Improving detection probabilities for pests in stored grains

BACKGROUND: The presence of insects in stored grains is a significant problem for grain farmers, bulk grain handlers and distributors worldwide. Inspections of bulk grain commodities is essential to detect pests and therefore to reduce the risk of their presence in exported goods. It has been well documented that insect pests cluster in response to factors such as microclimatic conditions within bulk grain. Statistical sampling methodologies for grains, however, have typically considered pests and pathogens to be homogeneously distributed throughout grain commodities. In this paper we demonstrate a sampling methodology that accounts for the heterogeneous distribution of insects in bulk grains. RESULTS: We show that failure to account for the heterogeneous distribution of pests may lead to overestimates of the capacity for a sampling program to detect insects in bulk grains. Our results indicate the importance of the proportion of grain that is infested in addition to the density of pests within the infested grain. We also demonstrate that the probability of detecting pests in bulk grains increases as the number of sub-samples increases, even when the total volume or mass of grain sampled remains constant. CONCLUSION: This study demonstrates the importance of considering an appropriate biological model when developing sampling methodologies for insect pests. Accounting for a heterogeneous distribution of pests leads to a considerable improvement in the detection of pests over traditional sampling models.

Spatial variability of soil carbon in forested and cultivated sites: Implications for change detection

The potential to sequester atmospheric carbon in agricultural and forest soils to offset greenhouse gas emissions has generated interest in measuring changes in soil carbon resulting from changes in land management. However, inherent spatial variability of soil carbon limits the precision of measurement of changes in soil carbon and hence, the ability to detect changes. We analyzed variability of soil carbon by intensively sampling sites under different land management as a step toward developing efficient soil sampling designs. Sites were tilled crop-land and a mixed deciduous forest in Tennessee, and old-growth and second-growth coniferous forest in western Washington, USA. Six soil cores within each of three microplots were taken as an initial sample and an additional six cores were taken to simulate resampling. Soil C variability was greater in Washington than in Tennessee, and greater in less disturbed than in more disturbed sites. Using this protocol, our data suggest that differences on the order of 2.0 Mg C ha(-1) could be detected by collection and analysis of cores from at least five (tilled) or two (forest) microplots in Tennessee. More spatial variability in the forested sites in Washington increased the minimum detectable difference, but these systems, consisting of low C content sandy soil with irregularly distributed pockets of organic C in buried logs, are likely to rank among the most spatially heterogeneous of systems. Our results clearly indicate that consistent intramicroplot differences at all sites will enable detection of much more modest changes if the same microplots are resampled.

A novel high voltage pulsed power supply based on low voltage switch-capacitor units

This paper presents a high voltage pulsed power system based on low voltage switch-capacitor units connected to a current source for several applications such as plasma systems. A modified positive buck-boost converter topology is used to utilize the current source concept and a series of low voltage switch-capacitor units is connected to the current source in order to provide high voltage with high voltage stress (dv/dt) as demanded by loads. This pulsed power converter is flexible in terms of energy control, in that the stored energy in the current source can be adjusted by changing the current magnitude to significantly improve the efficiency of various systems with different requirements. Output voltage magnitude and stress (dv/dt) can be controlled by a proper selection of components and control algorithm to turn on and off switching devices.

Osteogenic induction of human bone marrow-derived mesenchymal progenitor cells in novel synthetic polymer-hydrogel matrices

The aim of this project was to investigate the in vitro osteogenic potential of human mesenchymal progenitor cells in novel matrix architectures built by means of a three-dimensional bioresorbable synthetic framework in combination with a hydrogel. Human mesenchymal progenitor cells (hMPCs) were isolated from a human bone marrow aspirate by gradient centrifugation. Before in vitro engineering of scaffold-hMPC constructs, the adipogenic and osteogenic differentiation potential was demonstrated by staining of neutral lipids and induction of bone-specific proteins, respectively. After expansion in monolayer cultures, the cells were enzymatically detached and then seeded in combination with a hydrogel into polycaprolactone (PCL) and polycaprolactone-hydroxyapatite (PCL-HA) frameworks. This scaffold design concept is characterized by novel matrix architecture, good mechanical properties, and slow degradation kinetics of the framework and a biomimetic milieu for cell delivery and proliferation. To induce osteogenic differentiation, the specimens were cultured in an osteogenic cell culture medium and were maintained in vitro for 6 weeks. Cellular distribution and viability within three-dimensional hMPC bone grafts were documented by scanning electron microscopy, cell metabolism assays, and confocal laser microscopy. Secretion of the osteogenic marker molecules type I procollagen and osteocalcin was analyzed by semiquantitative immunocytochemistry assays. Alkaline phosphatase activity was visualized by p-nitrophenyl phosphate substrate reaction. During osteogenic stimulation, hMPCs proliferated toward and onto the PCL and PCL-HA scaffold surfaces and metabolic activity increased, reaching a plateau by day 15. The temporal pattern of bone-related marker molecules produced by in vitro tissue-engineered scaffold-cell constructs revealed that hMPCs differentiated better within the biomimetic matrix architecture along the osteogenic lineage.

Novel PCL-based honeycomb scaffolds as drug delivery systems for rhBMP-2

This study investigated a novel drug delivery system (DDS), consisting of polycaprolactone (PCL) or polycaprolactone 20% tricalcium phosphate (PCL-TCP) biodegradable scaffolds, fibrin Tisseel sealant and recombinant bone morphogenetic protein-2 (rhBMP-2) for bone regeneration. PCL and PCL-TCP-fibrin composites displayed a loading efficiency of 70% and 43%, respectively. Fluorescence and scanning electron microscopy revealed sparse clumps of rhBMP-2 particles, non-uniformly distributed on the rods’ surface of PCL-fibrin composites. In contrast, individual rhBMP-2 particles were evident and uniformly distributed on the rods’ surface of the PCL-TCP-fibrin composites. PCL-fibrin composites loaded with 10 and 20 μg/ml rhBMP-2 demonstrated a triphasic release profile as quantified by an enzyme-linked immunosorbent assay (ELISA). This consisted of burst releases at 2 h, and days 7 and 16. A biphasic release profile was observed for PCL-TCP-fibrin composites loaded with 10 μg/ml rhBMP-2, consisting of burst releases at 2 h and day 14. PCL-TCP-fibrin composites loaded with 20 μg/ml rhBMP-2 showed a tri-phasic release profile, consisting of burst releases at 2 h, and days 10 and 21. We conclude that the addition of TCP caused a delay in rhBMP-2 release. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) and alkaline phosphatase assay verified the stability and bioactivity of eluted rhBMP-2 at all time points

Flow modeling in a novel non-perfusion conical bioreactor

We have developed a bioreactor vessel design which has the advantages of simplicity and ease of assembly and disassembly, and with the appropriately determined flow rate, even allows for a scaffold to be suspended freely regardless of its weight. This article reports our experimental and numerical investigations to evaluate the performance of a newly developed non-perfusion conical bioreactor by visualizing the flow through scaffolds with 45° and 90° fiber lay down patterns. The experiments were conducted at the Reynolds numbers (Re) 121, 170, and 218 based on the local velocity and width of scaffolds. The flow fields were captured using short-time exposures of 60 µm particles suspended in the bioreactor and illuminated using a thin laser sheet. The effects of scaffold fiber lay down pattern and Reynolds number were obtained and correspondingly compared to results obtained from a computational fluid dynamics (CFD) software package. The objectives of this article are twofold: to investigate the hypothesis that there may be an insufficient exchange of medium within the interior of the scaffold when using our non-perfusion bioreactor, and second, to compare the flows within and around scaffolds of 45° and 90° fiber lay down patterns. Scaffold porosity was also found to influence flow patterns. It was therefore shown that fluidic transport could be achieved within scaffolds with our bioreactor design, being a non-perfusion vessel. Fluid velocities were generally same of the same or one order lower in magnitude as compared to the inlet flow velocity. Additionally, the 90° fiber lay down pattern scaffold was found to allow for slightly higher fluid velocities within, as compared to the 45° fiber lay down pattern scaffold. This was due to the architecture and pore arrangement of the 90° fiber lay down pattern scaffold, which allows for fluid to flow directly through (channel-like flow).

The QUT-NOISE-TIMIT corpus for the evaluation of voice activity detection algorithms

The QUT-NOISE-TIMIT corpus consists of 600 hours of noisy speech sequences designed to enable a thorough evaluation of voice activity detection (VAD) algorithms across a wide variety of common background noise scenarios. In order to construct the final mixed-speech database, a collection of over 10 hours of background noise was conducted across 10 unique locations covering 5 common noise scenarios, to create the QUT-NOISE corpus. This background noise corpus was then mixed with speech events chosen from the TIMIT clean speech corpus over a wide variety of noise lengths, signal-to-noise ratios (SNRs) and active speech proportions to form the mixed-speech QUT-NOISE-TIMIT corpus. The evaluation of five baseline VAD systems on the QUT-NOISE-TIMIT corpus is conducted to validate the data and show that the variety of noise available will allow for better evaluation of VAD systems than existing approaches in the literature.

Bottlenecks detection of track allocation schemes at rail stations by Petri nets

Robustness of the track allocation problem is rarely addressed in literatures and the obtained track allocation schemes (TAS) embody some bottlenecks. Therefore, an approach to detect bottlenecks is needed to support local optimization. First a TAS is transformed to an executable model by Petri nets. Then disturbances analysis is performed using the model and the indicators of the total trains' departure delays are collected to detect bottlenecks when each train suffers a disturbance. Finally, the results of the tests based on a rail hub linking six lines and a TAS about thirty minutes show that the minimum buffer time is 21 seconds and there are two bottlenecks where the buffer times are 57 and 44 seconds respectively, and it indicates that the bottlenecks do not certainly locate at the area where there is minimum buffer time. The proposed approach can further support selection of multi schemes and robustness optimization.

A fiber Bragg grating sensor system for train axle counting

Railway signaling facilitates two main functions, namely, train detection and train control, in order to maintain safe separations among the trains. Track circuits are the most commonly used train detection means with the simple open/close circuit principles; and subsequent adoption of axle counters further allows the detection of trains under adverse track conditions. However, with electrification and power electronics traction drive systems, aggravated by the electromagnetic interference in the vicinity of the signaling system, railway engineers often find unstable or even faulty operations of track circuits and axle counting systems, which inevitably jeopardizes the safe operation of trains. A new means of train detection, which is completely free from electromagnetic interference, is therefore required for the modern railway signaling system. This paper presents a novel optical fiber sensor signaling system. The sensor operation, field setup, axle detection solution set, and test results of an installation in a trial system on a busy suburban railway line are given.

BLAST Atlas : a function based multiple genome browser

BLAST Atlas is a visual analysis system for comparative genomics that supports genome-wide gene characterisation, functional assignment and function-based browsing of one or more chromosomes. Inspired by applications such as the WorldWide Telescope, Bing Maps 3D and Google Earth, BLAST Atlas uses novel three-dimensional gene and function views that provide a highly interactive and intuitive way for scientists to navigate, query and compare gene annotations. The system can be used for gene identification and functional assignment or as a function-based multiple genome comparison tool which complements existing position based comparison and alignment viewers.

Signature analysis on wheel-rail interaction for rail defect detection

Fibre Bragg Grating (FBG) sensors have been installed along an existing line for the purposes of train detection and weight measurement. The results show fair accuracy and high resolution on the vertical force acted on track when the train wheels are rolling upon. While the sensors are already in place and data is available, further applications beyond train detection are explored. This study presents the analysis on the unique signatures from the data collected to characterise wheel-rail interaction for rail defect detection. Focus of this first stage of work is placed on the repeatability of signals from the same wheel-rail interactions while the rail is in healthy state. Discussions on the preliminary results and hence the feasibility of this condition monitoring application, as well as technical issues to be addressed in practice, are given.

The application of profluorescent nitroxides to detect reactive oxygen species derived from combustion-generated particulate matter: Cigarette smoke – a case study

Reactive oxygen species (ROS) and related free radicals are considered to be key factors underpinning the various adverse health effects associated with exposure to ambient particulate matter. Therefore, measurement of ROS is a crucial factor for assessing the potential toxicity of particles. In this work, a novel profluorescent nitroxide, BPEAnit, was investigated as a probe for detecting particle-derived ROS. BPEAnit has a very low fluorescence emission due to inherent quenching by the nitroxide group, but upon radical trapping or redox activity, a strong fluorescence is observed. BPEAnit was tested for detection of ROS present in mainstream and sidestream cigarette smoke. In the case of mainstream cigarette smoke, there was a linear increase in fluorescence intensity with an increasing number of cigarette puffs, equivalent to an average of 101 nmol ROS per cigarette based on the number of moles of the probe reacted. Sidestream cigarette smoke sampled from an environmental chamber exposed BPEAnit to much lower concentrations of particles, but still resulted in a clearly detectible increase in fluorescence intensity with sampling time. It was calculated that the amount of ROS was equivalent to 50 ± 2 nmol per mg of particulate matter; however, this value decreased with ageing of the particles in the chamber. Overall, BPEAnit was shown to provide a sensitive response related to the oxidative capacity of the particulate matter. These findings present a good basis for employing the new BPEAnit probe for the investigation of particle-related ROS generated from cigarette smoke as well as from other combustion sources.

Oxidative potential of logwood and pellet burning particles assessed by a novel profluorescent nitroxide probe

This study reports the potential toxicological impact of particles produced during biomass combustion by an automatic pellet boiler and a traditional logwood stove under various combustion conditions using a novel profluorescent nitroxide probe BPEAnit. This probe is weakly fluorescent, but yields strong fluorescence emission upon radical trapping or redox activity. Samples were collected by bubbling aerosol through an impinger containing BPEAnit solution, followed by fluorescence measurement. The fluorescence of BPEAnit was measured for particles produced during various combustion phases, at the beginning of burning (cold start), stable combustion after refilling with the fuel (warm start) and poor burning conditions. For particles produced by the logwood stove under cold-start conditions significantly higher amounts of reactive species per unit of particulate mass were observed compared to emissions produced during a warm start. In addition, sampling of logwood burning emissions after passing through a thermodenuder at 250oC resulted in an 80-100% reduction of the fluorescence signal of BPEAnit probe, indicating that the majority of reactive species were semivolatile. Moreover, the amount of reactive species showed a strong correlation with the amount of particulate organic material. This indicates the importance of semivolatile organics in particle-related toxicity. Particle emissions from the pellet boiler, although of similar mass concentration, were not observed to lead to an increase in fluorescence signal during any of the combustion phases.

Clone Detection in Repositories of Business Process Models

Business process model repositories capture precious knowledge about an organization or a business domain. In many cases, these repositories contain hundreds or even thousands of models and they represent several man-years of effort. Over time, process model repositories tend to accumulate duplicate fragments, as new process models are created by copying and merging fragments from other models. This calls for methods to detect duplicate fragments in process models that can be refactored as separate subprocesses in order to increase readability and maintainability. This paper presents an indexing structure to support the fast detection of clones in large process model repositories. Experiments show that the algorithm scales to repositories with hundreds of models. The experimental results also show that a significant number of non-trivial clones can be found in process model repositories taken from industrial practice.