Parental monitoring moderates the importance of genetic and environmental influences on adolescent smoking.

Although there is a substantial literature on the role of parenting in adolescent substance use, most parenting effects have been small in magnitude and studied outside the context of genetically informative designs, raising debate and controversy about the influence that parents have on their children (D. C. Rowe, 1994). Using a genetically informative twin-family design, the authors studied the role of parental monitoring on adolescent smoking at age 14. Although monitoring had only small main effects, consistent with the literature, there were dramatic moderation effects associated with parental monitoring: At high levels of parental monitoring, environmental influences were predominant in the etiology of adolescent smoking, but at low levels of parental monitoring, genetic influences assumed far greater importance. These analyses demonstrate that the etiology of adolescent smoking varies dramatically as a function of parenting. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Characterization and Response Model of the PPS-M Aerosol Sensor

The Pegasor PPS-M sensor is an electrical aerosol sensor based on diffusion charging and current measurement without particle collection. In this study, the role and effect of each component in the instrument is discussed shortly and the results from a thorough calibration measurements are presented. A comprehensive response model for the operation of the PPS-M sensor was developed based on the calibration results and computational fluid dynamics (CFD) modeling results. The obtained response model, covering the effects of the particle charger, the mobility analyzer, and both diffusion and inertial losses, was tested in the laboratory measurements with polydisperse test aerosols, where a good correlation between the model and the measured results was found.

Copyright 2014 American Association for Aerosol Research     

Phase retrieval via spatial light modulator phase modulation in 4f optical setup: numerical inverse imaging with sparse regularization for phase and amplitude

The 4f optical setup is considered with a wave field modulation by a spatial light modulator located in the focal plane of the first lens. Phase as well as amplitude of the wave field are reconstructed from noisy multiple-intensity observations. The reconstruction is optimal due to a constrained maximum likelihood formulation of the problem. The proposed algorithm is iterative with decoupling of the inverse of the forward propagation of the wave field and the filtering of phase and amplitude. The sparse modeling of phase and amplitude enables the advanced high-accuracy filtering and sharp imaging of the complex-valued wave field. Artifacts typical for the conventional algorithms (wiggles, ringing, waves, etc.) and attributed to optical diffraction can be suppressed by the proposed algorithm.     

Phthalocyanine–Virus Nanofibers as Heterogeneous Catalysts for Continuous‐Flow Photo‐Oxidation Processes

The generation of highly reactive oxygen species (ROS) at room temperature for application in organic synthesis and wastewater treatment represents a great challenge of the current chemical industry. In fact, the development of biodegradable scaffolds to support ROS‐generating active sites is an important prerequisite for the production of environmentally benign catalysts. Herein, the electrostatic cocrystallization of a cationic phthalocyanine (Pc) and negatively charged tobacco mosaic virus (TMV) is described, together with the capacity of the resulting crystals to photogenerate ROS. To this end, a novel peripherally crowded zinc Pc (1) is synthesized. With 16 positive charges, this photosensitizer shows no aqueous aggregation, and is able to act as a molecular glue in the unidimensional assembly of TMV. A step‐wise decrease of ionic strength in mixtures of both components results in exceptionally long fibers, constituted by hexagonally bundled viruses thoroughly characterized by electron and confocal microscopy. The fibers are able to produce ROS in a proof‐of‐concept microfluidic device, where they are immobilized and irradiated in several cycles, showing a resilient performance. The bottom‐up approach also enables the light‐triggered disassembly of fibers after use. This work represents an important example of a biohybrid material with projected application in light‐mediated heterogeneous catalysis.     

The Role of Temperature and Lipid Charge on Intake/Uptake of Cationic Gold Nanoparticles into Lipid Bilayers

Understanding the molecular mechanisms governing nanoparticle–membrane interactions is of prime importance for drug delivery and biomedical applications. Neutron reflectometry (NR) experiments are combined with atomistic and coarse‐grained molecular dynamics (MD) simulations to study the interaction between cationic gold nanoparticles (AuNPs) and model lipid membranes composed of a mixture of zwitterionic di‐stearoyl‐phosphatidylcholine (DSPC) and anionic di‐stearoyl‐phosphatidylglycerol (DSPG). MD simulations show that the interaction between AuNPs and a pure DSPC lipid bilayer is modulated by a free energy barrier. This can be overcome by increasing temperature, which promotes an irreversible AuNP incorporation into the lipid bilayer. NR experiments confirm the encapsulation of the AuNPs within the lipid bilayer at temperatures around 55 °C. In contrast, the AuNP adsorption is weak and impaired by heating for a DSPC–DSPG (3:1) lipid bilayer. These results demonstrate that both the lipid charge and the temperature play pivotal roles in AuNP–membrane interactions. Furthermore, NR experiments indicate that the (negative) DSPG lipids are associated with lipid extraction upon AuNP adsorption, which is confirmed by coarse‐grained MD simulations as a lipid‐crawling effect driving further AuNP aggregation. Overall, the obtained detailed molecular view of the interaction mechanisms sheds light on AuNP incorporation and membrane destabilization.     

Caustics mapping: an image-space technique for real-time caustics

In this paper, we present a simple and practical technique for real-time rendering of caustics from reflective and refractive objects. Our algorithm, conceptually similar to shadow mapping, consists of two main parts: creation of a caustic map texture, and utilization of the map to render caustics onto nonshiny surfaces. Our approach avoids performing any expensive geometric tests, such as ray-object intersection, and involves no precomputation; both of which are common features in previous work. The algorithm is well suited for the standard rasterization pipeline and runs entirely on the graphics hardware     

Blur identification by multilayer neural network based on multivalued neurons.

A multilayer neural network based on multivalued neurons (MLMVN) is a neural network with a traditional feedforward architecture. At the same time, this network has a number of specific different features. Its backpropagation learning algorithm is derivative-free. The functionality of MLMVN is superior to that of the traditional feedforward neural networks and of a variety kernel-based networks. Its higher flexibility and faster adaptation to the target mapping enables to model complex problems using simpler networks. In this paper, the MLMVN is used to identify both type and parameters of the point spread function, whose precise identification is of crucial importance for the image deblurring. The simulation results show the high efficiency of the proposed approach. It is confirmed that the MLMVN is a powerful tool for solving classification problems, especially multiclass ones.     

Genetic and Environmental Influences on Pubertal Development: Longitudinal Data From Finnish Twins at Ages 11 and 14.

To study sources of individual differences in pubertal development, the authors fit a sex-limitation common factor model to data reported, at ages 11 and 14 years, by 1,891 twin pairs on items that comprise the Pubertal Development Scale (PDS; A. C. Petersen, L. Crockett, M. Richards, & A. Boxer, 1988). The model divides variation into a general pubertal factor and item-specific variation and, in addition, decomposes it into constituent sources. In both boys and girls, genetic influences made the largest contribution to variance common to PDS items. Genetic and nonshared environmental factors accounted for variation specific to PDS items in boys, whereas for girls, common environmental influences were added for growth spurt and menarcheal status. For both common and item-specific variation, genetic effects were partially sex specific. Subsidiary analyses found accelerated maturation in both boys and girls who at age 14 were reared in father-absent homes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Bayesian Robust PCA of Incomplete Data

We present a probabilistic model for robust factor analysis and principal component analysis in which the observation noise is modeled by Student-t distributions in order to reduce the negative effect of outliers. The Student-t distributions are modeled independently for each data dimensions, which is different from previous works using multivariate Student-t distributions. We compare methods using the proposed noise distribution, the multivariate Student-t and the Laplace distribution. Intractability of evaluating the posterior probability density is solved by using variational Bayesian approximation methods. We demonstrate that the assumed noise model can yield accurate reconstructions because corrupted elements of a bad quality sample can be reconstructed using the other elements of the same data vector. Experiments on an artificial dataset and a weather dataset show that the dimensional independency and the flexibility of the proposed Student-t noise model can make it superior in some applications.