Real-time monitoring of electrochemically active biofilm developing behavior on bioanode by using EQCM and ATR/FTIR

In the current study, the relationship between current and biomass and bio-adhesion mechanism of electrogenic biofilm on electrode were investigated using EQCM and ATR-SEIRAS linking electrochemistry. The results indicated that cellular biomass of biofilm on QCM-crystal surface showed maximum value of 6.0 μg/cm2 in initial batch and 11.5 μg/cm2 in the second batch on mature biofilm, producing a similar maximum current density of 110 μA/μg. Especially, the optimum cell biomass linking high electricity production ratio (110 μA/μg) occurred before maximum biomass coming, implying that over-growth mature biofilm is not an optimum state for enhancing power output of MFCs. On the other hand, the spectra using ATR-SEIRAS technique linking electrochemistry obviously exhibited water structure adsorption change at early biofilm formation and meanwhile the water adsorption accompanied the adsorbed bacteria and the bound cells population on the electrode increased with time. Meanwhile, the direct contact of bacteria and electrode via outer-membrane protein can be confirmed via a series spectra shift at amide I and amide II modes and water movement from negative bands displacing by adsorbed bacteria. Our study provided supplementary information about the interaction between the microbes and electrode beyond traditional electrochemistry.

Dynamical Approach for Real-Time Monitoring of Agricultural Crops

In this paper, a novel approach for exploiting multitemporal remote sensing data focused on real-time monitoring of agricultural crops is presented. The methodology is defined in a dynamical system context using state-space techniques, which enables the possibility of merging past temporal information with an update for each new acquisition. The dynamic system context allows us to exploit classical tools in this domain to perform the estimation of relevant variables. A general methodology is proposed, and a particular instance is defined in this study based on polarimetric radar data to track the phenological stages of a set of crops. A model generation from empirical data through principal component analysis is presented, and an extended Kalman filter is adapted to perform phenological stage estimation. Results employing quad-pol Radarsat-2 data over three different cereals are analyzed. The potential of this methodology to retrieve vegetation variables in real time is shown.

Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.

Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power

Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F-0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F-0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (D-LR) appeared to be an effective way to predict whether F-0 immigrants could be identified for a particular pair of populations using a given set of markers.

Real-time imaging of human cortical activity evoked by painful esophageal stimulation

Background & Aims: Current models of visceral pain processing derived from metabolic brain imaging techniques fail to differentiate between exogenous (stimulus-dependent) and endogenous (non-stimulus-specific) neural activity. The aim of this study was to determine the spatiotemporal correlates of exogenous neural activity evoked by painful esophageal stimulation. Methods: In 16 healthy subjects (8 men; mean age, 30.2 ± 2.2 years), we recorded magnetoencephalographic responses to 2 runs of 50 painful esophageal electrical stimuli originating from 8 brain subregions. Subsequently, 11 subjects (6 men; mean age, 31.2 ± 1.8 years) had esophageal cortical evoked potentials recorded on a separate occasion by using similar experimental parameters. Results: Earliest cortical activity (P1) was recorded in parallel in the primary/secondary somatosensory cortex and posterior insula (∼85 ms). Significantly later activity was seen in the anterior insula (∼103 ms) and cingulate cortex (∼106 ms; P = .0001). There was no difference between the P1 latency for magnetoencephalography and cortical evoked potential (P = .16); however, neural activity recorded with cortical evoked potential was longer than with magnetoencephalography (P = .001). No sex differences were seen for psychophysical or neurophysiological measures. Conclusions: This study shows that exogenous cortical neural activity evoked by experimental esophageal pain is processed simultaneously in somatosensory and posterior insula regions. Activity in the anterior insula and cingulate - brain regions that process the affective aspects of esophageal pain - occurs significantly later than in the somatosensory regions, and no sex differences were observed with this experimental paradigm. Cortical evoked potential reflects the summation of cortical activity from these brain regions and has sufficient temporal resolution to separate exogenous and endogenous neural activity. © 2005 by the American Gastroenterological Association.

Real-time detection of DNA interactions with long-period fiber-grating-based biosensor

Using an optical biosensor based on a dual-peak long-period fiber grating, we have demonstrated the detection of interactions between biomolecules in real time. Silanization of the grating surface was successfully realized for the covalent immobilization of probe DNA, which was subsequently hybridized with the complementary target DNA sequence. It is interesting to note that the DNA biosensor was reusable after being stripped off the hybridized target DNA from the grating surface, demonstrating a function of multiple usability.

Cost and time control of construction project: inhibiting factors and mitigating measures in practice

Despite the availability of various control techniques and project control software many construction projects still do not achieve their cost and time objectives. Research in this area so far has mainly been devoted to identifying causes of cost and time overruns. There is limited research geared towards studying factors inhibiting the ability of practitioners to effectively control their projects. To fill this gap, a survey was conducted on 250 construction project organizations in the UK, which was followed by face-to-face interviews with experienced practitioners from 15 of these organizations. The common factors that inhibit both time and cost control during construction projects were first identified. Subsequently 90 mitigating measures have been developed for the top five leading inhibiting factors—design changes, risks/uncertainties, inaccurate evaluation of project time/duration, complexities and non-performance of subcontractors were recommended. These mitigating measures were classified as: preventive, predictive, corrective and organizational measures. They can be used as a checklist of good practice and help project managers to improve the effectiveness of control of their projects.

Cost and time control of construction projects: a survey of contractors and consultants in the UK

Numerous techniques have been developed to control cost and time of construction projects. However, there is limited research on issues surrounding the practical usage of these techniques. To address this, a survey was conducted on the top 150 construction companies and 100 construction consultancies in the UK aimed at identifying common project control practices and factors inhibiting effective project control in practice. It found that despite the vast application of control techniques a high proportion of respondents still experienced cost and time overruns on a significant proportion of their projects. Analysis of the survey results concluded that more effort should be geared at the management of the identified top project control inhibiting factors. This paper has outlined some measures for mitigating these inhibiting factors so that the outcome of project time and cost control can be improved in practice.

Real-time detection of DNA interactions with long-period fiber-grating-based biosensor

Using an optical biosensor based on a dual-peak long-period fiber grating, we have demonstrated the detection of interactions between biomolecules in real time. Silanization of the grating surface was successfully realized for the covalent immobilization of probe DNA, which was subsequently hybridized with the complementary target DNA sequence. It is interesting to note that the DNA biosensor was reusable after being stripped off the hybridized target DNA from the grating surface, demonstrating a function of multiple usability. © 2007 Optical Society of America.

Real-time scheduling of embedded applications on multi-core platforms

For the past several decades, we have experienced the tremendous growth, in both scale and scope, of real-time embedded systems, thanks largely to the advances in IC technology. However, the traditional approach to get performance boost by increasing CPU frequency has been a way of past. Researchers from both industry and academia are turning their focus to multi-core architectures for continuous improvement of computing performance. In our research, we seek to develop efficient scheduling algorithms and analysis methods in the design of real-time embedded systems on multi-core platforms. Real-time systems are the ones with the response time as critical as the logical correctness of computational results. In addition, a variety of stringent constraints such as power/energy consumption, peak temperature and reliability are also imposed to these systems. Therefore, real-time scheduling plays a critical role in design of such computing systems at the system level. We started our research by addressing timing constraints for real-time applications on multi-core platforms, and developed both partitioned and semi-partitioned scheduling algorithms to schedule fixed priority, periodic, and hard real-time tasks on multi-core platforms. Then we extended our research by taking temperature constraints into consideration. We developed a closed-form solution to capture temperature dynamics for a given periodic voltage schedule on multi-core platforms, and also developed three methods to check the feasibility of a periodic real-time schedule under peak temperature constraint. We further extended our research by incorporating the power/energy constraint with thermal awareness into our research problem. We investigated the energy estimation problem on multi-core platforms, and developed a computation efficient method to calculate the energy consumption for a given voltage schedule on a multi-core platform. In this dissertation, we present our research in details and demonstrate the effectiveness and efficiency of our approaches with extensive experimental results.

Westminster Serious Games Platform (wmin-SGP) a tool for real-time authoring of roleplay simulations for learning

The use of serious games in education and their pedagogical benefit is being widely recognized. However, effective integration of serious games in education depends on addressing two big challenges: the successful incorporation of motivation and engagement that can lead to learning; and the highly specialised skills associated with customised development to meet the required pedagogical objectives. This paper presents the Westminster Serious Games Platform (wmin-SGP) an authoring tool that allows educators/domain experts without games design and development technical skills to create bespoke roleplay simulations in three dimensional scenes featuring fully embodied virtual humans capable of verbal and non-verbal interaction with users fit for specific educational objectives. The paper presents the wmin-SGP system architecture and it evaluates its effectiveness in fulfilling its purpose via the implementation of two roleplay simulations, one for Politics and one for Law. In addition, it presents the results of two types of evaluation that address how successfully the wmin-SGP combines usability principles and game core drives based on the Octalysis gamification framework that lead to motivating games experiences. The evaluation results shows that the wmin-SGP: provides an intuitive environment and tools that support users without advanced technical skills to create in real-time bespoke roleplay simulations in advanced graphical interfaces; satisfies most of the usability principles; and provides balanced simulations based on the Octalysis framework core drives. The paper concludes with a discussion of future extension of this real time authoring tool and directions for further development of the Octalysis framework to address learning.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.

Real-time detection of faces in video streams

[EN]This paper describes a face detection system which goes beyond traditional approaches normally designed for still images. First the video stream context is considered to apply the detector, and therefore, the resulting system is designed taking into consideration a main feature available in a video stream, i.e. temporal coherence. The resulting system builds a feature based model for each detected face, and searches them using various model information in the next frame. The results achieved for video stream processing outperform Rowley-Kanade's and Viola-Jones' solutions providing eye and face data in a reduced time with a notable correct detection rate.