Structural reliability prediction of a steel bridge element using Dynamic Object Oriented Bayesian Network (DOOBN)

Different from conventional methods for structural reliability evaluation, such as, first/second-order reliability methods (FORM/SORM) or Monte Carlo simulation based on corresponding limit state functions, a novel approach based on dynamic objective oriented Bayesian network (DOOBN) for prediction of structural reliability of a steel bridge element has been proposed in this paper. The DOOBN approach can effectively model the deterioration processes of a steel bridge element and predict their structural reliability over time. This approach is also able to achieve Bayesian updating with observed information from measurements, monitoring and visual inspection. Moreover, the computational capacity embedded in the approach can be used to facilitate integrated management and maintenance optimization in a bridge system. A steel bridge girder is used to validate the proposed approach. The predicted results are compared with those evaluated by FORM method.

Automated object identification using optical video cameras on construction sites

Visual recording devices such as video cameras, CCTVs, or webcams have been broadly used to facilitate work progress or safety monitoring on construction sites. Without human intervention, however, both real-time reasoning about captured scenes and interpretation of recorded images are challenging tasks. This article presents an exploratory method for automated object identification using standard video cameras on construction sites. The proposed method supports real-time detection and classification of mobile heavy equipment and workers. The background subtraction algorithm extracts motion pixels from an image sequence, the pixels are then grouped into regions to represent moving objects, and finally the regions are identified as a certain object using classifiers. For evaluating the method, the formulated computer-aided process was implemented on actual construction sites, and promising results were obtained. This article is expected to contribute to future applications of automated monitoring systems of work zone safety or productivity.

Analysis of Object-Specific Authorization Protocol (OSAP) using coloured petri nets - Version 1.0

Analyzing security protocols is an ongoing research in the last years. Different types of tools are developed to make the analysis process more precise, fast and easy. These tools consider security protocols as black boxes that can not easily be composed. It is difficult or impossible to do a low-level analysis or combine different tools with each other using these tools. This research uses Coloured Petri Nets (CPN) to analyze OSAP trusted computing protocol. The OSAP protocol is modeled in different levels and it is analyzed using state space method. The produced model can be combined with other trusted computing protocols in future works.

Spatially offset Raman spectroscopy (SORS) for the analysis and detection of packaged pharmaceuticals and concealed drugs

Spatially offset Raman spectroscopy (SORS) is a powerful new technique for the non-invasive detection and identification of concealed substances and drugs. Here, we demonstrate the SORS technique in several scenarios that are relevant to customs screening, postal screening, drug detection and forensics applications. The examples include analysis of a multi-layered postal package to identify a concealed substance; identification of an antibiotic capsule inside its plastic blister pack; analysis of an envelope containing a powder; and identification of a drug dissolved in a clear solvent, contained in a non-transparent plastic bottle. As well as providing practical examples of SORS, the results highlight several considerations regarding the use of SORS in the field, including the advantages of different analysis geometries and the ability to tailor instrument parameters and optics to suit different types of packages and samples. We also discuss the features and benefits of SORS in relation to existing Raman techniques, including confocal microscopy, wide area illumination and the conventional backscattered Raman spectroscopy. The results will contribute to the recognition of SORS as a promising method for the rapid, chemically-specific analysis and detection of drugs and pharmaceuticals.

Spatial population genetic structure reveals strong natal site fidelity in Echinocladius martini (Diptera: Chironomidae) in northeast Queensland, Australia

1. A diverse array of patterns has been reported regarding the spatial extent of population genetic structure and effective dispersal in freshwater macroinvertebrates. In river systems, the movements of many taxa can be restricted to varying degrees by the natural stream channel hierarchy. 2. In this study, we sampled populations of the non-biting freshwater midge Echinocladius martini in the Paluma bioregion of tropical northeast Queensland to investigate fine scale patterns of within- and among-stream dispersal and gene flow within a purported historical refuge. We amplified a 639 bp fragment of mitochondrial COI and analysed genetic structure using pairwise ΦST, hierarchical AMOVA, Mantel tests and a parsimony network. Genetic variation was partitioned among stream sections using Streamtree to investigate the effect of potential instream dispersal barriers. 3. The data revealed strong natal site fidelity and significant differentiation among neighbouring, geographically proximate streams. We found evidence for only episodic adult flight among sites on separate stream reaches. Overall, however, our data suggested that both larval and adult dispersal was largely limited to within a stream channel. 4. This may arise from a combination of the high density of riparian vegetation physically restricting dispersal and from the joint effects of habitat stability and large population sizes. Together these may mitigate the requirement for movement among streams to avoid inbreeding and local extinction due to habitat change and may thus enable persistence of upstream populations in the absence of regular compensatory upstream flight. Taken together, these data suggest that dispersal of E. martini is highly restricted, to the scale of only a few kilometres, and hence occurs predominantly within the natal stream.

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design

Spectral–texture feature extraction using statistical moments with application to object-based vegetation species classification

The use of appropriate features to characterise an output class or object is critical for all classification problems. In order to find optimal feature descriptors for vegetation species classification in a power line corridor monitoring application, this article evaluates the capability of several spectral and texture features. A new idea of spectral–texture feature descriptor is proposed by incorporating spectral vegetation indices in statistical moment features. The proposed method is evaluated against several classic texture feature descriptors. Object-based classification method is used and a support vector machine is employed as the benchmark classifier. Individual tree crowns are first detected and segmented from aerial images and different feature vectors are extracted to represent each tree crown. The experimental results showed that the proposed spectral moment features outperform or can at least compare with the state-of-the-art texture descriptors in terms of classification accuracy. A comprehensive quantitative evaluation using receiver operating characteristic space analysis further demonstrates the strength of the proposed feature descriptors.

High-density lipoprotein and the risk of recurrent venous thromboembolism

BACKGROUND - High-density lipoprotein (HDL) protects against arterial atherothrombosis, but it is unknown whether it protects against recurrent venous thromboembolism. METHODS AND RESULTS - We studied 772 patients after a first spontaneous venous thromboembolism (average follow-up 48 months) and recorded the end point of symptomatic recurrent venous thromboembolism, which developed in 100 of the 772 patients. The relationship between plasma lipoprotein parameters and recurrence was evaluated. Plasma apolipoproteins AI and B were measured by immunoassays for all subjects. Compared with those without recurrence, patients with recurrence had lower mean (±SD) levels of apolipoprotein AI (1.12±0.22 versus 1.23±0.27 mg/mL, P<0.001) but similar apolipoprotein B levels. The relative risk of recurrence was 0.87 (95% CI, 0.80 to 0.94) for each increase of 0.1 mg/mL in plasma apolipoprotein AI. Compared with patients with apolipoprotein AI levels in the lowest tertile (<1.07 mg/mL), the relative risk of recurrence was 0.46 (95% CI, 0.27 to 0.77) for the highest-tertile patients (apolipoprotein AI >1.30 mg/mL) and 0.78 (95% CI, 0.50 to 1.22) for midtertile patients (apolipoprotein AI of 1.07 to 1.30 mg/mL). Using nuclear magnetic resonance, we determined the levels of 10 major lipoprotein subclasses and HDL cholesterol for 71 patients with recurrence and 142 matched patients without recurrence. We found a strong trend for association between recurrence and low levels of HDL particles and HDL cholesterol. CONCLUSIONS - Patients with high levels of apolipoprotein AI and HDL have a decreased risk of recurrent venous thromboembolism. © 2007 American Heart Association, Inc.

High-density lipoprotein deficiency and dyslipoproteinemia associated with venous thrombosis in men

Background-Although dyslipoproteinemia is associated with arterial atherothrombosis, little is known about plasma lipoproteins in venous thrombosis patients. Methods and Results-We determined plasma lipoprotein subclass concentrations using nuclear magnetic resonance spectroscopy and antigenic levels of apolipoproteins AI and B in blood samples from 49 male venous thrombosis patients and matched controls aged <55 years. Venous thrombosis patients had significantly lower levels of HDL particles, large HDL particles, HDL cholesterol, and apolipoprotein AI and significantly higher levels of LDL particles and small LDL particles. The quartile-based odds ratios for decreased HDL particle and apolipoprotein AI levels in patients compared with controls were 6.5 and 6.0 (95% CI, 2.3 to 19 and 2.1 to 17), respectively. Odds ratios for apolipoprotein B/apolipoprotein AI ratio and LDL cholesterol/HDL cholesterol ratio were 6.3 and 2.7 (95% CI, 1.9 to 21 and 1.1 to 6.5), respectively. When polymorphisms in genes for hepatic lipase, endothelial lipase, and cholesteryl ester transfer protein were analyzed, patients differed significantly from controls in the allelic frequency for the TaqI B1/B2 polymorphism in cholesteryl ester transfer protein, consistent with the observed pattern of lower HDL and higher LDL. Conclusions-Venous thrombosis in men aged <55 years old is associated with dyslipoproteinemia involving lower levels of HDL particles, elevated levels of small LDL particles, and an elevated ratio of apolipoprotein B/apolipoprotein AI. This dyslipoproteinemia seems associated with a related cholesteryl ester transfer protein genotype difference. © 2005 American Heart Association, Inc.

Improved image quality for x-ray CT imaging of gel dosimeters

Purpose: This study provides a simple method for improving precision of x-ray computed tomography (CT) scans of irradiated polymer gel dosimetry. The noise affecting CT scans of irradiated gels has been an impediment to the use of clinical CT scanners for gel dosimetry studies. Method: In this study, it is shown that multiple scans of a single PAGAT gel dosimeter can be used to extrapolate a ‘zero-scan’ image which displays a similar level of precision to an image obtained by averaging multiple CT images, without the compromised dose measurement resulting from the exposure of the gel to radiation from the CT scanner. Results: When extrapolating the zero-scan image, it is shown that exponential and simple linear fits to the relationship between Hounsfield unit and scan number, for each pixel in the image, provides an accurate indication of gel density. Conclusions: It is expected that this work will be utilised in the analysis of three-dimensional gel volumes irradiated using complex radiotherapy treatments.

Stochastic simulation of chemical reactions in spatially complex media

Discrete stochastic simulations, via techniques such as the Stochastic Simulation Algorithm (SSA) are a powerful tool for understanding the dynamics of chemical kinetics when there are low numbers of certain molecular species. However, an important constraint is the assumption of well-mixedness and homogeneity. In this paper, we show how to use Monte Carlo simulations to estimate an anomalous diffusion parameter that encapsulates the crowdedness of the spatial environment. We then use this parameter to replace the rate constants of bimolecular reactions by a time-dependent power law to produce an SSA valid in cases where anomalous diffusion occurs or the system is not well-mixed (ASSA). Simulations then show that ASSA can successfully predict the temporal dynamics of chemical kinetics in a spatially constrained environment.