Towards the development of a portable device for the monitoring of gaseous toxic industrial chemicals based on a chemical sensor array

The ability of chemical sensor array (CSA) technology to identify multiple gaseous analytes and differentiate between various analyte concentrations has been documented. To date, CSA response was monitored using a flatbed scanner driven by a personal computer. While this system is suitable for use in a laboratory setting it is not suitable for use in the field for environmental monitoring. We describe herein progress made towards the development of a rapid, inexpensive, portable, battery-operated, handheld device based on CSA technology for the detection of toxic industrial compounds (TICs). This prototype successfully differentiates between four TICs at both permissible exposure limit (PEL) and immediately dangerous to life and health (IDLH) concentrations, and three interferent gases, in less than 2 min.     

An evaluation of remote sensing techniques for enhanced detection of the toxic dinoflagellate, Karenia brevis

Optical techniques were investigated to enhance current bloom detection capabilities in support of an operational system for forecasting harmful Karenia brevis blooms along the west coast of Florida, within the Gulf of Mexico. Algorithms pertaining to backscatter and changes in spectral shape of remote-sensing reflectance were applied to SeaWiFS and MODIS imagery during known K. brevis and non-K. brevis events. A method to remove resuspended chlorophyll in Texas showed limited use when applied to several scenes following tropical storms off the west Florida coast. This analysis suggests that an ensemble image approach, wherein a combination of a chlorophyll anomaly, spectral shape at 490 nm and a backscatter ratio product would provide an improvement in satellite detection of K. brevis blooms. For southwest Florida, the combination of these methods through an ensemble approach may lead to an increase in user accuracy by 30-50%, as a result of correctly identifying non-K. brevis features. Where available, MODIS FLH scenes were analyzed to determine their use in K. brevis detection. However, insufficient imagery was available to make a fair assessment. Similar approaches could be applied to bloom tracking and monitoring in other regions.     

Synthesis of ground and remote sensing data for monitoring ecosystem functions in the Colorado River Delta, Mexico

The delta of the Colorado River in Mexico supports a rich mix of estuarine, wetland and riparian ecosystems that provide habitat for over 350 species of birds as well as fish, marine mammals, and other wildlife. An important part of the delta ecosystem is the riparian corridor, which is supported by agricultural return flows and waste spills of water originating in the U.S. and Mexico. These flows may be curtailed in the future due to climate change and changing land use practices (out-of-basin water transfers, increased agricultural efficiency, and more optimal management of dams) in the U.S. and Mexico, and resource managers need to monitor the effects of their water management practices on these ecosystems. We developed ground-validated, remote sensing methods to monitor the vegetation status, habitat value, and water use of wetland and riparian ecosystems using multi-temporal, multi-resolution images. The integrated methodology allowed us to project species composition, leaf area index, fractional cover, habitat value, and evapotranspiration over seasons and years throughout the delta, in response to variable water flows from the U.S. to Mexico. Waste spills of water from the U.S. have regenerated native cottonwood and willow trees in the riparian corridor and created backwater and marsh areas that support birds and other wildlife. However, the main source of water supporting the riparian vegetation is the regional aquifer recharged by underflow from U.S. and Mexico irrigation districts. Native trees have a short half-life in the riparian zone due to human-set fires and harvesting for timber. Active management, monitoring, and restoration programs are needed to maintain the habitat value of this ecosystem for the future.     

Electrochemical studies on the performance characteristics of alkaline solid embeddable sensor for concrete environments

In this study, alkaline solid embeddable MnO₂ is used as a reference sensor for concrete environments. The performance characteristics are evaluated in a saturated calcium hydroxide solution, a synthetic concrete pore solution and ordinary Portland cement (OPC) extracts which correspond to the concrete environments. The electrochemical stability of the MnO₂ electrode is studied in the said concrete environments. The uniformity of the MnO₂ sensor is tested in concrete environments. The reversibility of MnO₂ sensor in three alkaline solutions is within ±10 mV, which is very well within the limit as sensor for concrete. The polarization behaviour of MnO₂ electrode in concrete environments is carried out potentiodynamically and impedance behaviour showed the stability of sensor. All the studies revealed that MnO₂ as a suitable sensor electrode for concrete structures.     

Linking the growth of filamentous algae to the 3D-ecohydrodynamic model of the Gulf of Finland

One of the most visible symptoms of eutrophication in the Gulf of Finland is blooms of unattached filamentous algae. This decomposing algal biomass causes serious nuisance problems for recreational uses of the coastal zone, particularly when cast ashore. The nutrient availability for these macroscopic filamentous algae is regulated by a superior competitor, the phytoplankton. Nutrients are left for the weaker competitor only when the conditions are not suitable for the growth of phytoplankton. This happens during vertical mixing of the water column. The lack of stratification prevents the formation of phytoplankton blooms, but does not limit the growth of filamentous algae when still growing attached to the bottom. A simple growth model was developed to describe the growth and biomass of filamentous algae. In the absence of suitable nutrient measurements, the model was linked to a 3D-ecohydrodynamic model which generated the nutrient input data. The model was calibrated with three-year monitoring data of filamentous algal biomass at one location. Validation was carried out with one-year monitoring data from an adjacent location. The model was able to describe the number of biomass peaks and their timing with good accuracy. After further development, the filamentous algal model will be used as one of the management tools for the evaluation of the sustainable nutrient load to the Gulf of Finland.     

Improvement of the NOx selectivity for a planar YSZ sensor

In recent years planar yttria-stabilized zirconia (YSZ) based electrochemical gas sensors for automotive exhaust applications have become a major source of interest. The present work aims to develop a sensor for industrialisation. For this reason planar YSZ-based electrochemical sensors using two metallic electrodes (platinum and gold) were fabricated using screen-printing technology and tested in a laboratory test bench for different concentrations of pollutant gas such as CO, NO, NO₂ and hydrocarbons in oxygen rich atmosphere. It was furthermore shown that the selectivity towards NO_x could be highly reinforced by deposing a catalytic filter consisting of 1.7-4.5 wt.% Pt dispersed on alumina directly on the sensing elements. This filter was characterized by the use of SEM, TPD and XRD.     

Electrochemical genosensor based on modified octadecanethiol self-assembled monolayer for Escherichia coli detection

An electrochemical genosensor based on 1-fluoro-2-nitro-4-azidobenzene (FNAB) modified octadecanethiol (ODT) self-assembled monolayer (SAM) has been fabricated for Escherichia coli detection. The results of electrochemical response measurements investigated using methylene blue (MB) as a redox indicator reveal that this nucleic acid sensor has 60 s of response time, high sensitivity (0.5 × 10⁻¹⁸ M) and linearity as 0.5 × 10⁻¹⁸-1 × 10⁻⁶ M. The sensor has been found to be stable for about four months and can be used about ten times. It is shown that water borne pathogens like Klebsiella pneumonia, Salmonella typhimurium and other gram-negative bacterial samples has no significant effects in the response of this sensor.     

The effect of La2CuO4 sensing electrode thickness on a potentiometric NOx sensor response

In order to further understand the different contributions to NO_x sensing mechanism as well as the importance of electrode geometry, solid state potentiometric sensors with varying La₂CuO₄ sensing electrode thicknesses were studied. These sensors (with a Pt counter electrode) showed a dependence of NO₂ sensitivity which decreased with increasing thickness in the temperature range of 550-650 °C. They also showed NO sensitivity that was independent of thickness at 400 °C and 600 °C, but varied at temperatures between. This behavior was attributed to multiple mechanistic contributions explained by Differential Electrode Equilibria.     

Tethered DNA scaffolds on optical sensor platforms for detection of hipO gene from Campylobacter jejuni

DNA biosensors have gained increased attention over traditional diagnostic methods due to their fast and responsive operation and cost-effective design. The specificity of DNA biosensors relies on single-stranded oligonucleotide probes immobilized to a transduction platform. Here, we report the development of biosensors to detect the hippuricase gene (hipO) from Campylobacter jejuni using direct covalent coupling of thiol- and biotin-labeled single-stranded DNA (ssDNA) on both surface plasmon resonance (SPR) and diffraction optics technology (DOT, dotLab) transduction platforms. This is the first known report of the dotLab to detect targeted DNA. Application of 6-mercapto-1-hexanol as a spacer thiol for SPR gold surface created a self-assembled monolayer that removed unbound ssDNA and minimized non-specific detection. The detection limit of SPR sensors was shown to be 2.5 nM DNA while dotLab sensors demonstrated a slightly decreased detection limit of 5.0 nM (0.005 μM). It was possible to reuse the SPR sensor due to the negligible changes in sensor sensitivity (∼9.7 × 10⁻⁷ ΔRU) and minimal damage to immobilized probes following use, whereas dotLab sensors could not be reused. Results indicated feasibility of optical biosensors for rapid and sensitive detection of the hipO gene of Campylobacter jejuni using specific ssDNA as a probe.     

Continuum removed band depth analysis for detecting the effects of natural gas, methane and ethane on maize reflectance

It is known that natural gas in the soil affects vegetation health, which may be detected through analysis of reflectance spectra. Since natural gas is invisible, changes in the vegetation could potentially indicate gas leakage. Although it is known that gas in soil affects plant reflectance, the relationship between natural gas and the development and reflectance properties of plants has not been studied. The objective of this study was to test whether natural gas and its two main components, methane and ethane, affect vegetation reflectance in the chlorophyll and water absorption regions. An experiment was carried out in which maize (Zea mays) plants were grown in pots that were flushed with 10 l of gas per day for 39 ±4 days. Leaf reflectance was measured once a week with a spectrophotometer. The reflectance was analysed using continuum removal of the blue (400-550 nm), red (550-750 nm) and two water absorption features (1370-1570 nm and 1870-2170 nm), after which the band depths and normalized band depths were analyzed for each treatment. The band depth analysis showed that ethane caused an initial increase of 10% in reflectance between 560 and 590 nm, followed by a decrease during the course of the experiment. Normalized band depth analysis showed that ethane caused a reflectance shift of 1 to 5 nm towards longer wavelengths compared to the control reflectance in the visible region. All gases caused an increase in reflectance in the water absorption bands. The physiological reflectance index, PRI, which has previously linked water stress to photosynthetic activity, suggested that the hydrocarbon gases (particularly ethane) decreased the photosynthetic activity of the plants.The combination of reduced band depths in the chlorophyll and water absorption regions and the increased PRI suggests that ethane gas in the soil hampered a normal water uptake by maize plants in an early stage of their growth. Although further research is necessary to upscale the results from the laboratory to the field, the increased reflectance in the 560-590 nm region caused by ethane together with the increased PRI are promising indicators for gas leakage.     

Remote sensing chlorophyll a of optically complex waters (rias Baixas, NW Spain): Application of a regionally specific chlorophyll a algorithm for MERIS full resolution data during an upwelling cycle

This study takes advantage of a regionally specific algorithm and the characteristics of Medium Resolution Imaging Spectrometer (MERIS) in order to deliver more accurate, detailed chlorophyll a (chla) maps of optically complex coastal waters during an upwelling cycle. MERIS full resolution chla concentrations and in situ data were obtained on the Galician (NW Spain) shelf and in three adjacent rias (embayments), sites of extensive mussel culture that experience frequent harmful algal events. Regionally focused algorithms (Regional neural network for rias Baixas or NNRB) for the retrieval of chla in the Galician rias optically complex waters were tested in comparison to sea-truth data. The one that showed the best performance was applied to a series of six MERIS (FR) images during a summer upwelling cycle to test its performance. The best performance parameters were given for the NN trained with high-quality data using the most abundant cluster found in the rias after the application of fuzzy c-mean clustering techniques (FCM). July 2008 was characterized by three periods of different meteorological and oceanographic states. The main changes in chla concentration and distribution were clearly captured in the images. After a period of strong upwelling favorable winds a high biomass algal event was recorded in the study area. However, MERIS missed the high chlorophyll upwelled water that was detected below surface in the ria de Vigo by the chla profiles, proving the necessity of in situ observations. Relatively high biomass “patches” were mapped in detail inside the rias. There was a significant variation in the timing and the extent of the maximum chla areas. The maps confirmed that the complex spatial structure of the phytoplankton distribution in the rias Baixas is affected by the surface currents and winds on the adjacent continental shelf. This study showed that a regionally specific algorithm for an ocean color sensor with the characteristics of MERIS in combination with in situ data can be of great help in chla monitoring, detection and study of high biomass algal events in an area affected by coastal upwelling such as the rias Baixas.     

Effect of La2CuO4 electrode area on potentiometric NOx sensor response and its implications on sensing mechanism

The intent of this work is to look at the effects of varying the La₂CuO₄ electrode area and the asymmetry between the sensing and counter electrode in a solid state potentiometric sensor with respect to NO_x sensitivity. NO₂ sensitivity was observed at 500-600 °C with a maximum sensitivity of ∼22 mV/decade [NO₂] observed at 500 °C for the sensor with a La₂CuO₄ electrode area of ∼30 mm². The relationship between NO₂ sensitivity and area is nearly parabolic at 500 °C, decreases linearly with increasing electrode area at 600 °C, and was a mixture of parabolic and linear behavior 550 °C. NO sensitivity varied non-linearly with electrode area with a minima (maximum sensitivity) of ∼−22 mV/decade [NO] at 450 °C for the sensor with a La₂CuO₄ electrode area of 16 mm². The behavior at 400 °C was similar to that of 450 °C, but with smaller sensitivities due to a saturation effect. At 500 °C, NO sensitivity decreases linearly with area.We also used electrochemical impedance spectroscopy (EIS) to investigate the electrochemical processes that are affected when the sensing electrode area is changed. Changes in impedance with exposure to NO_x were attributed to either changes in La₂CuO₄ conductivity due to gas adsorption (high frequency impedance) or electrocatalysis occurring at the electrode/electrolyte interface (total electrode impedance). NO₂ caused a decrease in high frequency impedance while NO caused an increase. In contrast, NO₂ and NO both caused a decrease in the total electrode impedance. The effect of area on both the potentiometric and impedance responses show relationships that can be explained through the mechanistic contributions included in differential electrode equilibria.     

Neural network estimation of chlorophyll a from MERIS full resolution data for the coastal waters of Galician rias (NW Spain)

In typical Case 2 waters, accurate remote sensing retrieval of chlorophyll a (chla) is still a challenging task. In this study, focusing on the Galician rias (ΝW Spain), algorithms based on neural network (NN) techniques were developed for the retrieval of chla concentration in optically complex waters, using Medium Resolution Imaging Spectrometer (MERIS) data. There is considerable interest in the accurate estimation of chla for the Galician rias, because of the economic and social importance of the extensive culture of mussels, and the high frequency of harmful algal events. Fifteen MERIS full resolution (FR) cloud-free images paired with in situ chla data (for 2002-2004 and 2006-2008) were used for the development and validation of the NN. The scope of NN was established from the clusters obtained using fuzzy c-mean (FCM) clustering techniques applied to the satellite-derived data. Three different NNs were developed: one including the whole data set, and two others using only points belonging to one of the clusters. The input data for these latter two NNs was chosen depending on the quality level, defined on the basis of quality flags given to each data set. The fitting results were fairly good and proved the capability of the tool to predict chla concentrations in the study area. The best prediction was given for the NN trained with high-quality data using the most abundant cluster data set. The performance parameters in the validation set of this NN were R² = 0.86, mean percentage error (MPE) = − 0.14, root mean square error (RMSE) = 0.75 mg m^− 3, and relative RMSE = 66%. The NN developed in this study detected accurately the peaks of chla, in both training and validation sets. The performance of the Case-2-Regional (C2R) algorithm, routinely used for MERIS data, was also tested and compared with our best performing NN and the sea-truthing data. Results showed that this NN outperformed the C2R, giving much higher R² and lower RMSE values.This study showed that the combination of in situ data and NN technology improved the retrieval of chla in Case 2 waters, and could be used to obtain more accurate chla maps. A local-based algorithm for the chla retrieval from an ocean colour sensor with the characteristics of MERIS would be a great support in the quantitative monitoring and study of harmful algal events in the coastal waters of the Rias Baixas. The limitations and possible improvements of the developed chla algorithms are also discussed.     

Estimation of cyanobacterial pigments in a freshwater lake using OCM satellite data

Cyanobacteria represent a major harmful algal group in fresh to brackish water environments. Lac des Allemands, a freshwater lake of 49 km² southwest of New Orleans, Louisiana on the upper end of the Barataria Estuary, provides a natural laboratory for remote characterization of cyanobacterial blooms because of their seasonal occurrence. The Oceansat-1 satellite Ocean Colour Monitor (OCM) provides measurements similar to SeaWiFS but with higher spatial resolution, and this work is the first attempt to use OCM measurements to quantify cyanobacterial pigments. The satellite signal was first vicariously calibrated using SeaWiFS as a reference, and then corrected to remove the atmospheric effects using a customized atmospheric correction procedure. Then, empirical inversion algorithms were developed to convert the OCM remote sensing reflectance (R_rs) at bands 4 and 5 (centered at 510.6 and 556.4 nm, respectively) to concentrations of phycocyanin (PC), the primary cyanobacterial pigment. A holistic approach was used to minimize the influence of other optically active constituents on the PC algorithm. Similarly, empirical algorithms to estimate chlorophyll a (Chl a) concentrations were developed using OCM bands 5 and 6 (centered at 556.4 and 669 nm, respectively). The best PC algorithm (R² = 0.7450, p < 0.0001, n = 72) yielded a root mean square error (RMSE) of 36.92 μg/L with a relative RMSE of 10.27% (PC from 2.75 to 363.50 μg/L, n = 48). The best algorithm for Chl a (R² = 0.7510, p < 0.0001, n = 72) produced an RMSE of 31.19 μg/L with a relative RMSE of 16.56% (Chl a from 9.46 to 212.76 μg/L, n = 48). While more field data are required to further validate the long-term performance of these algorithms, currently they represent the best protocol for establishing a long time-series of cyanobacterial blooms in the Lac des Allemands using OCM data.     

On employing fuzzy modeling algorithms for the valuation of residential premises

In this paper, we investigate fuzzy modeling techniques for predicting the prices of residential premises, based on some main drivers such as usable area of premises, age of a building, number of rooms in a flat, floor on which a flat is located, number of storeys in a building as well as the distance from the city center. Our proposed modeling techniques rely on two aspects: the first one (called SparseFIS) is a batch off-line modeling method and tries to out-sparse an initial dense rule population by optimizing the rule weights within an iterative optimization procedure subject to constrain the number of important rules; the second one (called FLEXFIS) is a single-pass incremental method which is able to build up fuzzy models in an on-line sample-wise learning context. As such, it is able to adapt former generated prediction models with new data recordings on demand and also to cope with on-line data streams. The final obtained fuzzy models provide some interpretable insight into the relations between the various features and residential prices in form of linguistically readable rules (IF-THEN conditions). Both methods will be compared with a state-of-the-art premise estimation method usually conducted by many experts and exploiting heuristic concepts such as sliding time window, nearest neighbors and averaging. The comparison is based on a two real-world data set including prices for residential premises within the years 1998-2008.     

Linking operational semantics and algebraic semantics for a probabilistic timed shared-variable language

Complex software systems typically involve features like time, concurrency and probability, with probabilistic computations playing an increasing role. However, it is currently challenging to formalize languages incorporating all those features. Recently, the language PTSC has been proposed to integrate probability and time with shared-variable concurrency (Zhu et al. (2006, 2009) [51] and [53]), where the operational semantics has been explored and a set of algebraic laws has been investigated via bisimulation. This paper investigates the link between the operational and algebraic semantics of PTSC, highlighting both its theoretical and practical aspects.The link is obtained by deriving the operational semantics from the algebraic semantics, an approach that may be understood as establishing soundness of the operational semantics with respect to the algebraic semantics. Algebraic laws are provided that suffice to convert any PTSC program into a form consisting of a guarded choice or an internal choice between programs, which are initially deterministic. That form corresponds to a simple execution of the program, so it is used as a basis for an operational semantics. In that way, the operational semantics is derived from the algebraic semantics, with transition rules resulting from the derivation strategy. In fact the derived transition rules and the derivation strategy are shown to be equivalent, which may be understood as establishing completeness of the operational semantics with respect to the algebraic semantics.That theoretical approach to the link is complemented by a practical one, which animates the link using Prolog. The link between the two semantics proceeds via head normal form. Firstly, the generation of head normal form is explored, in particular animating the expansion laws for probabilistic interleaving. Then the derivation of the operational semantics is animated using a strategy that exploits head normal form. The operational semantics is also animated. These animations, which again supports to claim soundness and completeness of the operational semantics with respect to the algebraic, are interesting because they provide a practical demonstration of the theoretical results.     

Anti-windup compensation for systems with sensor saturation: a study of architecture and structure

This article proposes a linear dynamic anti-windup strategy for the alleviation of performance and stability problems in systems which are linear apart from saturating sensors. Unlike anti-windup compensation for systems subject to actuator saturation, there is no agreed architecture for applying anti-windup to systems with sensor saturation and therefore attention is devoted to the discussion of various candidate configurations which can be interpreted as a particular choice of a static non-linear map. The main results of the article give existence conditions for compensators which yield global exponential stability and finite ?₂ gain of the overall non-linear closed-loop system. The existence conditions are different to those which have appeared hitherto in the literature.     

Milne, a routine for the numerical solution of Milne's problem

The routine Milne provides accurate numerical values for the classical Milne's problem of neutron transport for the planar one speed and isotropic scattering case. The solution is based on the Case eigen-function formalism. The relevant X functions are evaluated accurately by the Double Exponential quadrature. The calculated quantities are the extrapolation distance and the scalar and the angular fluxes. Also, the H function needed in astrophysical calculations is evaluated as a byproduct.

Program summary

Program title: MilneCatalogue identifier: AEGS_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGS_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 701No. of bytes in distributed program, including test data, etc.: 6845Distribution format: tar.gzProgramming language: Fortran 77Computer: PC under Linux or WindowsOperating system: Ubuntu 8.04 (Kernel version 2.6.24-16-generic), Windows-XPClassification: 4.11, 21.1, 21.2Nature of problem: The X functions are integral expressions. The convergence of these regular and Cauchy Principal Value integrals are impaired by the singularities of the integrand in the complex plane. The DE quadrature scheme tackles these singularities in a robust manner compared to the standard Gauss quadrature.Running time: The test included in the distribution takes a few seconds to run.     

On a family of multivariate copulas for aggregation processes

We introduce a family of multivariate copulas - a special type of n-ary aggregation operations - depending on a univariate function. This family is used in the construction of a special aggregation operation that satisfies a Lipschitz condition. Several examples are provided and some statistical properties are studied.     

In2O3 + xBaO (x = 0.5-5 at.%) - A novel material for trace level detection of NOx in the ambient

Indium oxide (In₂O₃) doped with 0.5-5 at.% of Ba was examined for their response towards trace levels of NO_x in the ambient. Crystallographic phase studies, electrical conductivity and sensor studies for NO_x with cross interference for hydrogen, petroleum gas (PG) and ammonia were carried out. Bulk compositions with x ≤ 1 at.% of Ba exhibited high response towards NO_x with extremely low cross interference for hydrogen, PG and ammonia, offering high selectivity. Thin films of 0.5 at.% Ba doped In₂O₃ were deposited using pulsed laser deposition technique using an excimer laser (KrF) operating at a wavelength of (λ) 248 nm with a fluence of ∼3 J/cm² and pulsed at 10 Hz. Thin film sensors exhibited better response towards 3 ppm NO_x quite reliably and reproducibly and offer the potential to develop NO_x sensors (Threshold limit value of NO₂ and NO is 3 and 25 ppm, respectively).