Study of lee-side flows over conically cambered delta wings at supersonic speeds, part 1

An experimental investigation was performed in which surface pressure data, flow visualization data, and force and moment data were obtained on four conical delta wing models which differed in leading-edge camber only. Wing leading-edge camber was achieved through a deflection of the outboard 30% of the local wind semispan of a reference 75 degrees swept flat delta wing. The four wing models have leading-edge deflection angles delta sub F of 0, 5, 10, and 15 degrees measured streamwise. Data for the wings with delta sub F = 10 and 15 degrees showed that hinge-line separation dominated the lee-side wing loading and prohibited the develpment of leading-edge separation on the deflected portion of wing leading edge. However, data for the wing with delta sub F = 5 degrees, a vortex was positioned on the deflected leading edge with reattachment at the hinge line. Flow visualization results were presented which detail the influence of Mach number, angle of attack, and camber on the lee-side flow characteristics of conically cambered delta wings. Analysis of photgraphic data identified the existence of 12 distinctive lee-side flow types. In general, the aerodynamic force and moment data correlated well with the pressure and flow visualization data

Q-sorting and MIS Research: A Primer

Q-sort offers a powerful, theoretically grounded, and quantitative tool for examining opinions and attitudes. This article provides clear guidelines in an effort to facilitate successful understanding and application of Q-sort. Following a description of the steps of Q-sorting, an example Q-sort of MIS professors on the topic of PhD preparation is presented. The example includes details of Web-based data collection and data analysis using freeware tools. The use of Q-sorting in MIS research and issues surrounding the use of Q-sort are discussed

Determination of biomembrane bending moduli in fully atomistic simulations.

The bilayer bending modulus (Kc) is one of the most important physical constants characterizing lipid membranes, but precisely measuring it is a challenge, both experimentally and computationally. Experimental measurements on chemically identical bilayers often differ depending upon the techniques employed, and robust simulation results have previously been limited to coarse-grained models (at varying levels of resolution). This Communication demonstrates the extraction of Kc from fully atomistic molecular dynamics simulations for three different single-component lipid bilayers (DPPC, DOPC, and DOPE). The results agree quantitatively with experiments that measure thermal shape fluctuations in giant unilamellar vesicles. Lipid tilt, twist, and compression moduli are also reported

Adding Value to Key Issues Research Through Q-Sorts and Interpretive Structured Modeling

A questionnaire requiring respondents to rate the importance of key issues is the traditional data collection tool for investigating the key issues of Information Technology (IT) managers. Such an instrument does not force managers to confront the relationships between issues. Q-sort and interpretive structured modeling (ISM) force managers to consider the linkages among key issues. This article discusses the use of these methodologies for investigating key issues and demonstrates their application with data collected from Brazilian banking IT managers. This study illustrates how these approaches provide additional insights into the key concerns facing IT managers

Achieving open access to conservation science

Conservation science is a crisis discipline in which the results of scientific enquiry must be made available quickly to those implementing management. We assessed the extent to which scientific research published since the year 2000 in 20 conservation science journals is publicly available. Of the 19,207 papers published, 1,667 (8.68%) are freely downloadable from an official repository. Moreover, only 938 papers (4.88%) meet the standard definition of open access in which material can be freely reused providing attribution to the authors is given. This compares poorly with a comparable set of 20 evolutionary biology journals, where 31.93% of papers are freely downloadable and 7.49% are open access. Seventeen of the 20 conservation journals offer an open access option, but fewer than 5% of the papers are available through open access. The cost of accessing the full body of conservation science runs into tens of thousands of dollars per year for institutional subscribers, and many conservation practitioners cannot access pay-per-view science through their workplace. However, important initiatives such as Research4Life are making science available to organizations in developing countries. We urge authors of conservation science to pay for open access on a per-article basis or to choose publication in open access journals, taking care to ensure the license allows reuse for any purpose providing attribution is given. Currently, it would cost $51 million to make all conservation science published since 2000 freely available by paying the open access fees currently levied to authors. Publishers of conservation journals might consider more cost effective models for open access and conservation-oriented organizations running journals could consider a broader range of options for open access to nonmembers such as sponsorship of open access via membership fees

Global adaptation in networks of selfish components: emergent associative memory at the system scale

In some circumstances complex adaptive systems composed of numerous self-interested agents can self-organise into structures that enhance global adaptation, efficiency or function. However, the general conditions for such an outcome are poorly understood and present a fundamental open question for domains as varied as ecology, sociology, economics, organismic biology and technological infrastructure design. In contrast, sufficient conditions for artificial neural networks to form structures that perform collective computational processes such as associative memory/recall, classification, generalisation and optimisation, are well-understood. Such global functions within a single agent or organism are not wholly surprising since the mechanisms (e.g. Hebbian learning) that create these neural organisations may be selected for this purpose, but agents in a multi-agent system have no obvious reason to adhere to such a structuring protocol or produce such global behaviours when acting from individual self-interest. However, Hebbian learning is actually a very simple and fully-distributed habituation or positive feedback principle. Here we show that when self-interested agents can modify how they are affected by other agents (e.g. when they can influence which other agents they interact with) then, in adapting these inter-agent relationships to maximise their own utility, they will necessarily alter them in a manner homologous with Hebbian learning. Multi-agent systems with adaptable relationships will thereby exhibit the same system-level behaviours as neural networks under Hebbian learning. For example, improved global efficiency in multi-agent systems can be explained by the inherent ability of associative memory to generalise by idealising stored patterns and/or creating new combinations of sub-patterns. Thus distributed multi-agent systems can spontaneously exhibit adaptive global behaviours in the same sense, and by the same mechanism, as the organisational principles familiar in connectionist models of organismic learning