Microcystin-LR detection in water by the Fabry–Pérot interferometer using an optical fibre coated with a sol–gel imprinted sensing membrane

Cyanobacteria deteriorate the water quality and are responsible for emerging outbreaks and epidemics causing harmful diseases in Humans and animals because of their toxins. Microcystin-LR (MCT) is one of the most relevant cyanotoxin, being the most widely studied hepatotoxin. For safety purposes, the World Health Organization recommends a maximum value of 1 μg L−1 of MCT in drinking water. Therefore, there is a great demand for remote and real-time sensing techniques to detect and quantify MCT. In this work a Fabry–Pérot sensing probe based on an optical fibre tip coated with a MCT selective thin film is presented. The membranes were developed by imprinting MCT in a sol–gel matrix that was applied over the tip of the fibre by dip coating. The imprinting effect was obtained by curing the sol–gel membrane, prepared with (3-aminopropyl) trimethoxysilane (APTMS), diphenyl-dimethoxysilane (DPDMS), tetraethoxysilane (TEOS), in the presence of MCT. The imprinting effect was tested by preparing a similar membrane without template. In general, the fibre Fabry–Pérot with a Molecular Imprinted Polymer (MIP) sensor showed low thermal effect, thus avoiding the need of temperature control in field applications. It presented a linear response to MCT concentration within 0.3–1.4 μg L−1 with a sensitivity of −12.4 ± 0.7 nm L μg−1. The corresponding Non-Imprinted Polymer (NIP) displayed linear behaviour for the same MCT concentration range, but with much less sensitivity, of −5.9 ± 0.2 nm L μg−1. The method shows excellent selectivity for MCT against other species co-existing with the analyte in environmental waters. It was successfully applied to the determination of MCT in contaminated samples. The main advantages of the proposed optical sensor include high sensitivity and specificity, low-cost, robustness, easy preparation and preservation.

Novel potentiometric sensors of molecular imprinted polymers for specific binding of chlormequat

Molecularly imprinted polymers (MIP) were used as potentiometric sensors for the selective recognition and determination of chlormequat (CMQ). They were produced after radical polymerization of 4-vinyl pyridine (4-VP) or methacrylic acid (MAA) monomers in the presence of a cross-linker. CMQwas used as template. Similar nonimprinted (NI) polymers (NIP) were produced by removing the template from reaction media. The effect of kind and amount of MIP or NIP sensors on the potentiometric behavior was investigated. Main analytical features were evaluated in steady and flow modes of operation. The sensor MIP/4-VP exhibited the best performance, presenting fast near-Nernstian response for CMQover the concentration range 6.2×10-6 – 1.0×10-2 mol L-1 with detection limits of 4.1×10-6 mol L-1. The sensor was independent from the pH of test solutions in the range 5 – 10. Potentiometric selectivity coefficients of the proposed sensors were evaluated over several inorganic and organic cations. Results pointed out a good selectivity to CMQ. The sensor was applied to the potentiometric determination of CMQin commercial phytopharmaceuticals and spiked water samples. Recoveries ranged 96 to 108.5%.

Molecularly-imprinted materials for potentiometric transduction: application to the antibiotic enrofloxacin

Enrofloxacin (ENR) is an antimicrobial used both in humans and in food producing species. Its control is required in farmed species and their surroundings in order to reduce the prevalence of antibiotic resistant bacteria. Thus, a new biomimetic sensor enrofloxacin is presented. An artificial host was imprinted in specific polymers. These were dispersed in 2-nitrophenyloctyl ether and entrapped in a poly(vinyl chloride) matrix. The potentiometric sensors exhibited a near-Nernstian response. Slopes expressing mVΔlog([ENR]/M) varied within 48–63. The detection limits ranged from 0.28 to 1.01 µg mL 1. Sensors were independent from the pH of test solutions within 4–7. Good selectivity was observed toward potassium, calcium, barium, magnesium, glycine, ascorbic acid, creatinine, norfloxacin, ciprofloxacin, and tetracycline. In flowing media, the biomimetic sensors presented good reproducibility (RSD of ±0.7%), fast response, good sensitivity (47 mV/Dlog([ENR]/ M), wide linear range (1.0×10-5–1.0×10-3 M), low detection limit (0.9 µg mL-1), and a stable baseline for a 5×10-2 M acetate buffer (pH 4.7) carrier. The sensors were used to analyze fish samples. The method offered the advantages of simplicity, accuracy, and automation feasibility. The sensing membrane may contribute to the development of small devices allowing in vivo measurements of enrofloxacin or parent-drugs.

Trimethoprim-selective electrodes with molecularly imprinted polymers acting as ionophores and potentiometric transduction on graphite solid-contact

This work proposes a new biomimetic sensor material for trimethoprim. It is prepared by means of radical polymerization, having trimethylolpropane trimethacrylate as cross-linker, benzoyl peroxide as radicalar iniciator, chloroform as porogenic solvent, and methacrylic acid and 2-vinyl pyridine as monomers. Different percentages of sensor in a range between 1 and 6% were studied. Their behavior was compared to that obtained with ion-exchanger quaternary ammonium salt (additive tetrakis(p-chlorophenyl)borate or tetraphenylborate). The effect of an anionic additive in the sensing membrane was also tested. Trimethoprim sensors with 1% of imprinted particles from methacrylic acid monomers showed the best response in terms of slope (59.7 mV/decade) and detection limit (4.01×10−7 mol/L). These electrodes displayed also a good selectivity towards nickel, manganese aluminium, ammonium, lead, potassium, sodium, iron, chromium, sulfadiazine, alanine, cysteine, tryptophan, valine and glycine. The sensors were not affected by pH changes from 2 to 6. They were successfully applied to the analysis of water from aquaculture.

New molecularly-imprinted polymer for carnitine and its application as ionophore in potentiometric selective membranes

Carnitine (CRT) is a biological metabolite found in urine that contributes in assessingseveral disease conditions, including cancer. Novel quick screening procedures for CRT are therefore fundamental. This work proposes a novel potentiometric device where molecularly imprinted polymers (MIPs) were used as ionophores. The host-tailored sites were imprinted on a polymeric network assembled by radical polymerization of methacrylic acid (MAA) and trimethylpropane trimethacrylate (TRIM). Non-imprinted polymers (NIPs) were produced as control by removing the template from the reaction media. The selective membrane was prepared by dispersing MIP or NIP particles in plasticizer and poly(vinyl chloride), PVC, and casting this mixture over a solid contact support made of graphite. The composition of the selective membrane was investigated with regard to kind/amount of sensory material (MIP or NIP), and the need for a lipophilic additive. Overall, MIP sensors with additive exhibited the best performance, with near-Nernstian response down to ~ 1 × 10− 4 mol L− 1, at pH 5, and a detection limitof ~ 8 × 10− 5 mol L− 1. Suitable selectivity was found for all membranes, assessed by the matched potential method against some of the most common species in urine (urea, sodium, creatinine, sulfate, fructose and hemoglobin). CRT selective membranes including MIP materials were applied successfully to the potentiometric determination of CRT in urine samples.

Label-free Detection of Microcystin-LR in Waters Using Real-Time Potentiometric Biosensors Based on Single-Walled Carbon Nanotubes Imprinted Polymers

Microcystin-LR (MC-LR) is a dangerous toxin found in environmental waters, quantified by high performance liquid chromatography and/or enzyme-linked immunosorbent assays. Quick, low cost and on-site analysis is thus required to ensure human safety and wide screening programs. This work proposes label-free potentiometric sensors made of solid-contact electrodes coated with a surface imprinted polymer on the surface of Multi-Walled Carbon NanoTubes (CNTs) incorporated in a polyvinyl chloride membrane. The imprinting effect was checked by using non-imprinted materials. The MC-LR sensitive sensors were evaluated, characterized and applied successfully in spiked environmental waters. The presented method offered the advantages of low cost, portability, easy operation and suitability for adaptation to flow methods.

Determination of Microcystin-LR in waters in the subnanomolar range by sol–gel imprinted polymers on solid contact electrodes

The present work reports new sensors for the direct determination of Microcystin-LR (MC-LR) in environmental waters. Both selective membrane and solid contact were optimized to ensure suitable analytical features in potentiometric transduction. The sensing layer consisted of Imprinted Sol–Gel (ISG) materials capable of establishing surface interactions with MC-LR. Non-Imprinted Sol–Gel (NISG) membranes were used as negative control. The effects of an ionic lipophilic additive, time of sol–gel polymerization, time of extraction of MC-LR from the sensitive layer, and pH were also studied. The solid contact was made of carbon, aluminium, titanium, copper or nickel/chromium alloys (80 : 20 or 90 : 10). The best ISG sensor had a carbon solid contact and displayed average slopes of 211.3 mV per decade, with detection limits of 7.3 1010 M, corresponding to 0.75 mg L1 . It showed linear responses in the range of 7.7 1010 to 1.9 109 M of MC-LR (corresponding to 0.77–2.00 mg L1 ), thus including the limiting value for MC-LR in waters (1.0 mg L1 ). The potentiometric-selectivity coefficients were assessed by the matched potential method for ionic species regularly found in waters up to their limiting levels. Chloride (Cl) showed limited interference while aluminium (Al3+), ammonium (NH4 + ), magnesium (Mg2+), manganese (Mn2+), sodium (Na+ ), and sulfate (SO4 2) were unable to cause the required potential change. Spiked solutions were tested with the proposed sensor. The relative errors and standard deviation obtained confirmed the accuracy and precision of the method. It also offered the advantages of low cost, portability, easy operation and suitability for adaptation to flow methods.

Molecularly-Imprinted Materials for Potentiometric Transduction: Application to the Antibiotic Enrofloxacin

Enrofloxacin (ENR) is an antimicrobial used both in humans and in food producing species. Its control is required in farmed species and their surroundings in order to reduce the prevalence of antibiotic resistant bacteria. Thus, a new biomimetic sensor enrofloxacin is presented. An artificial host was imprinted in specific polymers. These were dispersed in 2-nitrophenyloctyl ether and entrapped in a poly(vinyl chloride) matrix. The potentiometric sensors exhibited a near-Nernstian response. Slopes expressing mV/Δlog([ENR]/M) varied within 48–63. The detection limits ranged from 0.28 to 1.01 µg mL−1. Sensors were independent from the pH of test solutions within 4–7. Good selectivity was observed toward potassium, calcium, barium, magnesium, glycine, ascorbic acid, creatinine, norfloxacin, ciprofloxacin, and tetracycline. In flowing media, the biomimetic sensors presented good reproducibility (RSD of ± 0.7%), fast response, good sensitivity (47 mV/Δlog([ENR]/M), wide linear range (1.0 × 10−5–1.0 × 10−3 M), low detection limit (0.9 µg mL−1), and a stable baseline for a 5 × 10−2 M acetate buffer (pH 4.7) carrier. The sensors were used to analyze fish samples. The method offered the advantages of simplicity, accuracy, and automation feasibility. The sensing membrane may contribute to the development of small devices allowing in vivo measurements of enrofloxacin or parent-drugs.

Trimethoprim-selective electrodes with molecularly imprinted polymers acting as ionophores and potentiometric transduction on graphite solid-contact

This work proposes a new biomimetic sensor material for trimethoprim. It is prepared by means of radical polymerization, having trimethylolpropane trimethacrylate as cross-linker, benzoyl peroxide as radicalar iniciator, chloroform as porogenic solvent, and methacrylic acid and 2-vinyl pyridine as monomers. Different percentages of sensor in a range between 1 and 6% were studied. Their behavior was compared to that obtained with ion-exchanger quaternary ammonium salt (additive tetrakis(p-chlorophenyl)borate or tetraphenylborate). The effect of an anionic additive in the sensing membrane was also tested. Trimethoprim sensors with 1% of imprinted particles from methacrylic acid monomers showed the best response in terms of slope (59.7 mV/decade) and detection limit (4.01 × 10− 7 mol/L). These electrodes displayed also a good selectivity towards nickel, manganese aluminium, ammonium, lead, potassium, sodium, iron, chromium, sulfadiazine, alanine, cysteine, tryptophan, valine and glycine. The sensors were not affected by pH changes from 2 to 6. They were successfully applied to the analysis of water from aquaculture.

Biomimetic Sensor Potentiometric System for Doxycycline Antibiotic Using a Molecularly Imprinted Polymer as an Artificial Recognition Element

Molecular imprinting is a useful technique for the preparation of functional materials with molecular recognition properties. A Biomimetic Sensor Potentiometric System was developed for assessment of doxycycline (DOX) antibiotic. The molecularly imprinted polymer (MIP) was synthesized by using doxycycline as a template molecule, methacrylic acid (MAA) and/or acrylamide (AA) as a functional monomer and ethylene glycol dimethacrylat (EGDMA) as a cross-linking agent. The sensing elements were fabricated by the inclusion of DOX imprinted polymers in polyvinyl chloride (PVC) matrix. The sensors showed a high selectivity and a sensitive response to the template in aqueous system. Electrochemical evaluation of these sensors under static (batch) mode of operation reveals near-Nernstian response. MIP/MAA membrane sensor was incorporated in flow-through cells and used as detectors for flow injection analysis (FIA) of DOX. The method has the requisite accuracy, sensitivity and precision to assay DOX in tablets and biological fluids.

A hybrid intelligent system for distributed dynamic scheduling

This chapter addresses the resolution of dynamic scheduling by means of meta-heuristic and multi-agent systems. Scheduling is an important aspect of automation in manufacturing systems. Several contributions have been proposed, but the problem is far from being solved satisfactorily, especially if scheduling concerns real world applications. The proposed multi-agent scheduling system assumes the existence of several resource agents (which are decision-making entities based on meta-heuristics) distributed inside the manufacturing system that interact with other agents in order to obtain optimal or near-optimal global performances.

Scheduling maintenance activities of electric power transmission networks using an hybrid constraint method

In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

Hybrid fuzzy Monte Carlo and logic programming model for distribution network reconfiguration in the presence of outages

This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

A hybrid recommendation approach for a tourism system

Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality.