixed micelle composition were found to be close to ideal behavior. This so-called charge screening in IL is in sharp contrast to that of aqueous solution and can be explained by Debye theory. Moreover, our pulsed-field gradient spin-echo (PGSE)-NMR data confirmed the existence of micelle formation and showed evidence that the IL anion partially incorporates into surfactant micelles, resulting in slower diffusion when the surfactant concentration is above the CMC. Lastly, through use of X-ray photoelectron spectroscopy (XPS), the roles of surfactant alkyl chain length, concentration, and probing depth on interfacial properties were investigated. Depending on the chain length and concentration, surfactants can alter the IL interface to varying extents, highlighting a simple route to manipulate interfacial properties. XPS is further demonstrated to be a direct measurement of the surface activity and ion-exchange behavior in surfactant-ionic liquid system. The results here give insight into the interaction between solutes and IL solvents and the nature of self-assembly of surfactants in ILs. This study could significantly broaden the potential application of ionic liquids such as novel solvents for protein storage and electrolytes for Li-ion batteries

Wide-Area Measurement Application and Power System Dynamics

Frequency monitoring network (FNET) is a GPS-synchronized distribution-level phasor measurement system. It is a powerful synchronized monitoring network for large-area power systems that provides significant information and data for power system situational awareness, real time and post-event analysis, and other important aspects of bulk systems. This work explored FNET measurements and utilized them for different applications and power system analysis. An island system was built and validated with FNET measurements to study the stability of the OTEC integration. FNET measurements were also used to validate a large system model like the U.S. Eastern Interconnection. It tries to match the simulation result and frequency measurement of a real event by adjusting the simulation model. The system model is tuned with the combination of different impact factors for different confirmed actual events, and some general rules and specific tuning quantities were concluded from the model validation process. This work also investigated the behavior of the power system frequency during large-scale, synchronous societal events, like the World Cup, Super Bowl and Royal Wedding. It is apparent that large groups of people engaging in the same event at roughly the same time can have significant impacts on the power grid frequency. The systematic analysis of the accumulating and statistical FNET frequency data presents an incisive point of view on the power grid frequency behavior during such events. To better understanding of system events recorded by FNET, a visualization tool was developed to visualize major events that occurred in the North American power grid. The measurement plot combined with the geographical contour map provides intuitive visualization of the event. Finally, the EI system was simplified and clustered into four groups based on FNET measurements and simulation results of generator trip cases. The generation and load capacity of each cluster was calculated based on the clustering result and simulation model, and a flow diagram of this simplified EI system was demonstrated with clusters and power flow between them

On Mutual Fund Investment Styles

We provide an exploratory investigation of mutual funds' investment styles. Funds' styles tend to cluster around a broad market benchmark. When funds deviate from the benchmark they are more likely to favor growth stocks with good past performance. There is some consistency in styles, although funds with poor past performance are more likely to change styles. Some evidence suggests that growth funds have better style-adjusted performance than value funds. The results are not sensitive to style identification procedure, but an approach based on fund portfolio characteristics performs better in predicting future fund returns.

Autonomous Deployment of a Solar Panel Using an Elastic Origami and Distributed Shape Memory Polymer Actuators

Deployable mechanical systems such as space solar panels rely on the intricate stowage of passive modules, and sophisticated deployment using a network of motorized actuators. As a result, a significant portion of the stowed mass and volume are occupied by these support systems. An autonomous solar panel array deployed using the inherent material behavior remains elusive. In this work, we develop an autonomous self-deploying solar panel array that is programmed to activate in response to changes in the surrounding temperature. We study an elastic "flasher" origami sheet embedded in a circle of scissor mechanisms, both printed with shape memory polymers. The scissor mechanisms are optimized to provide the maximum expansion ratio while delivering the necessary force for deployment. The origami sheet is also optimized to carry the maximum number of solar panels given space constraints. We show how the folding of the "flasher" origami exhibits a bifurcation behavior resulting in either a cone or disk shape both numerically and in experiments. A folding strategy is devised to avoid the undesired cone shape. The resulting design is entirely 3D printed, achieves an expansion ratio of 1000% in under 40 seconds, and shows excellent agreement with simulation prediction both in the stowed and deployed configurations.Comment: 12 pages, 12 figure