Using Automated Negotiation for Grid Services

The popularity of grid services has widened their application to numerous domains and increased the utilization of computational resources. In order to create more incentives for the resources owners to lease their resources and prevent users from wasting the resources, the introduction of a market-oriented grid is inevitable. However, the issues for the negotiation between service provider and consumer over the supply and demand of resources can be complex, with highly interdependent issues. In this research, a simulated automated negotiation mechanism including a co-evolutionary mechanism and a modified game theory approach is proposed, to assist them in reaching an agreement over the conflicting issues. In the proposed architecture, the co-evolution process is able to reduce the multiple dimensional search space into a two-dimension search space and identify the appropriate negotiation strategies for the negotiating agents to form a payoff matrix which can be used for the game theory related stage of their interaction. The multiple stage negotiation process is introduced to improve the negotiation result. In this paper, an application which requires a large amount of computational resources to process the data generated from mobile devises is used to demonstrate that the proposed system is able to resolve the conflicts and obtain a valid solution.     

The lipid composition of selected tissues from a Mediterranean monk seal,Monachus monachus

The lipid composition of blubber, brain, muscle and heart from a Mediterranean monk sealMonachus monachus (an endangered species) were examined to allow comparisons with more common species of seals. Only neutral lipids (mainly triacylglycerols) were detectable in the blubber lipids, whereas polar lipids predominated in the heart and in the brain. Neutral and polar lipids comprised almost equal proportions in both liver and muscle. Choline glycerophospholipids (CGP) were the major polar lipids, followed by ethanolamine glycerophospholipids (EGP) in the liver, heart and muscle. Cerebrosides accounted for 28.8% of the brain lipids. All lipid classes of the liver contained high levels (31–47%) of polyunsaturated fatty acids (PUFA), with the exception of phosphatidylserine. The total proportion of n−6 PUFA exceeded that of n−3 PUFA in all lipid classes of the liver, due mainly to the high levels of 20∶4n−6. The highest level of 20∶4n−6 occurred in phosphatidylinositol, where it comprised 32.4% of the total fatty acids. The CGP and EGP of the brain contained lower levels of PUFA than those of the liver, muscle and heart. Alkenyl ethers accounted for 35.8% of the total long-chain moieties in brain EGP. The fatty acid composition of blubber triacylglycerols differed from those of the lipid classes from other tissues in that it had a very low ratio of n−6 to n−3 PUFA (0.3) as a result of a lower content of 20∶4n−6.     

Rainbow smelt population responses to species invasions and change in environmental condition

Invasive species can cause major disruptions in native food webs, yet the impact of species introductions and whether they will become invasive appears to be context-dependent. Rainbow smelt and alewife co-exist as invasive species in the Laurentian Great Lakes and as native species on the Atlantic coast of North America, but in Lake Champlain rainbow smelt is the dominant native forage fish and alewife are invasive. Alewife became abundant by 2007, providing an opportunity to explore the dynamics of these two species in a system where only one is invasive. We used data from a 28-year forage fish survey to compare demographics of rainbow smelt populations in three basins of Lake Champlain with different volumes, nutrient levels, and predator abundances. Rainbow smelt catch-per-unit-effort (CPUE) remained constant in the large, deep Main Lake before and after alewife invaded, but decreased in the two smaller basins. Declines were primarily a result of increased age-0 and age-1 mortality. Predation by top piscivores, system productivity, and competition for resources alone could not explain the patterns in CPUE across the basins. The mechanisms that allow alewife and rainbow smelt to co-exist could be related to system volume and oxythermal habitat availability, and may explain why the two species do not negatively affect each other in the Great Lakes. Summer hypoxia in the smaller basins could force individuals into smaller habitat volumes with higher densities of competitors and cannibalistic adult rainbow smelt. Habitat availability may mediate the impact of invasive alewife on native rainbow smelt.     

Biomarkers for Cancer Cachexia: A Mini Review

Cancer cachexia is a common condition in many cancer patients, particularly those with advanced disease. Cancer cachexia patients are generally less tolerant to chemotherapies and radiotherapies, largely limiting their treatment options. While the search for treatments of this condition are ongoing, standards for the efficacy of treatments have yet to be developed. Current diagnostic criteria for cancer cachexia are primarily based on loss of body mass and muscle function. However, these criteria are rather limiting, and in time, when weight loss is noticeable, it may be too late for treatment. Consequently, biomarkers for cancer cachexia would be valuable adjuncts to current diagnostic criteria, and for assessing potential treatments. Using high throughput methods such as “omics approaches”, a plethora of potential biomarkers have been identified. This article reviews and summarizes current studies of biomarkers for cancer cachexia.     

High aspect ratio gold nanopillars on microelectrodes for neural interfaces

Microelectrode arrays (MEA) have become an established tool in applied and fundamental research. Low impedance at the interface between tissue and conducting electrodes is of utmost importance for the electrical recording or stimulation of electrophysiological active cells such as cardiac myocytes and neurons. A common way to improve this interface is to increase the electrochemically active surface area of the electrode. In this paper the fabrication of microelectrodes covered with very high aspect ratio (AR > 100) gold nanopillars is presented and electrode biocompatibility is investigated using cell culture experiments. The nanopillar electrodes show decreased impedance over the entire scanned frequency range of 1 Hz–100 kHz and an impedance improvement of up to 89.5 at 1 kHz depending on nanopillar height. Neurons adhere well to the substrate and electrodes and signals with amplitudes up to ten times higher than with conventional gold electrodes were recorded in cell culture experiments.     

Dense subgraph maintenance under streaming edge weight updates for real-time story identification

Recent years have witnessed an unprecedented proliferation of social media. People around the globe author, everyday, millions of blog posts, social network status updates, etc. This rich stream of information can be used to identify, on an ongoing basis, emerging stories, and events that capture popular attention. Stories can be identified via groups of tightly coupled real-world entities, namely the people, locations, products, etc, that are involved in the story. The sheer scale and rapid evolution of the data involved necessitate highly efficient techniques for identifying important stories at every point of time. The main challenge in real-time story identification is the maintenance of dense subgraphs (corresponding to groups of tightly coupled entities) under streaming edge weight updates (resulting from a stream of user-generated content). This is the first work to study the efficient maintenance of dense subgraphs under such streaming edge weight updates. For a wide range of definitions of density, we derive theoretical results regarding the magnitude of change that a single edge weight update can cause. Based on these, we propose a novel algorithm, DynDens, which outperforms adaptations of existing techniques to this setting and yields meaningful, intuitive results. Our approach is validated by a thorough experimental evaluation on large-scale real and synthetic datasets.     

Modeling culture in intelligent virtual agents

This work addresses the challenge of creating virtual agents that are able to portray culturally appropriate behavior when interacting with other agents or humans. Because culture influences how people perceive their social reality it is important to have agent models that explicitly consider social elements, such as existing relational factors. We addressed this necessity by integrating culture into a novel model for simulating human social behavior. With this model, we operationalized a particular dimension of culture—individualism versus collectivism—within the context of an interactive narrative scenario that is part of an agent-based tool for intercultural training. Using this scenario we conducted a cross-cultural study in which participants from a collectivistic country (Portugal) were compared with participants from an individualistic country (the Netherlands) in the way they perceived and interacted with agents whose behavior was either individualistic or collectivistic, according to the configuration of the proposed model. In the obtained results, Portuguese subjects rated the collectivistic agents more positively than the Dutch but both countries had a similarly positive opinion about the individualistic agents. This experiment sheds new light on how people from different countries differ when assessing the social appropriateness of virtual agents, while also raising new research questions on this matter.