Behavioral consequences of crowding in the deermouse (Peromyscus maniculatus).

Hypothesized that, when the degree of crowding is manipulated by varying group size in cages of equal size, it is probable that crowded animals will engage in more contact than uncrowded animals. Home-cage observation of 24 male and 24 female deer mice indicates that crowded Ss do, in fact, engage in more contact behavior. Both home-cage observation and testing in pairs for pain-elicited aggression reveal that (a) crowded Ss display more agonistic behavior than uncrowded Ss, and (b) agonistic behavior increases with prolonged crowding. Support is obtained for the theory that the effect of crowding derives from contact with conspecifics. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Benzoic Acid Derivatives in a Hypogastrurid Collembolan: Temperature-Dependent Formation and Biological Significance as Deterrents

Two phenolic acids were identified in the collembolan Ceratophysella denticulata: 3-hydroxy-4,5 dimethoxy benzoic acid and 4-hydroxy-3,5-dimethoxybenzoic acid (syringic acid). These are localized on or in the integument of the springtail, in field-collected animals, in a ratio of 47:100 (v/v). Springtails kept under different temperature regimes showed differences in production and ratio of the benzoic acid derivatives. At 20 degrees C, C. denticulata produced only syringic acid, whereas at 10 degrees C both isomers in a ratio of 100:61 (v/v) were detected. Bioassays with C. denticulata as well as with the specialized collembolan predator Stenus comma (Staphylinidae) were carried out. Staphylinid beetles topically treated with the acids try to clean their mouthparts by rubbing them on the ground significantly more often than do control beetles. Both compounds individually and as a natural mixture have deterrent effects towards the predator S. comma.     

Development of a computer-based interviewing tool to enhance the requirements gathering process

Software design is an area where it is most important to elicit an accurate and complete set of requirements. Determining the users requirements and their qualitative satisfaction with a developing product are two major problems which arise, often due to the different backgrounds and perspectives of the different stakeholders, including the software engineer, the domain expert and the end-user. Involving users throughout the design and development process is an essential part of any project. Computer-based interviewing has been found to be a valuable tool in eliciting information, which can also enhance interpersonal communication afterwards. This paper discusses the development of a computer interviewing tool to facilitate the gathering of user requirements and conducting user evaluations.     

A comparative study of stochastic optimization methods in electric motor design

The efficiency of universal electric motors that are widely used in home appliances can be improved by optimizing the geometry of the rotor and the stator. Expert designers traditionally approach this task by iteratively evaluating candidate designs and improving them according to their experience. However, the existence of reliable numerical simulators and powerful stochastic optimization techniques make it possible to automate the design procedure. We present a comparative study of six stochastic optimization algorithms in designing optimal rotor and stator geometries of a universal electric motor where the primary objective is to minimize the motor power losses. We compare three methods from the domain of evolutionary computation, generational evolutionary algorithm, steady-state evolutionary algorithm and differential evolution, two particle-based methods, particle-swarm optimization and electromagnetism-like algorithm, and a recently proposed multilevel ant stigmergy algorithm. By comparing their performance, the most efficient method for solving the problem is identified and an explanation of its success is offered.     

Cognitive and learning difficulties and how they affect access to IT systems

In October 2005, the IBM Human Ability and Accessibility Center and T.J. Watson Research Center hosted a symposium on “cognitive and learning difficulties and how they affect access to IT systems”. The central premise of the symposium was the recognition that cognitive and learning difficulties have a profound impact on a person’s ability to interact with information technology (IT) systems, but that little support is currently being offered by those systems. By bringing together internationally renowned experts from a variety of different, but complementary, research fields, the symposium aimed to provide a complete overview of the issues related to this topic. This paper summarises the discussions and findings of the symposium.     

The Nonconvergence of h-Refinement in Prolate Elements

Prolate elements are a “plug-compatible” modification of spectral elements in which Legendre polynomials are replaced by prolate spheroidal wave functions of order zero. Prolate functions contain a“bandwidth parameter” $c \ge 0 $ c ≥ 0 whose value is crucial to numerical performance; the prolate functions reduce to Legendre polynomials for $c\,=\,0$ c = 0 . We show that the optimal bandwidth parameter $c$ c not only depends on the number of prolate modes per element $N$ N , but also on the element widths $h$ h . We prove that prolate elements lack $h$ h -convergence for fixed $c$ c in the sense that the error does not go to zero as the element size $h$ h is made smaller and smaller. Furthermore, the theoretical predictions that Chebyshev and Legendre polynomials require $\pi $ π degrees of freedom per wavelength to resolve sinusoidal functions while prolate series need only 2 degrees of freedom per wavelength are asymptotic limits as $N \rightarrow \infty $ N → ∞ ; we investigate the rather different behavior when $N \sim O(4-10)$ N ～ O ( 4 ? 10 ) as appropriate for spectral elements and prolate elements. On the other hand, our investigations show that there are certain combinations of $N,\,h$ N , h and $c>0$ c > 0 where a prolate basis clearly outperforms the Legendre polynomial approximation.     

A multi-objective approach to the application of real-world production scheduling

An initiative was introduced in one of the production facilities of Germany’s E.G.O. Group in order to enhance its SAP information system with a custom-made application for production-scheduling optimization. The goal of the optimization is to find a production schedule that satisfies different, contradictory production and business constraints. We show the challenges faced in the application of the multi-objective optimization approach, which is gaining influence in the management of production scheduling. We implement a memetic version of the Indicator-Based Evolutionary Algorithm with customized reproduction operators and local search procedures to find a set of feasible, non-dominated solutions. Such a memetic algorithm was applied to two real order lists from the production company. Additionally, we also lay out an efficient presentation of the multi-objective results for an expert’s support in decision making. This provides the management with the possibility to gain additional insights into how the production schedule dynamically reacts to changes in the decision criteria. We show that the multi-objective approach is able to find high-quality solutions, which enables flexibility when it comes to quickly adapting to specific business conditions.     

Gaussian process internal model control

Nonlinear modelling approaches such as neural networks, fuzzy models and multiple model networks have been proposed for model based control, to improve the poor transient response of adaptive control techniques. The quality of control is known to be strongly related to the accuracy of the model which represents the process. A Bayesian Gaussian process (GP) approach provides an analytic prediction of the model uncertainty, which makes the GP model an ideal candidate for model based control strategies. This article extends the use of the GP model for nonlinear internal model control. The invertibility of the GP model is discussed and the use of predicted variance is illustrated on a simulated example.     

Introduction to the special issue on design science

The rigorous application of design science in information and communications technology (ICT) research is growing rapidly and producing exciting results. The five papers published in this special issue reflect some of the most recent ideas and research projects in ICT design science research (DSR). This introduction begins with concise summaries of the published papers. We then reflect on three key design science issues, using the published papers to illustrate our views. The three issues are: (1) the nature of the artifacts/problems studied in DSR in ICT disciplines; (2) the research approaches that are used; and (3) the nature of the research contributions that are made. We explain why we believe that these issues are interdependent and why thinking about these three issues as a whole can support an improved understanding of the goals and processes of design science research.     

Impact of Posttraumatic Stress Disorder on early smoking lapse and relapse during a self-guided quit attempt among community-recruited daily smokers

The present investigation examined whether daily smokers with posttraumatic stress disorder (PTSD), as compared to daily smokers with either anxiety psychopathology or no current Axis I psychopathology, have decreased success in the early phases of a self-guided smoking quit attempt. Participants were 140 daily smokers (81 women; M (age) = 29.5; SD = 11.9; range = 18-65 years); approximately one-third of the sample met criteria for current PTSD (n = 47), one-third met criteria for other current anxiety disorders (without PTSD; n = 33), and one-third did not meet criteria for any current Axis I disorder (n = 60). Consistent with prediction, membership in the PTSD group, compared to membership in the other anxiety disorders group and the group with no current Axis I psychopathology, was associated with increased risk of lapse during the first week following quit day. Additionally, daily smokers with PTSD and other anxiety disorders were at significantly increased risk of relapse during the first week post-cessation compared to persons without Axis I psychopathology. However, the PTSD group and the other anxiety disorders group did not differ from one another in terms of relapse. Results suggest that PTSD is associated with increased risk of smoking lapse and relapse compared to smokers with no current Axis I psychiatric problems, and increased risk of early smoking lapse but not relapse, as compared to those with other anxiety disorders. Findings provide novel evidence that PTSD, and perhaps anxiety disorders more generally, may be important factors in reducing the odds of successful unaided quit attempts in the early phases of cessation.