A label-free DNA aptamer-based impedance biosensor for the detection of E. coli outer membrane proteins

A label-free DNA aptamer-based impedance biosensor for the detection of E. coli outer membrane proteins (OMPs) was developed. Two single stranded DNA sequences were tested as recognition elements and compared. The aptamer capture probes were immobilized, with and without 6-mercapto-1-hexanol (MCH) on a gold electrode. Each step of the modification process was characterized by Faradaic impedance spectroscopy (FIS). A linear relationship between the electron-transfer resistance (Ret) and E. coli OMPs concentration was demonstrated in a dynamic detection range of 1 × 10−7–2 × 10−6 M. Moreover, the aptasensor showed selectivity despite the presence of other possible water contaminates and could be regenerated under low pH condition. The developed biosensor shows great potential to be incorporated in a biochip and used for in situ detection of E. coli OMPs in water samples.

Molecular imprinted nanoelectrodes for ultra sensitive detection of ovarian cancer marker

The relentless discovery of cancer biomarkers demands improved methods for their detection. In this work, we developed protein imprinted polymer on three-dimensional gold nanoelectrode ensemble (GNEE) to detect epithelial ovarian cancer antigen-125 (CA 125), a protein biomarker associated with ovarian cancer. CA 125 is the standard tumor marker used to follow women during or after treatment for epithelial ovarian cancer. The template protein CA 125 was initially incorporated into the thin-film coating and, upon extraction of protein from the accessible surfaces on the thin film, imprints for CA 125 were formed. The fabrication and analysis of the CA 125 imprinted GNEE was done by using cyclic voltammetry (CV), differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS) techniques. The surfaces of the very thin, protein imprinted sites on GNEE are utilized for immunospecific capture of CA 125 molecules, and the mass of bound on the electrode surface can be detected as a reduction in the faradic current from the redox marker. Under optimal conditions, the developed sensor showed good increments at the studied concentration range of 0.5–400 U mL−1. The lowest detection limit was found to be 0.5 U mL−1. Spiked human blood serum and unknown real serum samples were analyzed. The presence of non-specific proteins in the serum did not significantly affect the sensitivity of our assay. Molecular imprinting using synthetic polymers and nanomaterials provides an alternative approach to the trace detection of biomarker proteins.

Screening of grapes and wine for azoxystrobin, kresoxim-methyl and trifloxystrobin fungicides by HPLC with diode array detection

The Quinone outside Inhibitors (QoI) are one of the most important and recent fungicide groups used in viticulture and also allowed by Integrated Pest Management. Azoxystrobin, kresoxim-methyl and trifloxystrobin are the main active ingredients for treating downy and powdery mildews that can be present in grapes and wines. In this paper, a method is reported for the analysis of these three QoI-fungicides in grapes and wine. After liquid–liquid extraction and a clean-up on commercial silica cartridges, analysis was by isocratic HPLC with diode array detection (DAD) with a run time of 13 min. Confirmation was by solid-phase micro-extraction (SPME), followed by GC/MS determination. The main validation parameters for the three compounds in grapes and wine were a limit of detection up to 0.073mg kg-1, a precision not exceeding 10.0% and an average recovery of 93% ±38.

A sensor classification strategy for robotic manipulators

In practice the robotic manipulators present some degree of unwanted vibrations. The advent of lightweight arm manipulators, mainly in the aerospace industry, where weight is an important issue, leads to the problem of intense vibrations. On the other hand, robots interacting with the environment often generate impacts that propagate through the mechanical structure and produce also vibrations. In order to analyze these phenomena a robot signal acquisition system was developed. The manipulator motion produces vibrations, either from the structural modes or from endeffector impacts. The instrumentation system acquires signals from several sensors that capture the joint positions, mass accelerations, forces and moments, and electrical currents in the motors. Afterwards, an analysis package, running off-line, reads the data recorded by the acquisition system and extracts the signal characteristics. Due to the multiplicity of sensors, the data obtained can be redundant because the same type of information may be seen by two or more sensors. Because of the price of the sensors, this aspect can be considered in order to reduce the cost of the system. On the other hand, the placement of the sensors is an important issue in order to obtain the suitable signals of the vibration phenomenon. Moreover, the study of these issues can help in the design optimization of the acquisition system. In this line of thought a sensor classification scheme is presented. Several authors have addressed the subject of the sensor classification scheme. White (White, 1987) presents a flexible and comprehensive categorizing scheme that is useful for describing and comparing sensors. The author organizes the sensors according to several aspects: measurands, technological aspects, detection means, conversion phenomena, sensor materials and fields of application. Michahelles and Schiele (Michahelles & Schiele, 2003) systematize the use of sensor technology. They identified several dimensions of sensing that represent the sensing goals for physical interaction. A conceptual framework is introduced that allows categorizing existing sensors and evaluates their utility in various applications. This framework not only guides application designers for choosing meaningful sensor subsets, but also can inspire new systems and leads to the evaluation of existing applications. Today’s technology offers a wide variety of sensors. In order to use all the data from the diversity of sensors a framework of integration is needed. Sensor fusion, fuzzy logic, and neural networks are often mentioned when dealing with problem of combing information from several sensors to get a more general picture of a given situation. The study of data fusion has been receiving considerable attention (Esteban et al., 2005; Luo & Kay, 1990). A survey of the state of the art in sensor fusion for robotics can be found in (Hackett & Shah, 1990). Henderson and Shilcrat (Henderson & Shilcrat, 1984) introduced the concept of logic sensor that defines an abstract specification of the sensors to integrate in a multisensor system. The recent developments of micro electro mechanical sensors (MEMS) with unwired communication capabilities allow a sensor network with interesting capacity. This technology was applied in several applications (Arampatzis & Manesis, 2005), including robotics. Cheekiralla and Engels (Cheekiralla & Engels, 2005) propose a classification of the unwired sensor networks according to its functionalities and properties. This paper presents a development of a sensor classification scheme based on the frequency spectrum of the signals and on a statistical metrics. Bearing these ideas in mind, this paper is organized as follows. Section 2 describes briefly the robotic system enhanced with the instrumentation setup. Section 3 presents the experimental results. Finally, section 4 draws the main conclusions and points out future work.

Influence of the abrasive particles size in the micro-abrasion wear tests of TiAlSiN thin coatings

Ball rotating micro-abrasion tribometers are commonly used to carry out wear tests on thin hard coatings. In these tests, different kinds of abrasives were used, as alumina (Al2O3), silicon carbide (SiC) or diamond. In each kind of abrasive, several particle sizes can be used. Some studies were developed in order to evaluate the influence of the abrasive particle shape in the micro-abrasion process. Nevertheless, the particle size was not well correlated with the material removed amount and wear mechanisms. In this work, slurry of SiC abrasive in distilled water was used, with three different particles size. Initial surface topography was accessed by atomic force microscopy (AFM). Coating hardness measurements were performed with a micro-hardness tester. In order to evaluate the wear behaviour, a TiAlSiN thin hard film was used. The micro-abrasion tests were carried out with some different durations. The abrasive effect of the SiC particles was observed by scanning electron microscopy (SEM) both in the films (hard material) as in the substrate (soft material), after coating perforation. Wear grooves and removed material rate were compared and discussed.

Micro-abrasion wear behaviour of TiAlCrSiN nanostructured coatings

The injection process of glass fibres reinforced plastics promotes the moulds surface degradation by erosion. In order to improve its wear resistance, several kinds of PVD thin hard coatings were used. It is well-known that nanostructures present a better compromise between hardness and toughness. Indeed, when the coating is constituted by a large number of ultra-thin different layers, cracks and interface troubles tend to decrease. However, it is not clear that these nanostructures present a better wear behaviour in erosion processes. In order to study its wear behaviour, a sputtered PVD nanostructured TiAlCrSiN coating was used. The substrate and film surfaces topography were analyzed by profilometry and atomic force microscopy techniques. Film adhesion to the substrate was evaluated by scratch tests. The surface hardness was measured with a Vickers micro-hardness tester. The wear resistance was evaluated by micro-abrasion with a rotating ball tribometer tests. Slurry of SiC particles in distilled water was used in order to provoke the surface abrasion. Different duration tests were performed in order to analyze the wear evolution. After these tests, the wear mechanisms developed were analyzed by scanning electron microscopy. Wear craters were measured and the wear rate was calculated and discussed. With the same purpose, coated inserts were mounted in an injection mould working with a 30% glass fibres reinforced polypropylene. After 45 000 cycles no relevant wear was registered.

Sensitive bi-enzymatic biosensor based on polyphenoloxidases–gold nanoparticles–chitosan hybrid film–graphene doped carbon paste electrode for carbamates detection

A bi-enzymatic biosensor (LACC–TYR–AuNPs–CS/GPE) for carbamates was prepared in a single step by electrodeposition of a hybrid film onto a graphene doped carbon paste electrode (GPE). Graphene and the gold nanoparticles (AuNPs) were morphologically characterized by transmission electron microscopy, X-ray photoelectron spectroscopy, dynamic light scattering and laser Doppler velocimetry. The electrodeposited hybrid film was composed of laccase (LACC), tyrosinase (TYR) and AuNPs entrapped in a chitosan (CS) polymeric matrix. Experimental parameters, namely graphene redox state, AuNPs:CS ratio, enzymes concentration, pH and inhibition time were evaluated. LACC–TYR–AuNPs–CS/GPE exhibited an improved Michaelis–Menten kinetic constant (26.9 ± 0.5 M) when compared with LACC–AuNPs–CS/GPE (37.8 ± 0.2 M) and TYR–AuNPs–CS/GPE (52.3 ± 0.4 M). Using 4-aminophenol as substrate at pH 5.5, the device presented wide linear ranges, low detection limits (1.68×10− 9 ± 1.18×10− 10 – 2.15×10− 7 ± 3.41×10− 9 M), high accuracy, sensitivity (1.13×106 ± 8.11×104 – 2.19×108 ± 2.51×107 %inhibition M− 1), repeatability (1.2–5.8% RSD), reproducibility (3.2–6.5% RSD) and stability (ca. twenty days) to determine carbaryl, formetanate hydrochloride, propoxur and ziram in citrus fruits based on their inhibitory capacity on the polyphenoloxidases activity. Recoveries at two fortified levels ranged from 93.8 ± 0.3% (lemon) to 97.8 ± 0.3% (orange). Glucose, citric acid and ascorbic acid do not interfere significantly in the electroanalysis. The proposed electroanalytical procedure can be a promising tool for food safety control.

3D-nanostructured Au electrodes for the event-specific detection of MON810 transgenic maize

In the present work, the development of a genosensor for the event-specific detection of MON810 transgenic maize is proposed. Taking advantage of nanostructuration, a cost-effective three dimensional electrode was fabricated and a ternary monolayer containing a dithiol, a monothiol and the thiolated capture probe was optimized to minimize the unspecific signals. A sandwich format assay was selected as a way of precluding inefficient hybridization associated with stable secondary target structures. A comparison between the analytical performance of the Au nanostructured electrodes and commercially available screen-printed electrodes highlighted the superior performance of the nanostructured ones. Finally, the genosensor was effectively applied to detect the transgenic sequence in real samples, showing its potential for future quantitative analysis.

Molecularly imprinted sensor for voltammetric detection of norfloxacin

In this work, a norfloxacin selective modified glassy carbon electrode (GCE) based on a molecularly imprinted polymer (MIP) as electrochemical sensor was developed. A suspension of multi-walled carbon nanotubes (MWCNTs) was deposited on the electrode surface. Subsequently, a molecularly imprinted film was prepared by electropolymerization, via cyclic voltammetry of pyrrole (PPy) in the presence of norfloxacin (NFX) as the template molecule. A control electrode (NIP) was also prepared. Scanning electron microscopy (SEM) and cyclic voltammetry in a ferrocyanide solution were performed for morphological and electrochemical characterisation, respectively. Several experimental parameters were studied and optimised. For quantification purposes the MIP/MWCNT/GCE was immersed in NFX solutions for 10 min, and the detection was performed in voltammetric cell by square wave voltammetry. The proposed sensor presented a linear behaviour, between peak current intensity and logarithmic concentration of NFX between 1 × 10−7 and 8 × 10−6 M. The obtained results presented good precision, with a repeatability of 4.3% and reproducibility of 9% and the detection limit was 4.6 × 10−8 M (S/N = 3). The developed sensor displayed good selectivity and operational lifetime, is simple to fabricate and easy to operate and was successfully applied to the analysis of NFX in urine samples.

Multi-agent simulation of continental, regional, and micro electricity markets

Renewable based power generation has significantly increased over the last years. However, this process has evolved separately from electricity markets, leading to an inadequacy of the present market models to cope with huge quantities of renewable energy resources, and to take full advantage of the presently existing and the increasing envisaged renewable based and distributed energy resources. This paper proposes the modelling of electricity markets at several levels (continental, regional and micro), taking into account the specific characteristics of the players and resources involved in each level and ensuring that the proposed models accommodate adequate business models able to support the contribution of all the resources in the system, from the largest to the smaller ones. The proposed market models are integrated in MASCEM (Multi- Agent Simulator of Competitive Electricity Markets), using the multi agent approach advantages for overcoming the current inadequacy and significant limitations of the presently existing electricity market simulators to deal with the complex electricity market models that must be adopted.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Iron oxide/gold core/shell nanomagnetic probes and CdS biolabels for amplified electrochemical immunosensing of Salmonella typhimurium

There is an imminent need for rapid methods to detect and determine pathogenic bacteria in food products as alternatives to the laborious and time-consuming culture procedures. In this work, an electrochemical immunoassay using iron/gold core/shell nanoparticles (Fe@Au) conjugated with anti-Salmonella antibodies was developed. The chemical synthesis and functionalization of magnetic and gold-coated magnetic nanoparticles is reported. Fe@Au nanoparticles were functionalized with different self-assembled monolayers and characterized using ultraviolet-visible spectrometry, transmission electron microscopy, and voltammetric techniques. The determination of Salmonella typhimurium, on screen-printed carbon electrodes, was performed by square-wave anodic stripping voltammetry through the use of CdS nanocrystals. The calibration curve was established between 1×101 and 1×106 cells/mL and the limit of detection was 13 cells/mL. The developed method showed that it is possible to determine the bacteria in milk at low concentrations and is suitable for the rapid (less than 1 h) and sensitive detection of S. typhimurium in real samples. Therefore, the developed methodology could contribute to the improvement of the quality control of food samples.

Celiac disease detection using a transglutaminase electrochemical immunosensor fabricated on nanohybrid screen-printed carbon electrodes

Celiac disease is a gluten-induced autoimmune enteropathy characterized by the presence of tissue tranglutaminase (tTG) autoantibodies. A disposable electrochemical immunosensor (EI) for the detection of IgA and IgG type anti-tTG autoantibodies in real patient’s samples is presented. Screen-printed carbon electrodes (SPCE) nanostructurized with carbon nanotubes and gold nanoparticles were used as the transducer surface. This transducer exhibits the excellent characteristics of carbon–metal nanoparticle hybrid conjugation and led to the amplification of the immunological interaction. The immunosensing strategy consisted of the immobilization of tTG on the nanostructured electrode surface followed by the electrochemical detection of the autoantibodies present in the samples using an alkaline phosphatase (AP) labelled anti-human IgA or IgG antibody. The analytical signal was based on the anodic redissolution of enzymatically generated silver by cyclic voltammetry. The results obtained were corroborated with a commercial ELISA kit indicating that the electrochemical immunosensor is a trustful analytical screening tool.

Ultrasensitive detection of ovarian cancer marker using immunoliposomes and gold nanoelectrodes

Mucin-16 (MUC16) is the established ovarian cancer marker used to follow the disease during or after treatment for epithelial ovarian cancer. The emerging science of cancer markers also demands for the new sensitive detection methods. In this work, we have developed an electrochemical immunosensor for antigen MUC16 using gold nanoelectrode ensemble (GNEE) and ferrocene carboxylic acid encapsulated liposomes tethered with monoclonal anti-Mucin-16 antibodies ( MUC16). GNEEs were fabricated by electroless deposition of the gold within the pores of polycarbonate track-etched membranes. Afterwards, MUC16 were immobilized on preformed self-assembled monolayer of cysteamine on the GNEE via cross-linking with EDC-Sulfo-NHS. A sandwich immunoassay was performed on MUC16 functionalized GNEE with MUC16 and immunoliposomes. The differential pulse voltammetry was employed to quantify the faradic redox response of ferrocene carboxylic acid released from immunoliposomes. The dose–response curve for MUC16 concentration was found between the range of 0.001–300 U mL−1. The lowest detection limit was found to be 5 × 10−4 U mL−1 (S/N = 3). We evaluated the performance of this developed immunosensor with commercial ELISA assay by comparing results obtained from spiked serum samples and real blood serum samples from volunteers.

Electrochemical immunosensor for multiplexed detection of food-borne pathogens using nanocrystal bioconjugates and MWCNT screen-printed electrode

Bacterial food poisoning is an ever-present threat that can be prevented with proper care and handling of food products. A disposable electrochemical immunosensor for the simultaneous measurements of common food pathogenic bacteria namely Escherichia coli O157:H7 (E. coli), campylobacter and salmonella were developed. The immunosensor was fabricated by immobilizing the mixture of anti-E. coli, anticampylobacter and anti-salmonella antibodies with a ratio of 1:1:1 on the surface of the multiwall carbon nanotube-polyallylamine modified screen printed electrode (MWCNT-PAH/SPE). Bacteria suspension became attached to the immobilized antibodies when the immunosensor was incubated in liquid samples. The sandwich immunoassay was performed with three antibodies conjugated with specific nanocrystal ( -E. coli-CdS, -campylobacter-PbS and -salmonella-CuS) which has releasable metal ions for electrochemical measurements. The square wave anodic stripping voltammetry (SWASV) was employed to measure released metal ions from bound antibody nanocrystal conjugates. The calibration curves for three selected bacteria were found in the range of 1 × 103 – 5 × 105 cells mL−1 with the limit of detection (LOD) 400 cells mL−1 for salmonella, 400 cells mL−1 for campylobacter and 800 cells mL−1 for E. coli. The precision and sensitivity of this method show the feasibility of multiplexed determination of bacteria in milk samples.