25 resultados para Robot sensing systems


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This paper discusses the importance of integrated sensing systems comprising techniques that give different types of data from a structure exposed to the marine environment so that its service life could reliably be predicted. For this purpose, a novel sensor combination was designed and installed in concrete panels which were exposed to Hangzhou Bay Bridge in China. The integrated sensor probe was used to monitor the cover concrete as well as the reinforcement. The sensor probes were connected to a monitoring station, which enabled access and control of the data remotely from Belfast, UK. The initial data obtained from the monitoring station gives interesting information on the early age properties of concrete and distinct variations in these properties with different types of concrete. This paper also reports the variation in electrical properties of different concrete samples and environmental data in response to the marine exposure condition at Hangzhou bay bridge.

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Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

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Ageing and deterioration of infrastructure is a challenge facing transport authorities. In
particular, there is a need for increased bridge monitoring in order to provide adequate
maintenance and to guarantee acceptable levels of transport safety. The Intelligent
Infrastructure group at Queens University Belfast (QUB) are working on a number of aspects
of infrastructure monitoring and this paper presents summarised results from three distinct
monitoring projects carried out by this group. Firstly the findings from a project on next
generation Bridge Weight in Motion (B-WIM) are reported, this includes full scale field testing
using fibre optic strain sensors. Secondly, results from early phase testing of a computer
vision system for bridge deflection monitoring are reported on. This research seeks to exploit
recent advances in image processing technology with a view to developing contactless
bridge monitoring approaches. Considering the logistical difficulty of installing sensors on a
‘live’ bridge, contactless monitoring has some inherent advantages over conventional
contact based sensing systems. Finally the last section of the paper presents some recent
findings on drive by bridge monitoring. In practice a drive-by monitoring system will likely
require GPS to allow the response of a given bridge to be identified; this study looks at the
feasibility of using low-cost GPS sensors for this purpose, via field trials. The three topics
outlined above cover a spectrum of SHM approaches namely, wired monitoring, contactless
monitoring and drive by monitoring

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Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

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The multitude of biomolecular and regulatory factors involved in staphylococcal adhesion and biofilm formation owe much to their ability to colonize surfaces, allowing the biofilm form to become the preferential bacterial phenotype. Judging by total number, biomass and variety of environments colonized, bacteria can be categorized as the most successful lifeform on earth. This is due to the ability of bacteria and other microorganisms to respond phenotypically via biomolecular processes to the stresses of their surrounding environment. This review focuses on the specific pathways involved in the adhesion of the Gram-positive bacteria Staphylococcus epidermidis and Staphylococcus aureus with reference to the role of specific cell surface adhesins, the ica operon, accumulation-associated proteins and quorum-sensing systems and their significance in medical device-related infection.

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Pseudomonas aeruginosa and Escherichia coli are the most prevalent Gram-negative biofilm forming medical device associated pathogens, particularly with respect to catheter associated urinary tract infections. In a similar manner to Gram-positive bacteria, Gram-negative biofilm formation is fundamentally determined by a series of steps outlined more fully in this review, namely adhesion, cellular aggregation, and the production of an extracellular polymeric matrix. More specifically this review will explore the biosynthesis and role of pili and flagella in Gram-negative adhesion and accumulation on surfaces in Pseudomonas aeruginosa and Escherichia coli. The process of biofilm maturation is compared and contrasted in both species, namely the production of the exopolysaccharides via the polysaccharide synthesis locus (Psl), pellicle Formation (Pel) and alginic acid synthesis in Pseudomonas aeruginosa, and UDP-4-amino-4-deoxy-l-arabinose and colonic acid synthesis in Escherichia coli. An emphasis is placed on the importance of the LuxR homologue sdiA; the luxS/autoinducer-II; an autoinducer-III/epinephrine/norepinephrine and indole mediated Quorum sensing systems in enabling Gram-negative bacteria to adapt to their environments. The majority of Gram-negative biofilms consist of polysaccharides of a simple sugar structure (either homo- or heteropolysaccharides) that provide an optimum environment for the survival and maturation of bacteria, allowing them to display increased resistance to antibiotics and predation.

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Bridge Weigh in Motion (B-WIM) uses accurate sensing systems to transform an existing bridge into a mechanism to determine actual traffic loading. This information on traffic loading can enable efficient and economical management of transport networks and is becoming a valuable tool for bridge safety assessment. B-WIM can provide site specific traffic loading on deteriorating bridges, which can be used to determine if the reduced capacity is still sufficient to allow the structure to remain operational and minimise unnecessary replacement or rehabilitation costs and prevent disruption to traffic. There have been numerous reports on the accuracy classifications of existing B-WIM installations and some common issues have emerged. This paper details some of the recent developments in B-WIM which were aimed at overcoming these issues. A new system has been developed at Queens University Belfast using fibre optic sensors to provide accurate axle detection and improved accuracy overall. The results presented in this paper show that the fibre optic system provided much more accurate results than conventional WIM systems, as the FOS provide clearer signals at high scanning rates which require less filtering and less post processing. A major disadvantage of existing B-WIM systems is the inability to deal with more than one vehicle on the bridge at the same time; sensor strips have been proposed to overcome this issue. A bridge can be considered safe if the probability that load exceeds resistance is acceptably low, hence B-WIM information from advanced sensors can provide confidence in our ageing structures.

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First, the direct and indirect electrochemical oxidation of ammonia has been studied by cyclic voltammetry at glassy carbon electrodes in propylene carbonate. In the case of the indirect oxidation of ammonia, its analytical utility of indirect for ammonia sensing was examined in the range from 10 and 100 ppm by measuring the peak current of new wave resulting from reaction between ammonia and hydroquinone, as function of ammonia concentration, giving a sensitivity 1.29 x 10(-7) A ppm(-1) (r(2)=0.999) and limit-of-detection 5 ppm ammonia. Further, the direct oxidation of ammonia has been investigated in several room temperature ionic liquids (RTILs), namely 1-butyl-3-methylimidazolium tetrafluoroborate ([C(4)mim] [BF4]), 1-butyl-3-methylimiclazolium trifluoromethylsulfonate ([C4mim] [OTf]), 1-Ethyl -3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([C(2)mim] [NTf2]), 1-butyl-3-methylimidazolium bis(tritluoromethylsulfonyl)imide ([C4mim] [NTf2]) and 1-butyl-3-methylimidazolium hexafluorophosphate ([C4mim] [PF6]) on a 10 put diameter Pt microdisk electrode. In four of the RTILs studied, the cyclic voltammetric analysis suggests that ammonia is initially oxidized to nitrogen, N-2, and protons, which are transferred to an ammonia molecule, forming NH4+ via the protonation of the anion(s) (A(-)). However, in [C4mim] [PF6], the protonated anion was formed first, followed by NH4+. In all five RTILs, both HA and NH4+ are reduced at the electrode surface, forming hydrogen gas, which is then oxidized. The analytical ability of this work has also been explored further, giving a limit-of-detection close to 50 ppm in [C(2)mim] [NTf2], [C(4)mim] [OTf], [C(4)mim] [BF4], with a sensitivity of ca. 6 x 10(-7) A ppm(-1) (r(2) = 0.999) for all three ionic liquids, showing that the limit of detection was ca. ten times larger than that in propylene carbonate since ammonia in propylene carbonate might be more soluble in comparison with RTILs when considering the higher viscosity of RTILs.

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Molecular logic-based computation continues to throw up new applications in sensing and switching, the newest of which is the edge detection of objects. The scope of this phenomenon is mapped out by the use of structure-activity relationships, where several structures of the molecules and of the objects are examined. The different angles and curvatures of the objects are followed with good-fidelity in the visualized edges, even when the objects are in reverse video.

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Burkholderia cenocepacia is commonly found in the environment and also as an important opportunistic pathogen infecting patients with cystic fibrosis. Successful infection by this bacterium requires coordinated expression of virulence factors, which is achieved through different quorum sensing (QS) regulatory systems. Biofilm formation and Type 6 secretion system (T6SS) expression in B. cenocepacia K56-2 are positively regulated by QS and negatively regulated by the sensor kinase hybrid AtsR. This study reveals that in addition to affecting biofilm and T6SS activity, the deletion of atsR in B. cenocepacia leads to overproduction of other QS-regulated virulence determinants including proteases and swarming motility. Expression of the QS genes, cepIR and cciIR, was upregulated in the ?atsR mutant and resulted in early and increased N-acylhomoserine lactone (AHL) production, suggesting that AtsR plays a role in controlling the timing and fine-tuning of virulence gene expression by modulating QS signalling. Furthermore, a ?atsR?cepI?cciI mutant could partially upregulate the same virulence determinants indicating that AtsR also modulates the expression of virulence genes by a second mechanism, independently of any AHL production. Together, our results strongly suggest that AtsR is a global virulence regulator in B. cenocepacia.

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Taxonomic studies of the past few years have shown that the Burkholderia cepacia complex, a heterogeneous group of B. cepacia-like organisms, consists of at least nine species. B. cepacia complex strains are ubiquitously distributed in nature and have been used for biocontrol, bioremediation, and plant growth promotion purposes. At the same time, B. cepacia complex strains have emerged as important opportunistic pathogens of humans, particularly those with cystic fibrosis. All B. cepacia complex species investigated thus far use quorum-sensing (QS) systems that rely on N-acylhomoserine lactone (AHL) signal molecules to express certain functions, including the production of extracellular proteases, swarming motility, biofilm formation, and pathogenicity, in a population-density-dependent manner. In this study we constructed a broad-host-range plasmid that allowed the heterologous expression of the Bacillus sp. strain 240B1 AiiA lactonase, which hydrolyzes the lactone ring of various AHL signal molecules, in all described B. cepacia complex species. We show that expression of AiiA abolished or greatly reduced the accumulation of AHL molecules in the culture supernatants of all tested B. cepacia complex strains. Phenotypic characterization of wild-type and transgenic strains revealed that protease production, swarming motility, biofilm formation, and Caenorhabditis elegans killing efficiency was regulated by AHL in the large majority of strains investigated.

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The rapid proliferation of remote sensing and geographic information systems (GIS) into geomorphologic mapping has increased the objectivity and efficiency of landform segmentation, measurement, and classification. The near ubiquitous presence of Earth-observing satellites provides an array of perspectives to visualize the biophysical characteristics of landscapes, access inhospitable terrain on a predictable schedule, and study landscape processes when conditions are hazardous. GIS technology has altered the analysis, visualization, and dissemination of landform data due to the shared theoretical concepts that are fundamental to geomorphology and GIScience. The authors review geospatial technology applications in landform mapping (including emerging issues) within glacial, volcanic, landslide, and fluvial research.

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Naphthalenic compounds are a rich resource for designers of fluorescent sensing/switching/logic systems. The degree of internal charge transfer (ICT) character in the fluorophore excited states can vary from negligible to substantial. Naphthalene-1,8;4,5-diimides (11–13), 1,8-naphthalimides (16) and 4-chloro-1,8-naphthalimides (15) are of the former type. The latter type is represented by the 4-alkylamino-1,8-naphthalimides (1). Whether ICT-based or not, these serve as the fluorophore in ‘fluorophore-spacer-receptor’ switching systems where PET holds sway until the receptor is bound to H+. On the other hand, 4-dialkylamino-1,8-naphthalimides (3–4) show modest H+-induced fluorescence switching unless the 4-dialkylamino group is a part of a small ring (5). Electrostatic destabilization of a non-emissive twisted internal charge transfer (ICT) excited state is the origin of this behaviour. An evolution to the non-emissive twisted ICT excited state is responsible for the weak emission of the model compound 6 (and related structures 7 and 8) across the pH range. Twisted ICT excited states are also implicated in the switch 9 and its model compound 10, which are based on the 6-dialkylamino-3H-benzimidazo[2,1-a]benz[d,e]isoquinolin-3-one fluorophore.