CO2Y the intelligent green solution: minimising carbon emissions by maximising shared travel opportunity.

It is in the interests of everybody that the environment is protected. In view of the recent leaps in environmental awareness it would seem timely and sensible, therefore, for people to pool vehicle resources to minimise the damaging impact of emissions. However, this is often contrary to how complex social systems behave – local decisions made by self-interested individuals often have emergent effects that are in the interests of nobody. For software engineers a major challenge is to help facilitate individual decision-making such that individual preferences can be met, which, when accumulated, minimise adverse effects at the level of the transport system. We introduce this general problem through a concrete example based on vehicle-sharing. Firstly, we outline the kind of complex transportation problem that is directly addressed by our technology (CO2y™ - pronounced “cosy”), and also show how this differs from other more basic software solutions. The CO2y™ architecture is then briefly introduced. We outline the practical advantages of the advanced, intelligent software technology that is designed to satisfy a number of individual preference criteria and thereby find appropriate matches within a population of vehicle-share users. An example scenario of use is put forward, i.e., minimisation of grey-fleets within a medium-sized company. Here we comment on some of the underlying assumptions of the scenario, and how in a detailed real-world situation such assumptions might differ between different companies, and individual users. Finally, we summarise the paper, and conclude by outlining how the problem of pooled transportation is likely to benefit from the further application of emergent, nature-inspired computing technologies. These technologies allow systems-level behaviour to be optimised with explicit representation of individual actors. With these techniques we hope to make real progress in facing the complexity challenges that transportation problems produce.

An assessment of the ability of the stay-green phenotype in Lolium species to provide an improved protein supply for ruminants

Kingston-Smith, A. H., Bollard, A. L., Humphreys, M. O,, Theodorou, M. K. (2002). An assessment of the ability of the stay-green phenotype in Lolium species to provide an improved protein supply for ruminants. Annals of Botany, 89(6), 731-740. Sponsorship: BBSRC/MAFF/Milk Development Council/Meat and Livestock Commission/Industry. RAE2008

AberNile - Stay-Green Perennial Ryegrass

Groupement National Interprofessionnel des Semences et plantes pp. Sponsorship: Industry RAE2008

Effects of a stay-green mutation on plant nitrogen relations in Lolium perenne during N starvation and after defoliation

Macduff, J. H., Humphreys, M. O., Thomas, Howard (2002). Effects of a stay-green mutation on plant nitrogen relations in Lolium perenne during N starvation and after defoliation. Annals of Botany, 89 (1), 11-21. Sponsorship: BBSRC RAE2008

Differences in growth and nitrogen productivity between a stay-green genotype and a wild-type of Lolium perenne under limiting relative addition rates of nitrate supply

James Macduff, Neil Raistrick and Mervyn Humphreys (2002). Differences in growth and nitrogen productivity between a stay-green genotype and a wild-type of Lolium perenne under limiting relative addition rates of nitrate supply. Physiologia Plantarum, 116 (1), 52-61. Sponsorship: BBSRC RAE2008

The mission of Methodism : being the twentieth Fernley lecture, delivered in Bristol, August 4th, 1890 / by Richard Green.

http://www.archive.org/details/themissionofmeth00greeuoft

Load Profiling for Efficient Route Selection in Multi-Class Networks

High-speed networks, such as ATM networks, are expected to support diverse Quality of Service (QoS) constraints, including real-time QoS guarantees. Real-time QoS is required by many applications such as those that involve voice and video communication. To support such services, routing algorithms that allow applications to reserve the needed bandwidth over a Virtual Circuit (VC) have been proposed. Commonly, these bandwidth-reservation algorithms assign VCs to routes using the least-loaded concept, and thus result in balancing the load over the set of all candidate routes. In this paper, we show that for such reservation-based protocols|which allow for the exclusive use of a preset fraction of a resource's bandwidth for an extended period of time-load balancing is not desirable as it results in resource fragmentation, which adversely affects the likelihood of accepting new reservations. In particular, we show that load-balancing VC routing algorithms are not appropriate when the main objective of the routing protocol is to increase the probability of finding routes that satisfy incoming VC requests, as opposed to equalizing the bandwidth utilization along the various routes. We present an on-line VC routing scheme that is based on the concept of "load profiling", which allows a distribution of "available" bandwidth across a set of candidate routes to match the characteristics of incoming VC QoS requests. We show the effectiveness of our load-profiling approach when compared to traditional load-balancing and load-packing VC routing schemes.

GreenCoop: Cooperative Green Routing with Energy-efficient Servers

Energy-efficient communication has recently become a key challenge for both researchers and industries. In this paper, we propose a new model in which a Content Provider and an Internet Service Provider cooperate to reduce the total power consumption. We solve the problem optimally and compare it with a classic formulation, whose aim is to minimize user delay. Results, although preliminary, show that power savings can be huge: up to 71% on real ISP topologies. We also show how the degree of cooperation impacts overall power consumption. Finally, we consider the impact of the Content Provider location on the total power savings.

A Neural Model of Visually Guided Steering, Obstacle Avoidance, and Route Selection

A neural model is developed to explain how humans can approach a goal object on foot while steering around obstacles to avoid collisions in a cluttered environment. The model uses optic flow from a 3D virtual reality environment to determine the position of objects based on motion discotinuities, and computes heading direction, or the direction of self-motion, from global optic flow. The cortical representation of heading interacts with the representations of a goal and obstacles such that the goal acts as an attractor of heading, while obstacles act as repellers. In addition the model maintains fixation on the goal object by generating smooth pursuit eye movements. Eye rotations can distort the optic flow field, complicating heading perception, and the model uses extraretinal signals to correct for this distortion and accurately represent heading. The model explains how motion processing mechanisms in cortical areas MT, MST, and VIP can be used to guide steering. The model quantitatively simulates human psychophysical data about visually-guided steering, obstacle avoidance, and route selection.

A Neural Model of Visually Guided Steering, Obstacle Avoidance, and Route Selection

A neural model is developed to explain how humans can approach a goal object on foot while steering around obstacles to avoid collisions in a cluttered environment. The model uses optic flow from a 3D virtual reality environment to determine the position of objects based on motion discontinuities, and computes heading direction, or the direction of self-motion, from global optic flow. The cortical representation of heading interacts with the representations of a goal and obstacles such that the goal acts as an attractor of heading, while obstacles act as repellers. In addition the model maintains fixation on the goal object by generating smooth pursuit eye movements. Eye rotations can distort the optic flow field, complicating heading perception, and the model uses extraretinal signals to correct for this distortion and accurately represent heading. The model explains how motion processing mechanisms in cortical areas MT, MST, and posterior parietal cortex can be used to guide steering. The model quantitatively simulates human psychophysical data about visually-guided steering, obstacle avoidance, and route selection.

Energy-aware dynamic route management for THAWS

In this research we focus on the Tyndall 25mm and 10mm nodes energy-aware topology management to extend sensor network lifespan and optimise node power consumption. The two tiered Tyndall Heterogeneous Automated Wireless Sensors (THAWS) tool is used to quickly create and configure application-specific sensor networks. To this end, we propose to implement a distributed route discovery algorithm and a practical energy-aware reaction model on the 25mm nodes. Triggered by the energy-warning events, the miniaturised Tyndall 10mm data collector nodes adaptively and periodically change their association to 25mm base station nodes, while 25mm nodes also change the inter-connections between themselves, which results in reconfiguration of the 25mm nodes tier topology. The distributed routing protocol uses combined weight functions to balance the sensor network traffic. A system level simulation is used to quantify the benefit of the route management framework when compared to other state of the art approaches in terms of the system power-saving.

A cycle route planner mobile-app for Dublin city

In a road network, cyclists are the group exposed to the maximum amount of risk. Route choice of a cyclist is often based on level of expertise, perceived or actual road risks, personal decisions, weather conditions and a number of other factors. Consequently, cycling tends to be the only significant travel mode where optimised route choice is not based on least-path or least-time. This paper presents an Android platform based mobile-app for personalised route planning of cyclists in Dublin. The mobile-app, apart from its immediate advantage to the cyclists, acts as the departure point for a number of research projects and aids in establishing some critical calibration values for the cycling network in Dublin. 

“Green preservatives” – combating fungi in the food industry by applying antifungal lactic acid bacteria

Fungal spoilage is the most common type of microbial spoilage in food leading to significant economical and health problems throughout the world. Fermentation by lactic acid bacteria (LAB) is one of the oldest and most economical methods of producing and preserving food. Thus, LAB can be seen as an interesting tool in the development of novel bio-preservatives for food industry. The overall objective of this study was to demonstrate, that LAB can be used as a natural way to improve the shelf-life and safety of a wide range of food products. In the first part of the thesis, 116 LAB isolates were screened for their antifungal activity against four Aspergillus and Penicillium spp. commonly found in food. Approximately 83% of them showed antifungal activity, but only 1% showed a broad range antifungal activity against all tested fungi. The second approach was to apply LAB antifungal strains in production of food products with extended shelf-life. L. reuteri R29 strain was identified as having strong antifungal activity in vitro, as well as in sourdough bread against Aspergillus niger, Fusarium culmorum and Penicillium expansum. The ability of the strain to produce bread of good quality was also determined using standard baking tests. Another strain, L. amylovorus DSM19280, was also identified as having strong antifungal activity in vitro and in vivo. The strain was used as an adjunct culture in a Cheddar cheese model system and demonstrated the inhibition of P. expansum. Significantly, its presence had no detectable negative impact on cheese quality as determined by analysis of moisture, salt, pH, and primary and secondary proteolysis. L. brevis PS1 a further strain identified during the screening as very antifungal, showed activity in vitro against common Fusarium spp. and was used in the production of a novel functional wortbased alcohol-free beverage. Challenge tests performed with F. culmorum confirmed the effectiveness of the antifungal strain in vivo. The shelf-life of the beverage was extended significantly when compared to not inoculated wort sample. A range of antifungal compounds were identified for the 4 LAB strains, namely L. reuteri ee1p, L. reuteri R29, L. brevis PS1 and L. amylovorous DSM20531. The identification of the compounds was based on liquid chromatography interfaced to the mass spectrometer and PDA detector

Multi-party actions as a route to collective redress for mass arm, having particular regard to environmental mass harm

Accepted Version

Inhibition of adaptive immune responses leads to a fatal clinical outcome in SIV-infected pigtailed macaques but not vervet African green monkeys.

African green monkeys (AGM) and other natural hosts for simian immunodeficiency virus (SIV) do not develop an AIDS-like disease following SIV infection. To evaluate differences in the role of SIV-specific adaptive immune responses between natural and nonnatural hosts, we used SIV(agmVer90) to infect vervet AGM and pigtailed macaques (PTM). This infection results in robust viral replication in both vervet AGM and pigtailed macaques (PTM) but only induces AIDS in the latter species. We delayed the development of adaptive immune responses through combined administration of anti-CD8 and anti-CD20 lymphocyte-depleting antibodies during primary infection of PTM (n = 4) and AGM (n = 4), and compared these animals to historical controls infected with the same virus. Lymphocyte depletion resulted in a 1-log increase in primary viremia and a 4-log increase in post-acute viremia in PTM. Three of the four PTM had to be euthanized within 6 weeks of inoculation due to massive CMV reactivation and disease. In contrast, all four lymphocyte-depleted AGM remained healthy. The lymphocyte-depleted AGM showed only a trend toward a prolongation in peak viremia but the groups were indistinguishable during chronic infection. These data show that adaptive immune responses are critical for controlling disease progression in pathogenic SIV infection in PTM. However, the maintenance of a disease-free course of SIV infection in AGM likely depends on a number of mechanisms including non-adaptive immune mechanisms.