Water quality monitoring, control and management (WQMCM) framework using collaborative wireless sensor networks

Improving water quality is of global concern, with agricultural practices being the major contributors to reduced water quality. The reuse of nutrient-rich drainage water can be a valuable strategy to gain economic-environmental benefits. However, currently the tools and techniques to allow this do not exist. Therefore, we have proposed a framework, WQMCM, which utilises increasingly common local farm-scale networks across a catchment, adding provision for collaborative information sharing. Using this framework, individual sub-networks can learn their environment and predict the impact of catchment events on their locality, allowing dynamic decision making for local irrigation strategies. Since resource constraints of network nodes (e.g. power consumption, computing power etc.) require a simplified predictive model for discharges, therefore low-dimensional model parameters are derived from the existing National Resource Conservation Method (NRCS), utilising real-time field values. Evaluation of the predictive models, developed using M5 decision trees, demonstrates accuracy of 84-94% compared with the traditional NRCS curve number model. The discharge volume and response time model was tested to perform with 6% relative root mean square error (RRMSE), even for a small training set of around 100 samples; however the discharge response time model required a minimum of 300 training samples to show reasonable performance with 16% RRMS

The outer halos of elliptical galaxies

Recent progress is summarized on the determination of the density distributions of stars and dark matter, stellar kinematics, and stellar population properties, in the extended, low surface brightness halo regions of elliptical galaxies. With integral field absorption spectroscopy and with planetary nebulae as tracers, velocity dispersion and rotation profiles have been followed to ~4 and ~5-8 effective radii, respectively, and in M87 to the outer edge at ~150 kpc. The results are generally consistent with the known dichotomy of elliptical galaxy types, but some galaxies show more complex rotation profiles in their halos and there is a higher incidence of misalignments, indicating triaxiality. Dynamical models have shown a range of slopes for the total mass profiles, and that the inner dark matter densities in ellipticals are higher than in spiral galaxies, indicating earlier assembly redshifts. Analysis of the hot X-ray emitting gas in X-ray bright ellipticals and comparison with dynamical mass determinations indicates that non-thermal components to the pressure may be important in the inner ~10 kpc, and that the properties of these systems are closely related to their group environments. First results on the outer halo stellar population properties do not yet give a clear picture. In the halo of one bright galaxy, lower [alpha/Fe] abundances indicate longer star formation histories pointing towards late accretion of the halo. This is consistent with independent evidence for on-going accretion, and suggests a connection to the observed size evolution of elliptical galaxies with redshift.Comment: 8 pages. Invited review to appear in the proceedings of "Galaxies and their Masks" eds. Block, D.L., Freeman, K.C. & Puerari, I., 2010, Springer (New York

Opportunistic energy trading between co-located energy-harvesting wireless sensor networks

Wireless sensor networks are increasingly using energy harvesting to extend their lifetime and avoid battery replacement. However, ambient energy sources typically exhibit temporal-spatial variation, and complex power management algorithms have been proposed to model and adapt to variation and achieve energy-neutral operation. However, existing algorithms are limited in the scale of spatial variation that they can accommodate, as they are restricted by the physical boundaries of the network. This paper proposes Opportunistic Energy Trading (OET) to overcome this limitation, and allow networks to trade energy to neighbouring networks which may either be heavily energy-constrained or else suffering from a temporary drought of harvested-energy. To show the potential of OET, we present a case study consisting of an energy-constrained battery-powered WSN which neighbours an energy-harvesting WSN. The case study considers a simplified version of OET, whereby the harvesting WSN transfers (i.e. trades for free) its excess energy to the constrained WSN in order to extend its lifetime. The case study is evaluated through simulation, and shows that the lifetime of the energy-constrained network increases by 40% while the effects on the harvesting network can be considered insignificant

Opportunistic direct interconnection between co-located wireless sensor networks

Wireless sensor networks are usually designed to avoid interaction with other networks. To share information, they are usually connected via a backbone network (e.g. the Internet) using gateways. The realization of visions for pervasive computing depends upon effective interconnection between individual networks. As the number of deployed sensor networks increases, the chance of any network having multiple neighbors also increases. In this paper, we argue that a paradigm shift towards ‘opportunistic direct interconnection’ is required. This enables one network to share information or resources with neighboring networks that it was unaware of at design-time. We present OI-MAC, which supports automatic neighbor discovery and cross-boundary data exchange without sacrificing the independence of each network. The effects of discovery and cross-boundary data injection are evaluated using both analytical models and network simulation. Initial results indicate that neighbor discovery has little effect on latency, while energy consumption increases insignificantly compared to ordinary operations of each node. If network traffic is doubled by packets ‘injected’ from a neighboring network, latency increases by around 7% while average power consumption increases by 20%

Haemogregarines and other blood infections from deep demersal fish of the Porcupine Seabight, north-east Atlantic

Giemsa-stained blood smears were examined from 70 deep demersal fish of 27 species in 20 genera, trawled from depths of 747–4143 m in the region of the Porcupine Seabight, north-east Atlantic. Infections were found in four species of teleosts in three families: 1/3 Alepocephalus rostratus and 1/3 Narcetes stomias (Alepocephalidae); 2/3 Antimora rostrata (Moridae); and 1/1 Cataetyx laticeps (Bythitidae). Blood films from C. laticeps and Antimora rostrata were well preserved but those from the other two species were less satisfactory. The blood parasites included two types of haemogregarines, Haemohormidium-like and viral erythrocytic necrosis (VEN)-like infections. Haemogregarina (sensu lato) johnstoni sp. nov. was described from C. laticeps captured at 1541 m. This haemogregarine was unusual in apparently having dimorphic gamonts, some with prominent caps. A second, but monomorphic, haemogregarine found in Alepocephalus rostratus captured from 985 m, was named as Desseria sp. since only extracellular stages were observed. Haemohormidium-like organisms were found in Antimora rostrata taken from 2441 m, and were similar to those described previously from this deep-sea fish. A VEN-like infection from one N. stomias captured from 2567 m was reported. No marked effects on host cells were evident in any of these blood infections.</jats:p