Enhancing job-site training of supported workers with autism: a reemphasis on simulation

Currently recommended practice in supported work emphasizes training job skills to workers with severe disabilities while on the job. Early behavioral research indicated that skills needed in natural environments could also be trained in simulated settings. We compared job-site plus simulation training for teaching job skills to supported workers with autism to provision of training exclusively on the job. Job-site training occurred in a small publishing company during the regular work routine, and simulation training occurred in an adult education site for people with severe disabilities. Two pairs of workers received training on two job skills; one skill was trained at the job site and the other was trained using job-site plus simulation training. Results indicated that for 3 of the 4 comparisons, job-site plus simulation training resulted in a higher level of skill or more rapid skill acquisition than did job-site-only training. Results suggested that job-site training, the assumed best practice for teaching vocational skills, is likely to be more effective if supplemented with simulation training. Directions for future research include expanding applications of behavioral technologies to other aspects of the current support paradigm.     

Modeling recognition memory using the similarity structure of natural input

The natural input memory (NIM) model is a new model for recognition memory that operates on natural visual input. A biologically informed perceptual preprocessing method takes local samples (eye fixations) from a natural image and translates these into a feature-vector representation. During recognition, the model compares incoming preprocessed natural input to stored representations. By complementing the recognition memory process with a perceptual front end, the NIM model is able to make predictions about memorability based directly on individual natural stimuli. We demonstrate that the NIM model is able to simulate experimentally obtained similarity ratings and recognition memory for individual stimuli (i.e., face images).     

Infiltration behaviour of water in a carbon nanotube under external pressure

The wetting behaviour and associated pressure effect of water in single-walled carbon nanotubes (SWCNTs) are investigated through molecular dynamics (MD) simulations. It is found that water molecules can enter SWCNTs via surface diffusion, and the effective infiltration rate increases with pressure. The effect of pressure on infiltration rate is highly non-linear, exhibiting characteristics of both hydrophilic and hydrophobic surfaces. There exists a nominal infiltration pressure that is dependent on the SWCNT size, above which the water flux is significantly increased.     

Flaw tolerance promoted by dissipative deformation mechanisms between material building blocks

Novel high-performance composite materials often draw inspiration from natural materials such as bone or mollusc shells. A prime feature of such composites is that they are, like their natural counterparts, quasibrittle. They are tolerant to material flaws up to a certain characteristic flaw-tolerant size scale, exhibiting high strength and toughness, but start to behave in a brittle manner when sufficiently large flaws are present. Here, we establish that better flaw tolerance can be achieved by maximizing fracture toughness relative to the maximum elastic energy available in the material, and we demonstrate this concept with simple two-dimensional coarse-grained simulations where the transition from brittle to quasibrittle behaviour is examined.     

Phase-field crystal modeling of anisotropic material systems of arbitrary Poisson's ratio

Recently, we derived a generalized model for isotropic as well as anisotropic crystal lattice systems of arbitrary Poisson's ratio within the framework of the continuum phase-field crystal (PFC) approach [R. Prieler, J. Hubert, D. Li, B. Verleye, R. Haberkern, H. Emmerich, J. Phys.: Condens. Matter 21 (2009) p.464110] and showed how its parameters can be derived from classical density functional theory [M.A. Choudhary, D. Li, H. Emmerich and H. Löwen, J. Phys.: Condens. Matter 23 (2011) p.265005]. Here, we present a general procedure to model anisotropic material systems of arbitrary Poisson's ratios. In that way we can for the first time identify PFC solutions of arbitrary Poisson's ratios and thereby extend the applicability of the PFC method to a larger class of material systems.     

Scaling relationships in indentation of power-law creep solids using self-similar indenters

We use dimensional analysis to derive scaling relationships for self-similar indenters indenting solids that exhibit power-law creep. We identify the parameter that represents the indentation strain rate. The scaling relationships are applied to several types of indentation creep experiment with constant displacement rate, constant loading rate or constant ratio of loading rate over load. The predictions compare favourably with experimental observations reported in the literature. Finally, a connection is found between creep and 'indentation-size effect' (i.e. changing hardness with indentation depth or load).     

Many-body potential for nitrogen in α-iron

N atom is one of the most frequent foreign interstitial atoms in α-iron along with C atoms. The Fe–C potential has been well-developed and can reproduce many significant interactions of C with point defects present in α-iron. However, there exists no satisfactory Fe–N potential to describe the interactions of N with point defects. Here, we develop a many-body potential for N in α-iron. The potential parameters are determined by fitting to ab initio data, which includes energetics, configurations, and relaxations of Fe atoms close to N atom. This potential successfully describes the interactions of Fe–N across a wide range of defect environments. The potential employs the embedded atom method form and hence is appropriate for large-scale molecular dynamics simulation.     

校正的Bootstrap方法对概化理论方差分量及其变异量估计的改善

Bootstrap方法是一种有放回的再抽样方法, 可用于概化理论的方差分量及其变异量估计。用Monte Carlo技术模拟四种分布数据, 分别是正态分布、二项分布、多项分布和偏态分布数据。基于p×i设计, 探讨校正的Bootstrap方法相对于未校正的Bootstrap方法, 是否改善了概化理论估计四种模拟分布数据的方差分量及其变异量。结果表明：跨越四种分布数据, 从整体到局部, 不论是“点估计”还是“变异量”估计, 校正的Bootstrap方法都要优于未校正的Bootstrap方法, 校正的Bootstrap方法改善了概化理论方差分量及其变异量估计。     

The antecedents of anticipatory purchase: Reconciling the two routes to optimism

Consumers often behave optimistically, purchasing products that they are unable to use at the time of purchase, but anticipate being able to use in the future. This research investigates such anticipatory purchase behavior, and demonstrates that optimism exerts its influence on anticipatory purchase via two distinct routes. One is driven by the perceived ease of the process required to achieve a given outcome and prevails when sufficient cognitive resources are available, while the other is driven directly by the perceived favorability of the outcome itself and holds when cognitive resources are constrained. Within each route, the focus of thought (process vs. outcome-focus) moderates the influence of optimism, and the two routes converge on enhanced motivation. Multiple experiments provide support for predictions derived from this framework, illuminating the substantive domain of anticipatory purchasing and providing theoretical insights into the nature of optimism.     

How Do Propensity Score Methods Measure Up in the Presence of Measurement Error? A Monte Carlo Study

Considering that the absence of measurement error in research is a rare phenomenon and its effects can be dramatic, we examine the impact of measurement error on propensity score (PS) analysis used to minimize selection bias in behavioral and social observational studies. A Monte Carlo study was conducted to explore the effects of measurement error on the treatment effect and balance estimates in PS analysis across seven different PS conditioning methods. In general, the results indicate that even low levels of measurement error in the covariates lead to substantial bias in estimates of treatment effects and concomitant reduction in confidence interval coverage across all methods of conditioning on the PS.