Autonomous search for a diffusive source in an unknown environment

The paper presents an approach to olfactory search for a diffusive emitting source of tracer (e.g. aerosol, gas) in an environment with unknown map of randomly placed and shaped obstacles. The measurements of tracer concentration are sporadic, noisy and without directional information. The search domain is discretised and modelled by a finite two-dimensional lattice. The links is the lattice represent the traversable paths for emitted particles and for the searcher. A missing link in the lattice indicates a blocked paths, due to the walls or obstacles. The searcher must simultaneously estimate the source parameters, the map of the search domain and its own location within the map. The solution is formulated in the sequential Bayesian framework and implemented as a Rao-Blackwellised particle filter with information-driven motion control. The numerical results demonstrate the concept and its performance.Comment: 11 pages, 7 figure

Decentralised Scalable Search for a Hazardous Source in Turbulent Conditions

The problem is autonomous coordinated search by an interconnected group of moving robots for the purpose of finding and localising a source of hazardous emissions (e.g., gas and particles). Dispersion of the emitted substance is assumed to be affected by turbulence, resulting in the absence of concentration gradients. The chapter proposes a search strategy that operates in a completely decentralised manner, as long as the communication network of the moving robots forms a connected graph. By decentralised operation, we mean that each moving robot is reasoning (i.e., estimating the source location and making decisions on robot motion) locally. Coordination of the group is achieved by consensus via communication with the neighbours only, in a manner which does not require global knowledge of the communication network topology

Bacterial infections associated with allogenic bone transplantation

© 2015, Institut za Vojnomedicinske Naucne Informacije/Documentaciju. All Rights Reserved. Background/Aim. Bone allografts are frequently used in or-thopedic reconstructive procedures carrying a high risk for re-cipients. To assess the nature and frequency of allograft con-tamination and associated surgical infection the case records from our institutional bone bank were reviewed. Methods. We retrospectively analyzed the microbiology of discarded bone al-lografts and the surgical site of the recipients. A case series of patients who acquired surgical site infection after allogenic bone transplantation was presented. Swab culturing was con-ducted on 309 femoral heads from living donors who under-went partial and total hip arthroplasty between January 2007 and December 2013. To prevent potential bone allograft con-tamination we used saline solution of 2.0 mg/ml of amikacin during thawing. The overall infection rate was analyzed in 197 recipients. Results. Of the 309 donated femoral heads, 37 were discarded due to bacterial contamination, giving the overall contamination rate of 11.97%. The postoperative survey of 213 bone allotransplantations among 197 recipients showed the in-fection rate of 2.03%. The coagulase-negative Staphylococcus was the most commonly identified contaminant of bone allografts and recipient surgical sites. Conclusion. The allograft con-tamination rate and the infection rate among recipients in our institution are in accordance with the international standards. The coagulase-negative Staphylococcus was the most commonly identified contaminant of bone allografts and recipient surgical sites. There is no strong evidence that surgical site infections were associated with bone allograft utilization. We plan further improvements in allograft handling and decontamination with highly concentrated antibiotic solutions in order to reduce in-fection risk for recipients

Modelling and Performance analysis of a Network of Chemical Sensors with Dynamic Collaboration

The problem of environmental monitoring using a wireless network of chemical sensors with a limited energy supply is considered. Since the conventional chemical sensors in active mode consume vast amounts of energy, an optimisation problem arises in the context of a balance between the energy consumption and the detection capabilities of such a network. A protocol based on "dynamic sensor collaboration" is employed: in the absence of any pollutant, majority of sensors are in the sleep (passive) mode; a sensor is invoked (activated) by wake-up messages from its neighbors only when more information is required. The paper proposes a mathematical model of a network of chemical sensors using this protocol. The model provides valuable insights into the network behavior and near optimal capacity design (energy consumption against detection). An analytical model of the environment, using turbulent mixing to capture chaotic fluctuations, intermittency and non-homogeneity of the pollutant distribution, is employed in the study. A binary model of a chemical sensor is assumed (a device with threshold detection). The outcome of the study is a set of simple analytical tools for sensor network design, optimisation, and performance analysis.Comment: 21 pages and 7 figure