The construction of a whole-cell biosensor for phosphonoacetate, based on the LysR-like transcriptional regulator PhnR from Pseudomonas fluorescens 23F

The phnA gene that encodes the carbon-phosphorus bond cleavage enzyme phosphonoacetate hydrolase is widely distributed in the environment, suggesting that its phosphonate substrate may play a significant role in biogeochemical phosphorus cycling. Surprisingly, however, no biogenic origin for phosphonoacetate has yet been established. To facilitate the search for its natural source we have constructed a whole-cell phosphonoacetate biosensor. The gene encoding the LysR-type transcriptional activator PhnR, which controls expression of the phosphonoacetate degradative operon in Pseudomonas fluorescens 23F, was inserted in the broad-host-range promoter probe vector pPROBE-NT, together with the promoter region of the structural genes. Cells of Escherichia coli DH5a that contained the resultant construct, pPANT3, exhibited phosphonoacetate-dependent green fluorescent protein fluorescence in response to threshold concentrations of as little as 0.5 µM phosphonoacetate, some 100 times lower than the detection limit of currently available non-biological analytical methods; the pPANT3 biosensor construct in Pseudomonas putida KT2440 was less sensitive, although with shorter response times. From a range of other phosphonates and phosphonoacetate analogues tested, only phosphonoacetaldehyde and arsonoacetate induced green fluorescent protein fluorescence in the E. coli DH5a (pPANT3) biosensor, although at much-reduced sensitivities (50 µM phosphonoacetaldehyde and 500 µM arsonoacetate).

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

Managing Software Requirements Changes Based On Negotiation-Style Revision

For any proposed software project, when the software requirements specification has been established, requirements changes may result in not only a modification of the requirements specification but also a series of modifications of all existing artifacts during the development. Then it is necessary to provide effective and flexible requirements changes management. In this paper, we present an approach to managing requirements changes based on Booth’s negotiation-style framework for belief revision. Informally, we consider the current requirements specification as a belief set about the system-to-be. The request of requirements change is viewed as new information about the same system-to-be. Then the process of executing the requirements change is a process of revising beliefs about the system-to-be. We design a family of belief negotiation models appropriate for different processes of requirements revision, including the setting of the request of requirements change being fully accepted, the setting of the current requirements specification being fully preserved, and that of the current specification and the request of requirements change reaching a compromise. In particular, the prioritization of requirements plays an important role in reaching an agreement in each belief negotiation model designed in this paper.

Advanced educational parallel DSP system based on TMS320C25 processors

This paper describes the design, application, and evaluation of a user friendly, flexible, scalable and inexpensive Advanced Educational Parallel (AdEPar) digital signal processing (DSP) system based on TMS320C25 digital processors to implement DSP algorithms. This system will be used in the DSP laboratory by graduate students to work on advanced topics such as developing parallel DSP algorithms. The graduating senior students who have gained some experience in DSP can also use the system. The DSP laboratory has proved to be a useful tool in the hands of the instructor to teach the mathematically oriented topics of DSP that are often difficult for students to grasp. The DSP laboratory with assigned projects has greatly improved the ability of the students to understand such complex topics as the fast Fourier transform algorithm, linear and circular convolution, the theory and design of infinite impulse response (IIR) and finite impulse response (FIR) filters. The user friendly PC software support of the AdEPar system makes it easy to develop DSP programs for students. This paper gives the architecture of the AdEPar DSP system. The communication between processors and the PC-DSP processor communication are explained. The parallel debugger kernels and the restrictions of the system are described. The programming in the AdEPar is explained, and two benchmarks (parallel FFT and DES) are presented to show the system performance.

Molecular Logic Gates and Luminescent Sensors Based on Photoinduced Electron Transfer

The competition between Photoinduced electron transfer (PET) and other de-excitation pathways such as fluorescence and phosphorescence can be controlled within designed molecular structures. Depending on the particular design, the resulting optical output is thus a function of various inputs such as ion concentration and excitation light dose. Once digitized into binary code, these input-output patterns can be interpreted according to Boolean logic. The single-input logic types of YES and NOT cover simple sensors and the double- (or higher-) input logic types represent other gates such as AND and OR. The logic-based arithmetic processors such as half-adders and half-subtractors are also featured. Naturally, a principal application of the more complex gates is in multi-sensing contexts.

Solid-state sodium-selective sensors based on screen-printed Ag/AgCl reference electrodes

The potentiometric and AC impedance characteristics of all solid-state sodium-selective electrodes based on planar screen-printed Ag/AgCl electrodes are described. Two solid-state designs have been investigated. The first was based on the deposition of a sodium-selective PVC membrane directly on top of a screen-printed Ag/AgCl electrode, The second design included a NaCl doped hydrogel layer, between the PVC and Ag\AgCl layers. The hydrogel provides a mechanism to relieve any blockage to charge transfer occurring when PVC membranes are used directly on top of Ag/AgCl and also improves adhesion between the two layers. Results suggest the electrodes display Fast ion exchange kinetics, low noise and drift. The performance compares favorably to that of a conventional ion-selective electrode with internal filling solution.

ELIMED:A new hadron therapy concept based on laser driven ion beams

Laser accelerated proton beams have been proposed to be used in different research fields. A great interest has risen for the potential replacement of conventional accelerating machines with laser-based accelerators, and in particular for the development of new concepts of more compact and cheaper hadrontherapy centers. In this context the ELIMED (ELI MEDical applications) research project has been launched by INFN-LNS and ASCR-FZU researchers within the pan-European ELI-Beamlines facility framework. The ELIMED project aims to demonstrate the potential clinical applicability of optically accelerated proton beams and to realize a laser-accelerated ion transport beamline for multi-disciplinary user applications. In this framework the eye melanoma, as for instance the uveal melanoma normally treated with 62 MeV proton beams produced by standard accelerators, will be considered as a model system to demonstrate the potential clinical use of laser-driven protons in hadrontherapy, especially because of the limited constraints in terms of proton energy and irradiation geometry for this particular tumour treatment. Several challenges, starting from laser-target interaction and beam transport development up to dosimetry and radiobiology, need to be overcome in order to reach the ELIMED final goals. A crucial role will be played by the final design and realization of a transport beamline capable to provide ion beams with proper characteristics in terms of energy spectrum and angular distribution which will allow performing dosimetric tests and biological cell irradiation. A first prototype of the transport beamline has been already designed and other transport elements are under construction in order to perform a first experimental test with the TARANIS laser system by the end of 2013. A wide international collaboration among specialists of different disciplines like Physics, Biology, Chemistry, Medicine and medical doctors coming from Europe, Japan, and the US is growing up around the ELIMED project with the aim to work on the conceptual design, technical and experimental realization of this core beamline of the ELI Beamlines facility. © 2013 SPIE.

Electrochemical sensor for catechol and dopamine based on a catalytic molecularly imprinted polymer-conducting polymer hybrid recognition element

One of the difficulties with using molecularly imprinted polymers (MIPs) and other electrically insulating materials as the recognition element in electrochemical sensors is the lack of a direct path for the conduction of electrons from the active sites to the electrode. We have sought to address this problem through the preparation and characterization of novel hybrid materials combining a catalytic MIP, capable of oxidizing the template, catechol, with an electrically conducting polymer. In this way a network of "molecular wires" assists in the conduction of electrons from the active sites within the MIP to the electrode surface. This was made possible by the design of a new monomer that combines orthogonal polymerizable functionality; comprising an aniline group and a methacrylamide. Conducting films were prepared on the surface of electrodes (Au on glass) by electropolymerization of the aniline moiety. A layer of MIP was photochemically grafted over the polyaniline, via N,N'-diethyldithiocarbamic acid benzyl ester (iniferter) activation of the methacrylamide groups. Detection of catechol by the hybrid-MIP sensor was found to be specific, and catechol oxidation was detected by cyclic voltammetry at the optimized operating conditions: potential range -0.6 V to +0.8 V (vs Ag/AgCl), scan rate 50 mV/s, PBS pH 7.4. The calibration curve for catechol was found to be linear to 144 µM, with a limit of detection of 228 nM. Catechol and dopamine were detected by the sensor, whereas analogues and potentially interfering compounds, including phenol, resorcinol, hydroquinone, serotonin, and ascorbic acid, had minimal effect (=3%) on the detection of either analyte. Nonimprinted hybrid electrodes and bare gold electrodes failed to give any response to catechol at concentrations below 0.5 mM. Finally, the catalytic properties of the sensor were characterized by chronoamperometry and were found to be consistent with Michaelis-Menten kinetics. © 2009 American Chemical Society.

Tailoring ionic liquid catalysts: structure, acidity and catalytic activity of protonic ionic liquids based on anionic clusters, [(HSO4)(H2SO4)x]− (x = 0, 1, or 2)

Aiming at inexpensive Brønsted-acidic ionic liquids, suitable for industrial-scale catalysis, a family of protonic ionic liquids based on nitrogen bases and sulfuric acid has been developed. Variation of the molar ratio of sulfuric acid, χH2SO4, was used to tune acidity. The liquid structure was studied using 1H NMR and IR spectroscopies, revealing the existence of hydrogen-bonded clusters, [(HSO4)(H2SO4)]−, for χH2SO4 > 0.50. Acidity, quantified by Gutmann Acceptor Number (AN), was found to be closely related to the liquid structure. The ionic liquids were employed as acid catalysts in a model reaction; Fischer esterification of acetic acid with 1-butanol. The reaction rate depended on two factors; for χH2SO4 > 0.50, the key parameter was acidity (expressed as AN value), while for χH2SO4 > 0.50 it was the mass transport (solubility of starting materials in the ionic liquid phase). Building on this insight, the ionic liquid catalyst and reaction conditions have been chosen. Conversion values of over 95% were achieved under exceptionally mild conditions, and using an inexpensive ionic liquid, which could be recycled up to eight times without diminution in conversion or selectivity. It has been demonstrated how structural studies can underpin rational design and development of an ionic liquid catalyst, and in turn lead to a both greener and economically viable process.

Behavioral Model Generation from Use Cases Based on Ontology Mapping and GRASP Patterns

This paper contributes a new approach for developing UML software designs from Natural Language (NL), making use of a meta-domain oriented ontology, well established software design principles and Natural Language Processing (NLP) tools. In the approach described here, banks of grammatical rules are used to assign event flows from essential use cases. A domain specific ontology is also constructed, permitting semantic mapping between the NL input and the modeled domain. Rules based on the widely-used General Responsibility Assignment Software Principles (GRASP) are then applied to derive behavioral models.

IRIDE:Interdisciplinary research infrastructure based on dual electron linacs and lasers

This paper describes the scientific aims and potentials as well as the preliminary technical design of IRIDE, an innovative tool for multi-disciplinary investigations in a wide field of scientific, technological and industrial applications. IRIDE will be a high intensity "particles factory", based on a combination of high duty cycle radio-frequency superconducting electron linacs and of high energy lasers. Conceived to provide unique research possibilities for particle physics, for condensed matter physics, chemistry and material science, for structural biology and industrial applications, IRIDE will open completely new research possibilities and advance our knowledge in many branches of science and technology. IRIDE is also supposed to be realized in subsequent stages of development depending on the assigned priorities. © 2013 Elsevier B.V.

A simplified procedure for sizing solar thermal systems based on national assessment methods in the UK and Ireland.

Solar heating systems have the potential to be an efficient renewable energy technology, provided they are sized correctly. Sizing a solar thermal system for domestic applications does not warrant the cost of a simulation. As a result simplified sizing procedures are required. The size of a system depends on a number of variables including the efficiency of the collector itself, the hot water demand and the solar radiation at a given location. Domestic Hot Water (DHW) demand varies with time and is assessed using a multi-parameter detailed model. Secondly, the national energy evaluation methodologies are evaluated from the perspective of solar thermal system sizing. Based on the assessment of the standards, limitations in the evaluation method for solar thermal systems are outlined and an adapted method, specific to the sizing of solar thermal systems, is proposed. The methodology is presented for two common dwelling scenarios. Results from this showed that it is difficult to achieve a high solar fraction given practical sizes of system infrastructure (storage tanks) for standard domestic properties. However, solar thermal systems can significantly offset energy loads due associated DHW consumption, particularly when sized appropriately. The presented methodology is valuable for simple solar system design and also for the quick comparison of salient criteria.

A Parametric Study of a Drive by Bridge Inspection System Based on the Morlet Wavelet

Many of the bridges currently in use worldwide are approaching the end of their design lives. However, rehabilitating and extending the lives of these structures raises important safety issues. There is also a need for increased monitoring which has considerable cost implications for bridge management systems. Existing structural health monitoring (SHM) techniques include vibration-based approaches which typically involve direct instrumentation of the bridge and are important as they can indicate the deterioration of the bridge condition. However, they can be labour intensive and expensive. In the past decade, alternative indirect vibration-based approaches which utilise the response of a vehicle passing over a bridge have been developed. This paper investigates such an approach; a low-cost approach for the monitoring of bridge structures which consists of the use of a vehicle fitted with accelerometers on its axles. The approach aims to detect damage in the bridge while obviating the need for direct instrumentation of the bridge. Here, the effectiveness of the approach in detecting damage in a bridge is investigated using a simplified vehicle-bridge interaction (VBI) model in theoretical simulations and a scaled VBI model in a laboratory experiment. In order to identify the existence and location of damage, the vehicle accelerations are recorded and processed using a continuous Morlet wavelet transform and a damage index is established. A parametric study is carried out to investigate the effect of parameters such as the bridge span length, vehicle speed, vehicle mass, damage level and road surface roughness on the accuracy of results.