A microbial fuel cell in contaminated ground delineated by electrical self-potential and normalized induced polarization data

There is a growing interest in the use of geophysical methods to aid investigation and monitoring of complex biogeochemical environments, for example delineation of contaminants and microbial activity related to land contamination. We combined geophysical monitoring with chemical and microbiological analysis to create a conceptual biogeochemical model of processes around a contaminant plume within a manufactured gas plant site. Self-potential, induced polarization and electrical resistivity techniques were used to monitor the plume. We propose that an exceptionally strong (>800 mV peak to peak) dipolar SP anomaly represents a microbial fuel cell operating in the subsurface. The electromagnetic and electrical geophysical data delineated a shallow aerobic perched water body containing conductive gasworks waste which acts as the abiotic cathode of microbial fuel cell. This is separated from the plume below by a thin clay layer across the site. Microbiological evidence suggests that degradation of organic contaminants in the plume is dominated by the presence of ammonium and its subsequent degradation. We propose that the degradation of contaminants by microbial communities at the edge of the plume provides a source of electrons and acts as the anode of the fuel cell. We hypothesize that ions and electrons are transferred through the clay layer that was punctured during the trial pitting phase of the investigation. This is inferred to act as an electronic conductor connecting the biologically mediated anode to the abiotic cathode. Integrated electrical geophysical techniques appear well suited to act as rapid, low cost sustainable tools to monitor biodegradation.

Stratification and Monitoring of Juvenile Idiopathic Arthritis Patients by Synovial Proteome Analysis

Juvenile idiopathic arthritis (JIA) comprises a poorly understood group of chronic, childhood onset, autoimmune diseases with variable clinical outcomes. We investigated whether profiling of the synovial fluid (SF) proteome by a fluorescent dye based, two-dimensional gel (DIGE) approach could distinguish patients in whom inflammation extends to affect a large number of joints, early in the disease process. SF samples from 22 JIA patients were analyzed: 10 with oligoarticular arthritis, 5 extended oligoarticular and 7 polyarticular disease. SF samples were labeled with Cy dyes and separated by two-dimensional electrophoresis. Multivariate analyses were used to isolate a panel of proteins which distinguish patient subgroups. Proteins were identified using MALDI-TOF mass spectrometry with expression further verified by Western immunoblotting and immunohistochemistry. Hierarchical clustering based on the expression levels of a set of 40 proteins segregated the extended oligoarticular from the oligoarticular patients (p <0.05). Expression patterns of the isolated protein panel have also been observed over time, as disease spreads to multiple joints. The data indicates that synovial fluid proteome profiles could be used to stratify patients based on risk of disease extension. These protein profiles may also assist in monitoring therapeutic responses over time and help predict joint damage. © 2009 American Chemical Society.

Monitoring of Corrosion in Structural Reinforcing Bars: performance comparison using in-situ fibre optic and electric wire strain gauge systems

Abstract This work addresses the problems of effective in situ measurement of the initiation or the rate of steel corrosion in reinforced concrete structures through the use of optical fiber sensor systems. By undertaking a series of tests over prolonged periods, coupled with acceleration of corrosion, the performance of fiber Bragg grating-based sensor systems attached to high-tensile steel reinforcement bars (ldquorebarsrdquo), and cast into concrete blocks was determined, and the results compared with those from conventional strain gauges where appropriate. The results show the benefits in the use of optical fiber networks under these circumstances and their ability to deliver data when conventional sensors failed.

Measurement-based Method for Wind Farm Power System Oscillations Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This study presents a measurement-based method for the early detection of power system oscillations, with consideration of mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet-based support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in frequency bands, whereas the SVDD method is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude, or that are resonant, can be alarmed to the system operator, to reduce the risk of system instability. The proposed method is exemplified using measured data from a chosen wind farm site.

Statistical-based monitoring of multivariate non-Gaussian systems

The monitoring of multivariate systems that exhibit non-Gaussian behavior is addressed. Existing work advocates the use of independent component analysis (ICA) to extract the underlying non-Gaussian data structure. Since some of the source signals may be Gaussian, the use of principal component analysis (PCA) is proposed to capture the Gaussian and non-Gaussian source signals. A subsequent application of ICA then allows the extraction of non-Gaussian components from the retained principal components (PCs). A further contribution is the utilization of a support vector data description to determine a confidence limit for the non-Gaussian components. Finally, a statistical test is developed for determining how many non-Gaussian components are encapsulated within the retained PCs, and associated monitoring statistics are defined. The utility of the proposed scheme is demonstrated by a simulation example, and the analysis of recorded data from an industrial melter.

Moving window kernel PCA for adaptive monitoring of nonlinear processes

This paper discusses the monitoring of complex nonlinear and time-varying processes. Kernel principal component analysis (KPCA) has gained significant attention as a monitoring tool for nonlinear systems in recent years but relies on a fixed model that cannot be employed for time-varying systems. The contribution of this article is the development of a numerically efficient and memory saving moving window KPCA (MWKPCA) monitoring approach. The proposed technique incorporates an up- and downdating procedure to adapt (i) the data mean and covariance matrix in the feature space and (ii) approximates the eigenvalues and eigenvectors of the Gram matrix. The article shows that the proposed MWKPCA algorithm has a computation complexity of O(N2), whilst batch techniques, e.g. the Lanczos method, are of O(N3). Including the adaptation of the number of retained components and an l-step ahead application of the MWKPCA monitoring model, the paper finally demonstrates the utility of the proposed technique using a simulated nonlinear time-varying system and recorded data from an industrial distillation column.

Developing a simple, rapid method for identifying and monitoring jellyfish aggregations from the air

Within the marine environment, aerial surveys have historically centred on apex predators, such as pinnipeds, cetaceans and sea birds. However, it is becoming increasingly apparent that the utility of this technique may also extend to subsurface species such as pre-spawning fish stocks and aggregations of jellyfish that occur close to the surface. In light of this, we tested the utility of aerial surveys to provide baseline data for 3 poorly understood scyphozoan jellyfish found throughout British and Irish waters: Rhizostoma octopus, Cyanea capillata and Chrysaora hysoscella. Our principal objectives were to develop a simple sampling protocol to identify and quantify surface aggregations, assess their consistency in space and time, and consider the overall applicability of this technique to the study of gelatinous zooplankton. This approach provided a general understanding of range and relative abundance for each target species, with greatest suitability to the study of R. octopus. For this species it was possible to identify and monitor extensive, temporally consistent and previously undocumented aggregations throughout the Irish Sea, an area spanning thousands of square kilometres. This finding has pronounced implications for ecologists and fisheries managers alike and, moreover, draws attention to the broad utility of aerial surveys for the study of gelatinous aggregations beyond the range of conventional ship-based techniques.

Time of flight mass spectrometry for quantitative data analysis in fast transient studies using a Temporal Analysis of Products (TAP) reactor

A Time of flight (ToF) mass spectrometer suitable in terms of sensitivity, detector response and time resolution, for application in fast transient Temporal Analysis of Products (TAP) kinetic catalyst characterization is reported. Technical difficulties associated with such application as well as the solutions implemented in terms of adaptations of the ToF apparatus are discussed. The performance of the ToF was validated and the full linearity of the specific detector over the full dynamic range was explored in order to ensure its applicability for the TAP application. The reported TAP-ToF setup is the first system that achieves the high level of sensitivity allowing monitoring of the full 0-200 AMU range simultaneously with sub-millisecond time resolution. In this new setup, the high sensitivity allows the use of low intensity pulses ensuring that transport through the reactor occurs in the Knudsen diffusion regime and that the data can, therefore, be fully analysed using the reported theoretical TAP models and data processing.

Limitations of instantaneous water quality sampling in surface-water catchments: Comparison with near-continuous phosphorus time-series data.

The validity of load estimates from intermittent, instantaneous grab sampling is dependent on adequate spatial coverage by monitoring networks and a sampling frequency that re?ects the variability in the system under study. Catchments with a ?ashy hydrology due to surface runoff pose a particular challenge as intense short duration rainfall events may account for a signi?cant portion of the total diffuse transfer of pollution from soil to water in any hydrological year. This can also be exacerbated by the presence of strong background pollution signals from point sources during low flows. In this paper, a range of sampling methodologies and load estimation techniques are applied to phosphorus data from such a surface water dominated river system, instrumented at three sub-catchments (ranging from 3 to 5 km2 in area) with near-continuous monitoring stations. Systematic and Monte Carlo approaches were applied to simulate grab sampling using multiple strategies and to calculate an estimated load, Le based on established load estimation methods. Comparison with the actual load, Lt, revealed signi?cant average underestimation, of up to 60%, and high variability for all feasible sampling approaches. Further analysis of the time series provides an insight into these observations; revealing peak frequencies and power-law scaling in the distributions of P concentration, discharge and load associated with surface runoff and background transfers. Results indicate that only near-continuous monitoring that re?ects the rapid temporal changes in these river systems is adequate for comparative monitoring and evaluation purposes. While the implications of this analysis may be more tenable to small scale ?ashy systems, this represents an appropriate scale in terms of evaluating catchment mitigation strategies such as agri-environmental policies for managing diffuse P transfers in complex landscapes.

Technical Note: Assessing a 24/7 solution for monitoring water quality loads in small river catchments

Quantifying nutrient and sediment loads in catchments is dif?cult owing to diffuse controls related to storm hydrology. Coarse sampling and interpolation methods are prone to very high uncertainties due to under-representation of high discharge, short duration events. Additionally, important low-?ow processes such as diurnal signals linked to point source impacts are missed. Here we demonstrate a solution based on a time-integrated approach to sampling with a standard 24 bottle autosampler con?gured to take a sample every 7 h over a week according to a Plynlimon design. This is evaluated with a number of other sampling strategies using a two-year dataset of sub-hourly discharge and phosphorus concentration data. The 24/7 solution is shown to be among the least uncertain in estimating load (inter-quartile range: 96% to 110% of actual load in year 1 and 97% to 104% in year 2) due to the increased frequency raising the probability of sampling storm events and point source signals. The 24/7 solution would appear to be most parsimonious in terms of data coverage and certainty, process signal representation, potential laboratory commitment, technology requirements and the ability to be widely deployed in complex catchments.

Developments in Performance Monitoring of Concrete Exposed to Extreme Environments

The performance of the surface zone of concrete is acknowledged as a major factor governing the rate of deterioration of reinforced concrete structures as it provides the only barrier to the ingress of water containing dissolved ionic species such as chlorides which, ultimately, initiate corrosion of the reinforcement. In-situ monitoring of cover-zone concrete is therefore critical in attempting to make realistic predictions as to the in-service performance of the structure. To this end, this paper presents developments in a remote interrogation system to allow continuous, real-time monitoring of the cover-zone concrete from an office setting. Use is made of a multi-electrode array embedded within cover-zone concrete to acquire discretized electrical resistivity and temperature measurements, with both parameters monitored spatially and temporally. On-site instrumentation, which allows remote interrogation of concrete samples placed at a marine exposure site, is detailed, together with data handling and processing procedures. Site-measurements highlight the influence of temperature on electrical resistivity and an Arrhenius-based temperature correction protocol is developed using on-site measurements to standardize resistivity data to a reference temperature; this is an advancement over the use of laboratory-based procedures. The testing methodology and interrogation system represents a robust, low-cost and high-value technique which could be deployed for intelligent monitoring of reinforced concrete structures.

Simultaneous, long-term monitoring of valve and cardiac activity in the blue mussel Mytilus edulis exposed to copper

Valve and cardiac activity were simultaneously measured in the blue mussel (Mytilus edulis) in response to 10 d copper exposure. Valve movements, heart rates and heart-rate variability were obtained non-invasively using a Musselmonitor(R) (valve activity) and a modified version of the Computer-Aided Physiological Monitoring system (CAPMON; cardiac activity). After 2 d exposure of mussels (4 individuals per treatment group) to a range of dissolved copper concentrations (0 to 12.5 mu M as CuCl2) median valve positions (% open) and median heart rates (beats per minute) declined as a function of copper concentration. Heart-rate variability (coefficient of variation for interpulse durations) rose in a concentration-dependent manner. The 48 h EC50 values (concentrations of copper causing 50% change) for valve positions, heart rates and heart-rate variability were 2.1, 0.8, and 0.06 mu M, respectively. Valve activity was weakly correlated with both heart rate (r = 0.48 +/- 0.02) and heart-rate variability (r = 0.32 +/- 0.06) for control individuals (0 mu M Cu2+). This resulted from a number of short enclosure events that did not coincide with a change in cardiac activity. Exposure of mussels to increasing copper concentrations (greater than or equal to 0.8 mu M) progressively reduced the correlation between valve activity and heart rates (r = 0 for individuals dosed with greater than or equal to 6.3 mu M Cu2+), while correlations between valve activity and heart-rate variability were unaffected. The poor correlations resulted from periods of valve flapping that were not mimicked by similar fluctuations in heart rate or heart-rate variability. The data suggest that the copper-induced bradycardia observed in mussels is not a consequence of prolonged valve closure.

Electrical Based Sensors and Remote Monitoring System for Assessing the Corrosion Related Activity in Concrete at Hangzhou Bay Bridge

Concrete structures in marine environments are subjected to cyclic wetting and drying, corrosion of reinforcement due to chloride ingress and biological deterioration. In order to assess the quality of concrete and predict the corrosion activity of reinforcing steel in concrete in this environment, it is essential to monitor the concrete continuously right from the construction phase to the end of service life of the structure. In this paper a novel combination of sensor techniques which are integrated in a sensor probe is used to monitor the quality of cover concrete and corrosion of the reinforcement. The integrated sensor probe was embedded in different concrete samples exposed to an aggressive marine environment at the Hangzhou Bay Bridge in China. The sensor probes were connected to a monitoring station, which enabled the access and control of the data remotely from Belfast, UK. The initial data obtained from the monitoring station reflected the early age properties of the concretes and distinct variations in these properties were observed with different concrete types.

Monitoring the moisture transport in building stones using fibre optic relative humidity sensors

Weathering of stone is one of the major reasons for the damage of stone masonry structures and it takes place due to interlinked chemical, physical and biological processes in stones. The key parameters involved in the deterioration processes are temperature, moisture and salt. It is now known that the sudden variations in temperature and moisture greatly accelerate the weathering process of the building stone fabric. Therefore, in order to monitor these sudden variations an effective and continuous monitoring system is needed. Furthermore, it must consist of robust sensors which are accurate and can survive in the harsh environments experienced in and around masonry structures. Although salt penetration is important for the rate of deterioration of stone masonry structures, the processes involved are much slower than the damage associated with temperature and moisture variations. Therefore, in this paper a novel fibre optic temperature cum relative humidity sensor is described and its applicability in monitoring building stones demonstrated. The performance of the sensor is assessed in an experiment comprising wetting and drying of limestone blocks. The results indicate that the novel fibre optic relative humidity sensor which is tailor made for applications in masonry structures performed well in wetting and drying tests, whilst commercial capacitance based sensors failed to recover during the drying regime for a long period after a wetting regime. That is, the fibre optic sensor has the capability to measure both sorption and de-sorption characteristics of stone blocks. This sensor is used in a test wall in Oxford and the data thus obtained strengthened the laboratory observations.

An orientation free adaptive step detection algorithm using a smart phone in physical activity monitoring

In this paper we present an Orientation Free Adaptive Step Detection (OFASD) algorithm for deployment in a smart phone for the purposes of physical activity monitoring. The OFASD algorithm detects individual steps and measures a user’s step counts using the smart phone’s in-built accelerometer. The algorithm considers both the variance of an individual’s walking pattern and the orientation of the smart phone. Experimental validation of the algorithm involved the collection of data from 10 participants using five phones (worn at five different body positions) whilst walking on a treadmill at a controlled speed for periods of 5 min. Results indicated that, for steps detected by the OFASD algorithm, there were no significant differences between where the phones were placed on the body (p > 0.05). The mean step detection accuracies ranged from 93.4 % to 96.4 %. Compared to measurements acquired using existing dedicated commercial devices, the results demonstrated that using a smart phone for monitoring physical activity is promising, as it adds value to an accepted everyday accessory, whilst imposing minimum interaction from the user. The algorithm can be used as the underlying component within an application deployed within a smart phone designed to promote self-management of chronic disease where activity measurement is a significant factor, as it provides a practical solution, with minimal requirements for user intervention and less constraints than current solutions.