Three hypotheses concerning young children's imitations of lexical items.

Examined 2 hypotheses concerning possible facilitative effects of imitation on lexical acquisition, using comprehension as well as production as metrics for lexical emergence. Three experiments, with 33 children aged 1 yr 4 mo to 2 yrs, provided evidence that imitation may facilitate children's ability to acquire words in production and that imitation of such words may decline only after a period in which the words are used both imitatively and spontaneously. Preliminary support was also found for a 3rd hypothesis: In some cases imitation of novel words may enable the child to respond to others when he/she is unable to contribute original information to the topic. (8 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Negotiating the middle years: Ego-resiliency and successful midlife adjustment in women.

Midlife is a time of heightened reevaluation and reorientation during which individuals are faced with potentially stressful changes and turning points. Ego-resiliency (ER) is proposed to be a powerful personality resource that enables individuals to adaptively negotiate the challenges of this period. Through examination of data from 2 longitudinal samples of women (N?=?208), Study 1 examined whether observer-based and self-reported ER assessed at the beginning of midlife (at age 43) can predict life adjustments of specific relevance to this period assessed in late middle age (ages 52 and 48). In Study 2 age 43 ER was used to predict directional changes in central life adjustments and feelings about life over this same period (between ages 43 and 52). Predictions across samples, across measures of ER, or both were confirmed by replicated findings. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An evaluation of commercial expert system building tools

The Force Requirements Expert System (FRESH) is the first phase of the Defense Advanced Research Projects Agency's (DARPA) Navy Battle Management Program, part of the Strategic Computing Initiative. To encourage long term maintainability of the delivered system, DARPA required the use of a commercial Expert System Building Tool. The selection of a tool required the establishment of an evaluation methodology: Analyze the problem domain in terms of AI theory, examine the previous research solutions to the problem and determine their requirements, solve the problem with each tool, compare the results and make the selection. This methodology was followed for three tools that run on Lisp Machines: KEE™ from the IntelliCorp, ART™ from Inference Corporation, and Knowledge Craft™ from Carnegie Group Incorporated. The determining factors in our choice were the size and complexity of the domain and the fact that long term maintenance will be performed by people other than the original knowledge engineers. For these reasons the selection of expert system building tool for FRESH was Knowledge Craft™. This paper presents the application of this evaluation methodology, the results obtained from the tests, and selection decision given the results. Use of this methodology produces comprehensive and functionally accurate information with which to make a selection.     

Marital therapy and spouse involvement in the treatment of depression, agoraphobia, and alcoholism.

Examines the literature on marital therapy and spouse involvement as treatments for major psychopathology. The focus is on three disorders that have attracted a sufficient number of empirical findings: depression, agoraphobia, and alcoholism. For each of these disorders, we first examine the relation between marital dynamics and the disorder and next discuss empirical efforts to evaluate the impact of marital therapy or spouse involvement on the disorder. In addition, we summarize trends and suggest methodological refinements for future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

MesoGAN: Generative Neural Reflectance Shells

We introduce MesoGAN, a model for generative 3D neural textures. This new graphics primitive represents mesoscale appearance by combining the strengths of generative adversarial networks (StyleGAN) and volumetric neural field rendering. The primitive can be applied to surfaces as a neural reflectance shell; a thin volumetric layer above the surface with appearance parameters defined by a neural network. To construct the neural shell, we first generate a 2D feature texture using StyleGAN with carefully randomized Fourier features to support arbitrarily sized textures without repeating artefacts. We augment the 2D feature texture with a learned height feature, which aids the neural field renderer in producing volumetric parameters from the 2D texture. To facilitate filtering, and to enable end-to-end training within memory constraints of current hardware, we utilize a hierarchical texturing approach and train our model on multi-scale synthetic datasets of 3D mesoscale structures. We propose one possible approach for conditioning MesoGAN on artistic parameters (e.g. fibre length, density of strands, lighting direction) and demonstrate and discuss integration into physically based renderers.     

Priority switching scheduler

We define a novel core network router scheduling architecture called priority switching scheduler (PSS), to carry and isolate time constrained and elastic traffic flows from best-effort traffic. To date, one possible solution has been to implement a core DiffServ network with standard fair queuing and scheduling mechanisms as proposed in the well-known “A Differentiated Services Code Point (DSCP) for Capacity-Admitted Traffic” from RFC5865. This architecture is one of the most selected solutions by internet service provider for access networks (e.g., customer-premises equipment) and deployed within several performance-enhancing proxies (PEPs) over satellite communications (SATCOM) architectures. In this study, we argue that the proposed standard implementation does not allow to efficiently quantify the reserved capacity for the AF class. By using a novel credit-based shaper mechanism called burst limiting shaper (BLS) to manage the AF class, we show that PSS can provide the same isolation for the time constrained EF class while better quantifying the part allocated to the AF class. PSS operates both when the output link capacity is fixed (e.g., wire links and terrestrial networks) or might vary due to system impairments or weather condition (e.g., wireless or satellite links). We demonstrate the capability of PSS through an emulated SATCOM scenario with variable capacity and show the AF output rate is less dependent on the EF traffic, which improves the quantification of the reserved capacity of AF, without impacting EF traffic.     

Construction of a 3D model of CP12, a protein linker

The chloroplast protein CP12 is known to play a leading role in a complex formation with the enzymes GAPDH and PRK. As a preliminary step towards the understanding of the complex formation mechanism and the exact role of this protein linker, a comparative modelling of the CP12 protein of the green alga Chlamydomonas reinhardtii was performed. Because of the very few structural information and poor template similarities, the derivation of the model consisted in an iterative trial-and-error procedure using the comparative modelling program MODELLER, the following three structure validation programs PROCHECK, PROSA, and WHATIF, and molecular mechanics energy refinement of the model using the program CHARMM. The analysis of the final model reveals a scaffold of key residues that is believed to be essential in the folding mechanism and that coincides with the residues conserved throughout the CP12 family. Our results suggest that this protein is a typical disordered protein. Finally, the various mechanisms by which the CP12 protein can self-interact or binds to other enzymes are discussed in light of its modelled structure and characteristics.     

A New Method to Increase the Margin of Multilayer Perceptrons

A new method to maximize the margin of MLP classifier in classification problems is described. Thismethod is based on a new cost function which minimizes the variance ofthe mean squared error. We show that with this cost function the generalizationperformance increase. This method is tested and compared with the standard mean square errorand is applied to a face detection problem.