Great Lakes coastal fish habitat classification and assessment

Basin-scale assessment of fish habitat in Great Lakes coastal ecosystems would increase our ability to prioritize fish habitat management and restoration actions. As a first step in this direction, we identified key habitat factors associated with highest probability of occurrence for several societally and ecologically important coastal fish species as well as community metrics, using data from the Great Lakes Aquatic Habitat Framework (GLAHF), Great Lakes Environmental Indicators (GLEI) and Coastal Wetland Monitoring Program (CWMP). Secondly, we assessed whether species-specific habitat was threatened by watershed-level anthropogenic stressors. In the southern Great Lakes, key habitat factors for determining presence/absence of several species of coastal fish were chlorophyll concentrations, turbidity, and wave height, whereas in the northern ecoprovince temperature was the major habitat driver for most of the species modeled. Habitat factors best explaining fish richness and diversity were bottom slope and chlorophyll a. These models could likely be further improved with addition of high-resolution submerged macrophyte complexity data which are currently unavailable at the basin-wide scale. Proportion of invasive species was correlated primarily with increasing maximum observed inorganic turbidity and chlorophyll a. We also demonstrate that preferred habitat for several coastal species and high-diversity areas overlap with areas of high watershed stress. Great Lakes coastal wetland fish are a large contributor to ecosystem services as well as commercial and recreational fishery harvest, and scalable basin-wide habitat models developed in this study may be useful for informing management actions targeting specific species or overall coastal fish biodiversity.     

Estimating the motion of plant root cells from in vivo confocal laser scanning microscopy images

Images of cellular structures in growing plant roots acquired using confocal laser scanning microscopy have some unusual properties that make motion estimation challenging. These include multiple motions, non-Gaussian noise and large regions with little spatial structure. In this paper, a method for motion estimation is described that uses a robust multi-frame likelihood model and a technique for estimating uncertainty. An efficient region-based matching approach was used followed by a forward projection method. Over small timescales the dynamics are simple (approximately locally constant) and the change in appearance small. Therefore, a constant local velocity model is used and the MAP estimate of the joint probability over a set of frames is recovered. Occurrences of multiple modes in the posterior are detected, and in the case of a single dominant mode, motion is inferred using Laplace’e method. The method was applied to several Arabidopsis thaliana root growth sequences with varying levels of success. In addition, comparative results are given for three alternative motion estimation approaches, the Kanade–Lucas–Tomasi tracker, Black and Anandan’s robust smoothing method, and Markov random field based methods.     

Competence Models and the Maintenance Problem

Case-based reasoning (CBR) systems solve problems by retrieving and adapting the solutions to similar problems that have been stored previously as a case base of individual problem solving episodes or cases. The maintenance problem refers to the problem of how to optimize the performance of a CBR system during its operational lifetime. It can have a significant impact on all the knowledge sources associated with a system (the case base, the similarity knowledge, the adaptation knowledge, etc.), and over time, any one, or more, of these knowledge sources may need to be adapted to better fit the current problem-solving environment. For example, many maintenance solutions focus on the maintenance of case knowledge by adding, deleting, or editing cases. This has lead to a renewed interest in the issue of case competence, since many maintenance solutions must ensure that system competence is not adversely affected by the maintenance process. In fact, we argue that ultimately any generic maintenance solution must explicitly incorporate competence factors into its maintenance policies. For this reason, in our work we have focused on developing explanatory and predictive models of case competence that can provide a sound foundation for future maintenance solutions. In this article we provide a comprehensive survey of this research, and we show how these models have been used to develop a number of innovative and successful maintenance solutions to a variety of different maintenance problems.     

Creating convivial affordances: A study of virtual world social movements

The study of technology and societal challenges is a growing area in information systems research. This paper explores how social movements can use virtual worlds to raise awareness or create safe spaces for their members. As social movements move into virtual worlds, the technical environment becomes more important. This paper presents an interpretive field study using netnographic research and empirical data from a study of a lesbian, gay, bisexual, and transgender social movement in World of Warcraft. This paper takes the position that an understanding of affordances is required for users to be able to create convivial outcomes to shape the use of virtual worlds for their own goals and intentions. The paper presents the concept of convivial affordances, which brings together the theories of affordances and conviviality, and suggests that social users can shape IT artefacts through a creative combination of affordances for their specific goals, and with community involvement.     

Bio‐Based Hybrid Magnetic Latex Particles Containing Encapsulated γ ‐Fe2O3 by Miniemulsion Copolymerization of Soybean Oil‐Acrylated Methyl Ester and Styrene

This work reports the use of acrylated fatty acid methyl ester (AFAME) as a biomonomer for the synthesis of bio‐based hybrid magnetic particles poly(styrene‐co‐AFAME)/γ‐Fe₂O₃ produced by miniemulsion polymerization. Poly(styrene‐co‐AFAME)/γ‐Fe₂O₃ can be tailored for use in various fields by varying the content of AFAME. The strategy employed is to encapsulate superparamagnetic iron oxide nanoparticles (SPIONs) as γ‐Fe₂O₃ into a styrene/AFAME‐based copolymer matrix. Raman spectroscopy is employed to ensure the formation of the SPIONs (γ‐Fe₂O₃) obtained by a co‐precipitation technique followed by oxidation of Fe₃O₄. The functionalization of SPIONs with oleic acid (OA) is carried out to increase the SPIONs–monomer affinity. The presence of OA on the surface of γ‐Fe₂O₃ is certified by identification of main absorption bands by fourier‐transform infrared spectroscopy (FTIR). Thermal analysis (differential thermogravimetry/differential thermo analysis and differential scanning calorimetry) results of poly(styrene‐co‐AFAME)/γ‐Fe₂O₃ show an increase in AFAME content leading to a lower copolymer glass transition temperature (T _g). Dynamic light scattering (DLS) measurements result in poly(styrene‐co‐AFAME)/γ‐Fe₂O₃ particles with diameter in the range of 100–150 nm. It is also observed by transmission electron microscopy (TEM) and cryo‐TEM techniques that γ‐Fe₂O₃ particles are successfully encapsulated into the poly(styrene‐co‐AFAME) matrix.     

Impact of silica pore structure on the performance of metallocene catalysts in ethylene gas-phase polymerization

Several commercial silicas were used to support metallocene active centres, and the resulting precatalysts were used to study the impact of the pore size and pore size distribution of the support on the polymerization kinetics and resulting polymer properties. Pore volume distribution played a major role in the fragmentation of silica-supported catalysts, where mesoporous silicas with a narrow distribution in the region obtained higher activities and faster fragmentation than silicas with a broad pore volume distribution. Therefore, it is shown that care must be taken when using standard information on particle porosity, as this quantity can be misleading. It appears that the minimum pore size, particularly on the particle surface, can be a very important parameter even if it does not impact the estimate of the porosity.