Effect of Prey Density on Diurnal Activity and Ovarian Development in \u3ci\u3eCalosoma Calidum\u3c/i\u3e (Coleoptera: Carabidae): Implications for Biological Control of the Gypsy Moth, \u3ci\u3eLymantria Dispar (Lepidoptera: Lymantriidae)\u3c/i\u3e in the Midwest

Four feeding treatments were used in the laboratory to study the effects of the availability of prey on diurnal behavior and ovarian development of Calosoma calidum. Activity was closely monitored for six weeks. No significant differences were found between male and female behavior patterns. Diurnal beetle activity was found to be inversely related to prey density; in treatments where prey was available, diurnal activity declined during the course of the experiment. At the end of six weeks, dissections of female beetles showed that ovarian development and fat body quantity were dependent upon the number of prey available for consumption

The University Pages Game: Gamified Use of the Linkedin Student & Alumni Tool to Enhance Student Understanding of the Role of Social Media in Building Social Capital

Like many other academic disciplines, gamified learning environments are increasing in IS education. Creating and using gamified learning experiences contributes to “flipped classrooms” and is widely viewed as a mechanism for increasing course engagement among millennial students. This paper describes the creation and use of a social media module for a MIS course that uses game elements to introduce students to LinkedIn’s Student and Alumni Tool and how it can be used to build social capital. Because LinkedIn Student & Alumni tool is relatively unknown among students, the social media module, which we call the University Pages Game, also provides instructors with a vehicle for illustrating precepts of the Unified Theory of Acceptance and Use of Technology (UTAUT)

Probing the Interstellar Medium of External Galaxies Using Quasar Absorption Lines: the 3C 232/NGC 3067 System

Quasar absorption lines offer unique opportunities to probe the interstellar medium of external galaxies. Researchers present new optical and UV absorption line spectroscopy of the quasar 3C232 (z=0.55) revealing new detail in the foreground absorption system due to the bright, spiral galaxy NGC 3067 (cz=1420 km/s). Specifically, the spectra show evidence for two and possibly three separate absorption components in CaII and Na I spanning approx. 150 km/s. The original HI detection of Haschick and Burke (1975) corresponds to the strongest of these metal systems which exhibits doublet ratios consistent with saturation in both CaII and Na I. Due to the recent detection in HI emission of a tidal tail or finger of HI extending from the western edge of NGC 3067 through the position of 3C 232 (Carilli, van Gorkom and Stocke, 1989), the morphology of the HI absorber is now known and is not either a warped disk nor a spherical halo as had been proposed. New deep continuum and H alpha imaging provides a sensitive upper limit on the the ionizing continuum impinging upon this cloud (and thus a limit on the intensity of the extragalactic ionizing radiation field). Together with the observed UV spectrum of 3C 232, the optical emission line ratios and the deep H alpha imaging set a minimum distance between the quasar and the HI cloud disregarding redshift information. This limit strains the non-cosmological redshift interpretation for 3C 232 -- and this quasar is one of the original 5 3C quasars found to be too close to NGC galaxies as if by chance (Burbidge, Burbidge, Solomon and Strittmatter, 1972)

Options for the Continuing Evolution of the Earth Science Constellation

No abstract availabl

The language of leadership in Laos

© 2016, © The Author(s) 2016. This paper responds to recent calls in the leadership studies literature for anthropologically informed empirical research on leadership phenomena in non-Western and non-Anglophone settings. The authors have worked extensively on rural development projects in Laos and draw on ethnographic ‘observant-participation’ and interview data to explore how leadership is construed in a contested terrain where traditional concepts intersect with those of official government and international development agencies. A theoretical discussion of linguistic relativity and the socially constitutive nature of language in general is offered as background justification for studying the language of leadership in context. The anthropological distinction between etic and emic operations is also introduced to differentiate between various interpretative positions that can be taken in relation to the fieldwork and data discussed in this paper. The study shows how difficult it can be for native Lao speakers to find words to describe leadership or give designations to ‘leaders’ outside of officially sanctioned semantic and social fields. A key finding of the study is that, viewed from the perspective of the Lao People’s Revolutionary Party, authority and leadership are coextensive. This social fact is reflected in the linguistic restrictions on what can and cannot be described as leadership in Laos

Leverage Your Science Data Return by Flying with the International Earth Science Constellation (ESC)

Constellations have proven to be an effective and efficient way to acquire earth science data. By flying together, sensors on all satellites in a constellation take measurements of the same air, water, or land mass at essentially the same time. The sensors form a single "virtual satellite". The key to making a constellation effective and efficient is keeping the operations as independent as possible in order to minimize the operational burden and costs. The Earth Science Constellation (ESC) has been successful on all counts and continues to welcome new missions to continue its 18+ year record of coincidental earth science observations. The ESC also serves as a model for future constellation designs. This paper describes the ESC and its evolution from its initial launches in 1999 through the present and how new missions might benefit from joining the ESC

Multi-objective optimisation of product modularity

The optimal modular configuration of a product’s architecture can lead to many advantages throughout the product lifecycle. Advantages such as: ease of product upgrade, maintenance, repair and disposal, increased product variety and greater product development speed. However, finding an optimal modular configuration is often difficult. Finding a solution will invariably mean trade-offs will have to be made between various lifecycle drivers. One of the main strengths of a computerised optimisation is that trade-off analysis becomes simple and straightforward and hence speeds up the product architecture decision making process. However, there are a lack of computerised methods that can be applied to optimise modularity for multiple lifecycle objectives. To this end, an integrated optimisation framework has been developed to optimise modularity from a whole lifecycle perspective, namely, design, production, use and end of life. For each lifecycle phase there are two modularity criteria- module independence and module coherence. The criteria that fall under the category of module independence evaluate the degree of coupling between the products components, coupling can be physical, functional or design based. Criteria under module coherence, evaluate the similarity of modular drivers between components. The paper will examine the developed optimisation framework and software prototype. The prototype software uses a number of matrixes to represent the product architecture. A goal based genetic algorithm is used to search the matrixes for modular configurations that most satisfies the criteria of the four lifecycle phases. Sensitively analysis is carried out by changing the goal weights

Product lifecycle optimisation of car climate controls using analytical hierarchical process (Ahp) analysis and a multi-objective grouping genetic algorithm (mogga)

© School of Engineering, Taylor’s University. A product’s lifecycle performance (e.g. assembly, outsourcing, maintenance and recycling) can often be improved through modularity. However, modularisation under different and often conflicting lifecycle objectives is a complex problem that will ultimately require trade-offs. This paper presents a novel multi-objective modularity optimisation framework; the application of which is illustrated through the modularisation of a car climate control system. Central to the framework is a specially designed multi-objective grouping genetic algorithm (MOGGA) that is able to generate a whole range of alternative product modularisations. Scenario analysis, using the principles of the analytical hierarchical process (AHP), is then carried out to explore the solution set and choose a suitable modular architecture that optimises the product lifecycle according to the company’s strategic vision

Exploring alternative product modularisations with multi-objective optimisation

This paper presents a multi-objective optimisation framework for product modularisation. At the heart of the software is a custom developed genetic algorithm that is able to generate a whole range of alternative product modularisations. Once generated, the solution set is then explored to examine the inherent trade-offs needed. In this way the decision maker is able to choose the most suitable modular architecture ac-cording to the company’s strategic objectives. The focus of this paper is to illustrate the developed computerised framework using an example product: a car climate control system

Multi-objective grouping genetic algorithm for product life-cycle optimisation

A product’s lifecycle performance (e.g. assembly, outsourcing, maintenance and recycling) can often be improved through modularity. However, modularisation under different and often conflicting lifecycle objectives is a complex problem that will ultimately require trade-offs. This paper presents a novel multi-objective modularity optimisation framework; the application of which is illustrated through the modularisation of a car climate control system. Central to the framework is a specially designed multi-objective grouping genetic algorithm (MOGGA) that is able to generate a whole range of alternative product modularisations. Scenario analysis, using the principles of the analytical hierarchical process (AHP), is then carried out to explore the solution set and choose a suitable modular architecture that optimises the product lifecycle according to the company’s strategic vision