Metric-based reasoning about pseudocode design in the partial metrics system

The goal of the PMS project is to produce an environment in which the intelligent online assessment of the design for large-scale ADA programming projects is provided. The focus is on the representation of knowledge about the design process for an individual module. Changes in pseudocode complexity are measured in terms of partial metrics. These metrics can take the designers inferences about the pseudocode program structure into account when assessing module complexity. Next, a model of the stepwise refinement process is given which demonstrates how pseudocode elaboration decisions can be modelled in partial metric terms. Finally, the decisions associated with each refinement step for 17 example refinements taken from the computer science literature are described using partial metrics.     

Alcohol consumption as a self-handicapping strategy in women.

Assessed whether women self-handicap with alcohol consumption prior to engaging in a social evaluation task, which may be more relevant to their self-esteem than the intellectual tasks used in past self-handicapping studies on substance use. 113 women (aged 19–32 yrs), who were evaluated as normal drinkers, performed either a solvable or an insolvable social judgment task and then received either success feedback or no feedback. Ss received access to alcoholic and nonalcoholic beverages while awaiting a retest. The study terminated before the retest. The self-handicapping hypothesis that noncontingent success would produce relatively greater alcohol consumption was not supported. Regardless of feedback, insolvable test Ss consumed more alcohol than did solvable test Ss. Findings suggest that the hypothesis may be limited as a general model of alcohol consumption in both sexes. (13 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An asymptotically efficient ARMA estimator based on sample covariances

An asymptotically efficient autoregressive moving-average (ARMA) spectral estimator is presented, based on the sample covariances of observed time series. The estimate of the autoregressive (AR) part is shown to be identical to the optimal instrumental variable (IV) estimator in [7] although derived here using a different approach. The moving-average (MA) spectral parameter estimate is new.     

Synthesis,characterization and properties of functionalized styrene–maleimide copolymers

New functionalized styrene–maleimide copolymers were prepared by free radical copolymerization of styrene (St) and N‐4‐carboxybutylmaleimide (NBMI) in chloroform, using 2,2′‐azobisisobutyronitrile (AIBN) as initiator. Monomer and copolymer characterization was carried out by ¹H‐ and ¹³C‐NMR. Copolymer composition was determined by elemental analysis and Fourier‐transform infrared (FTIR) spectroscopy. The glass transition temperature (from DSC) and the thermogravimetric analysis (TGA) of the copolymers were consistent with the thermal behavior and stability observed for alternating St–maleimide copolymers. St–NBMI copolymers crosslinked with divinylbenzene (DVB) were also synthesized and their cation exchange properties evaluated in order to assess the capacity of the new copolymers to bind metallic ions. Copyright © 2005 Society of Chemical Industry     

Analysis and synthesis of on-chip spiral inductors

This paper presents a physically based compact model for estimating high-frequency performance of spiral inductors. The model accurately accounts for skin and proximity effects in the metal conductors as well as eddy current losses in the substrate. The model shows excellent agreement with measured data mostly within 10% across a variety of inductor geometries and substrate dopings up to 20 GHz. A web-based spiral inductor synthesis and analysis tool COILS, which makes use of the compact models, is presented. An optimization algorithm using binary searches speeds up the synthesis of inductor designs.     

The incompatibility of knowledge regimes: consequences of the material world for cross-domain work

In this paper, we argue that successful integration of knowledge across work domains in the short-term can mask the generation of long-term consequences. We explore a setting, the introduction of environmental considerations into semiconductor manufacturing, where the eventual adoption of common measurement artifacts and associated practices enabled knowledge integration, but failed to address significant underlying consequences. Drawing from observational, interview, and archival data we develop an understanding of the work practices of the Tech and EnviroTech groups as structured by the material world and broader collective conventions. We introduce the concept of knowledge regime to outline the differences in knowledge across these work domains. More specifically, we find that differences in the causal specificity and developmental time horizon of knowledge and the measurement artifacts that result contribute to the relative power of one knowledge regime over another. Understanding these sources of incompatibility provides insight into the design requirements of information systems as boundary objects for knowledge integration, but also specifies the potential limits to any design effort.     

An APL procedure to estimate genotype by environment interaction when two environments are considered

Genotype by environment interaction (GEI) is a relevant topic in many fields of applied biology. Normal parametric approaches following analysis of variance are not suitable when large differences between error variances within environments are present. We illustrate an APL program following Yamada's approach to estimate GEIs and ancillary statistics when two environments are considered. The choice of APL environment is based on its value as a useful tool in algorithm implementation and problem-solving. Its use is suggested in biological applications where matrix algebra is involved and an understanding of the computing complexity of problems is generally not required.