Poly(methyl methacrylate)‐grafted cellulose nanocrystals: One‐step synthesis,nanocomposite preparation,and characterization

Cellulose nanocrystals (CNCs) are ideal reinforcing agents for polymer nanocomposites because they are lightweight and nano‐sized with a large aspect ratio and high elastic modulus. To overcome the poor compatibility of hydrophilic CNCs in non‐polar composite matrices, we grafted poly(methyl methacrylate) (PMMA) from the surface of CNCs using an aqueous, one‐pot, free radical polymerization method with ceric ammonium nitrate as the initiator. The hybrid nanoparticles were characterized by CP/MAS NMR, X‐ray photoelectron spectroscopy, infrared spectroscopy, contact angle, thermogravimetric analysis, X‐ray diffraction, and atomic force microscopy. Spectroscopy demonstrates that 0.11 g/g (11 wt %) PMMA is grafted from the CNC surface, giving PMMA‐g‐CNCs, which are similar in size and crystallinity to unmodified CNCs but have an onset of thermal degradation 45 °C lower. Nanocomposites were prepared by compounding unmodified CNCs and PMMA‐g‐CNCs (0.0025–0.02 g/g (0.25–2 wt %) loading) with PMMA using melt mixing and wet ball milling. CNCs improved the performance of melt‐mixed nanocomposites at 0.02 g/g (2 wt %) loading compared to the PMMA control, while lower loadings of CNCs and all loadings of PMMA‐g‐CNCs did not. The difference in Young's modulus between unmodified CNC and polymer‐grafted CNC composites was generally insignificant. Overall, ball‐milled composites had inferior mechanical and rheological properties compared to melt‐mixed composites. Scanning electron microscopy showed aggregation in the samples with CNCs, but more pronounced aggregation with PMMA‐g‐CNCs. Despite improving interfacial compatibility between the nanoparticles and the matrix, the effect of PMMA‐g‐CNC aggregation and decreased thermal stability dominated the composite performance.     

Scalable digital hardware for a trapped ion quantum computer

Quantum Information Processing - Many of the challenges of scaling quantum computer hardware lie at the interface between the qubits and the classical control signals used to manipulate them....     

Belief Decay or Persistence? A Mixed-method Study on Belief Movement Over Time

When individuals encounter new information (data), that information is incorporated with their existing beliefs (prior) to form a new belief (posterior) in a process referred to as belief updating. While most studies on rational belief updating in visual data analysis elicit beliefs immediately after data is shown, we posit that there may be critical movement in an individual's beliefs when elicited immediately after data is shown v. after a temporal delay (e.g., due to forgetfulness or weak incorporation of the data). Our paper investigates the hypothesis that posterior beliefs elicited after a time interval will “decay” back towards the prior beliefs compared to the posterior beliefs elicited immediately after new data is presented. In this study, we recruit 101 participants to complete three tasks where beliefs are elicited immediately after seeing new data and again after a brief distractor task. We conduct (1) a quantitative analysis of the results to understand if there are any systematic differences in beliefs elicited immediately after seeing new data or after a distractor task and (2) a qualitative analysis of participants' reflections on the reasons for their belief update. While we find no statistically significant global trends across the participants beliefs elicited immediately v. after the delay, the qualitative analysis provides rich insight into the reasons for an individual's belief movement across 9 prototypical scenarios, which includes (i) decay of beliefs as a result of either forgetting the information shown or strongly held prior beliefs, (ii) strengthening of confidence in updated beliefs by positively integrating the new data and (iii) maintaining a consistently updated belief over time, among others. These results can guide subsequent experiments to disambiguate when and by what mechanism new data is truly incorporated into one's belief system.     

Data‐Driven Bending Elasticity Design by Shell Thickness

We present a method to design the deformation behavior of 3D printed models by an interactive tool, where the variation of bending elasticity at different regions of a model is realized by a change in shell thickness. Given a soft material to be used in 3D printing, we propose an experimental setup to acquire the bending behavior of this material on tubes with different diameters and thicknesses. The relationship between shell thickness and bending elasticity is stored in an echo state network using the acquired dataset. With the help of the network, an interactive design tool is developed to generate non‐uniformly hollowed models to achieve desired bending behaviors. The effectiveness of this method is verified on models fabricated by different 3D printers by studying whether their physical deformation can match the designed target shape.     

Preference-based topology optimization for vehicle concept design with concurrent static and crash load cases

In the simulation-based design process of automotive structures, an increasing amount of multi-disciplinary requirements have to be considered. Methods of topology optimization can be used to devise structural concepts early in the design process to obtain the best possible structural layout as starting point for further development steps. Especially relevant for the vehicle design process is the concurrent consideration of static load requirements representing normal operating conditions and energy absorption requirements targeting passive safety in crash events. When the disciplines are considered separately, the heuristic Hybrid Cellular Automaton topology optimization is a suitable method. However, in practical applications, both disciplines are usually addressed sequentially. This complicates the overall process and may reduce the quality of the final optimization result, since optimization objectives may be conflicting. We propose a preference-based Scaled Energy Weighting approach to address the topology optimization of both disciplines concurrently. The main idea is to decouple the user preference from the scaling of the different magnitudes of energies. This enables a multi-objective optimization and ultimately the selection of the desired trade-off solution. We first validate the capability of the method to provide structures optimized for stiffness and energy absorption objectives on beam examples. Finally, the method is applied to optimize a concept structure of an industrial vehicle body, demonstrating its practical feasibility.     

Do problematic and non-problematic video game players differ in extraversion,trait empathy,social capital and prosocial tendencies?

The increasing popularity of online and multiplayer games has meant that for many, social interaction and cooperation are vital components of the gaming experience. Previous research has suggested that not only has this made gaming more attractive to socially oriented people but also that it may be socially beneficial in terms of social capital and prosocial behaviors. However, for problematic video game players (those showing signs of compulsive or detrimental video game use), this may not be the case, and a number of theories hold deficiencies in socializing in real life as central to the development of this issue. In the present study, an online questionnaire completed by 416 participants assessed problematic video game use, extraversion, trait empathy, online and offline social capital and prosocial tendencies. Contrary to hypotheses, non-problematic, problematic and non-gamers did not differ in empathy, extraversion or prosocial tendencies. Problematic video game play was, however, associated with significantly higher online social capital and lower offline social capital whereas non-problematic players demonstrated only higher online capital than non-players. This highlights the importance of social support but suggests personality is not an influential factor.     

Sheldon H. White (1928-2005).

Sheldon "Shep" Harold White, one of developmental psychology's most distinguished scholars, died on March 17, 2005, at the age of 76. He is perhaps best remembered for his sharp intellect, generous spirit, good humor, and warm compassion. Shep's principal work lay in three intermeshed areas: children's learning and cognitive development, social programs and policies, and the history of developmental psychology. Shep White is sorely missed by his family and friends, and countless children have unknowingly benefited from his research, scholarship, and contributions to public policy. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The role of dorsal hippocampus and basolateral amygdala NMDA receptors in the acquisition and retrieval of context and contextual fear memories.

The authors used 3-phase context preexposure facilitation methodology to study the contribution of N-methyl-D-aspartate (NMDA) receptors in dorsal hippocampus (DH) and the basal lateral region of the amygdala (BLA) to (a) acquisition of the context memory, (b) retrieval of the context memory, (c) acquisition of context-shock association, and (d) retrieval of the context-shock association. The NMDA receptor antagonist D-2-amino-5 phosphonopentanoic acid (D-AP5) was injected into either the DH or BLA prior to (a) the context preexposure phase, (b) the immediate shock phase, or (c) the test for contextual fear. Antagonizing NMDA receptors in the DH impaired the acquisition of the context memory but did not affect its retrieval or retrieval of the fear memory. Antagonizing NMDA receptors with D-AP5 in the BLA impaired acquisition of the context-shock association but had no effect on the expression of fear. However, both DL-AP5 and L-AP5 reduced the expression of fear when they were injected into the amygdala prior to testing for contextual fear. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Outlier removal in biomaterial image segmentations using a non-stationary Bayesian learning

Pattern Analysis and Applications - Segmentation of dried amnion biomaterial tends to produce invalid (outlier) contour point detections due to texture and colour inhomogeneity of the biomaterial....