Functional Modeling for Monitoring of Robotic System

With the expansion of robotic applications in the industrial domain, it is important that the robots can execute their tasks in a safe and reliable way. A monitoring system can be implemented to ensure the detection of abnormal situations of the robots and report the abnormality to their human supervisors or cooperators. In this work, we focus on developing a modeling framework for monitoring robotic system based on means-end analysis and the concept of action phases from action theory. A circular cascaded action phase structure is proposed for building the model of cyclical robotic events. This functional model provide a formal way of decompose robotic tasks and analyze each level of conditions for an action to be executed successfully. It can be used for monitoring robotic systems by checking the preconditions in the action phases and identifying the failure modes. The proposed method is demonstrated by using a simulated robotic manipulation system. The simulation results demonstrate the feasibility of the developed functional model in finding errors during the execution monitoring.     

High temperature electrolyte supported Ni-GDC/YSZ/LSM SOFC operation on two-stage Viking gasifier product gas

This paper presents the results from a 150 h test of a commercial high temperature single planar solid oxide fuel cell (SOFC) operating on wood gas from the Viking two-stage fixed-bed downdraft gasifier, which produces an almost tar-free gas, that was further cleaned for particulates, sulphur and tar traces. The chosen SOFC was electrolyte supported with a nickel/gadolinium-doped cerium oxide (Ni-GDC) anode, known for its carbon deposition resistance. Through humidification the steam to carbon ratio (S/C) was adjusted to 0.5, which results in a thermodynamically carbon free condition at the SOFC operating temperature T = 850 °C. The cell operated with a fuel utilisation factor (U_f) around 30% and a current density of 260 mA cm⁻² resulting in an average power density of 207 mW cm⁻². Throughout the duration of the test, only a minor cell overpotential increase of 10 mV was observed. Nevertheless, the V–j (voltage–current density) curves on H₂/N₂ before and after the wood gas test proved identical. Extensive SEM/EDS examination of the cell's anode showed that there was neither carbon deposition nor significant shifts in the anode microstructure or contamination when compared to an identical cell tested on H₂/N₂ only.     

Safe and Effective Ag Nanoparticles Immobilized Antimicrobial NanoNonwovens

Silver nanoparticles (AgNPs) with large surface‐to‐volume ratio have been widely studied as a valuable material for their strong antimicrobial effect. However, the practical applications of AgNPs in health care and water purification are often hampered by the concern of their toxicity and possibility of introduction of secondary pollution. Here, we present a novel strategy to produce a safe and effective antimicrobial nanononwoven material by immobilizing AgNPs on a rigid polymer nanofibrous matrix through simple co‐electrospinning of pre‐prepaired AgNPs and polystyrene (PS). Distribution of the AgNPs on the surface of PS fibers was achieved by tuning fiber diameters during electrospinning. Atomic force microscopy (AFM) analysis revealed that the AgNPs distributed at the fiber surface were still covered by a layer of polymer, which inhibited their antimicrobial activity. UV/ozone treatment was thus employed to degrade the polymer coating without loosening the AgNPs, resulting in an active antimicrobial nonwoven against Gram‐positive Staphylococcus xylosus. The mechanism based on cellular uptake of silver ions via close contact to the surface of AgNPs is proposed. The novel nanononwoven retains the enhanced antimicrobial activities from nanofeatured AgNPs without detectable AgNPs leaching, which holds great potential for safe and recyclable use.     

An evolutionary Bayesian belief network methodology for optimum management of groundwater contamination

An integrated methodology, based on Bayesian belief network (BBN) and evolutionary multi-objective optimization (EMO), is proposed for combining available evidence to help water managers evaluate implications, including costs and benefits of alternative actions, and suggest best decision pathways under uncertainty. A Bayesian belief network is a probabilistic graphical model that represents a set of variables and their probabilistic relationships, which also captures historical information about these dependencies. In complex applications where the task of defining the network could be difficult, the proposed methodology can be used in validation of the network structure and the parameters of the probabilistic relationship. Furthermore, in decision problems where it is difficult to choose appropriate combinations of interventions, the states of key variables under the full range of management options cannot be analyzed using a Bayesian belief network alone as a decision support tool. The proposed optimization method is used to deal with complexity in learning about actions and probabilities and also to perform inference. The optimization algorithm generates the state variable values which are fed into the Bayesian belief network. It is possible then to calculate the probabilities for all nodes in the network (belief propagation). Once the probabilities of all the linked nodes have been updated, the objective function values are returned to the optimization tool and the process is repeated. The proposed integrated methodology can help in dealing with uncertainties in decision making pertaining to human behavior. It also eliminates the shortcoming of Bayesian belief networks in introducing boundary constraints on probability of state values of the variables. The effectiveness of the proposed methodology is examined in optimum management of groundwater contamination risks for a well field capture zone outside Copenhagen city.     

Sorption of organic compounds to fresh and field-aged activated carbons in soils and sediments

Activated carbon (AC) amendment to polluted sediment or soil is an emerging in situ treatment technique that reduces freely dissolved porewater concentrations and subsequently reduces the ecological and human health risk of hydrophobic organic compounds (HOCs). An important question is the capacity of the amended AC after prolonged exposure in the field. To address this issue, sorption of freshly spiked and native HOCs to AC aged under natural field conditions and fresh AC amendments was compared for one soil and two sediments. After 12-32 months of field aging, all AC amendments demonstrated effectiveness for reducing pore water concentrations of both native (30-95%) and spiked (10-90%) HOCs compared to unamended sediment or soil. Values of K(AC) for field-aged AC were lower than freshly added AC for spiked HOCs up to a factor of 10, while the effect was less for native HOCs. The different behavior in sorbing native HOCs compared to freshly spiked HOCs was attributed to differences in the sorption kinetics and degree of competition for sorption sites between the contaminants and pore-clogging natural organic matter. The implications of these findings are that amended AC can still be effective in sorbing additional HOCs some years following amendment in the field. Thus, a certain level of long-term sustainability of this remediation approach is observed, but conclusions for decade-long periods cannot be drawn solely based on the present study.     

Immobilisation of living bacteria for AFM imaging under physiological conditions

Atomic force microscopy (AFM) holds great potential for studying the nanoscale surface structures of living cells, and to measure their interactions with abiotic surfaces, other cells, or specific biomolecules. However, the application of AFM in microbiology is challenging due to the difficulty of immobilising bacterial cells to a flat surface without changing the cell surface properties or cell viability. We have performed an extensive and thorough study of how to functionalise surfaces in order to immobilise living bacteria for AFM studies in liquid environments. Our aim was to develop a scheme which allows bacterial cells to be immobilised to a flat surface with sufficient strength to avoid detachment during the AFM scanning, and without affecting cell surface chemistry, structure, and viability. We compare and evaluate published methods, and present a new, reproducible, and generally applicable scheme for immobilising bacteria cells for an AFM imaging.