An egg apparatus-specific enhancer of Arabidopsis, identified by enhancer detection

Despite a central role in angiosperm reproduction, few gametophyte-specific genes and promoters have been isolated, particularly for the inaccessible female gametophyte (embryo sac). Using the Ds-based enhancer-detector line ET253, we have cloned an egg apparatus-specific enhancer (EASE) from Arabidopsis (Arabidopsis thaliana). The genomic region flanking the Ds insertion site was further analyzed by examining its capability to control gusA and GFP reporter gene expression in the embryo sac in a transgenic context. Through analysis of a 5' and 3' deletion series in transgenic Arabidopsis, the sequence responsible for egg apparatus-specific expression was delineated to 77 bp. Our data showed that this enhancer is unique in the Arabidopsis genome, is conserved among different accessions, and shows an unusual pattern of sequence variation. This EASE works independently of position and orientation in Arabidopsis but is probably not associated with any nearby gene, suggesting either that it acts over a large distance or that a cryptic element was detected. Embryo-specific ablation in Arabidopsis was achieved by transactivation of a diphtheria toxin gene under the control of the EASE. The potential application of the EASE element and similar control elements as part of an open-source biotechnology toolkit for apomixis is discussed.

Tactical driver lane change model using forward search

This paper describes the development and evaluation of a tactical lane change model using the forward search algorithm, for use in a traffic simulator. The tactical lane change model constructs a set of possible choices of near-term maneuver sequences available to the driver and selects the lane change action at the present time to realize the best maneuver plan. Including near term maneuver planning in the driver behavior model can allow a better representation of the complex interactions in situations such as a weaving section and high-occupancy vehicle (HOV) lane systems where drivers must weave across several lanes in order to access the HOV lanes. To support the investigation, a longitudinal control model and a basic lane change model were also analyzed. The basic lane change model is similar to those used by today's commonly-used traffic simulators. Parameters in all models were best-fit estimated for selected vehicles from a real-world freeway vehicle trajectory data set. The best-fit estimation procedure minimizes the discrepancy between the model vehicle and real vehicle's trajectories. With the best fit parameters, the proposed tactical lane change model gave a better overall performance for a greater number of cases than the basic lane change model.

Wheat Production Systems And Global Climate Change

About this book: Over 100 authors present 25 contributions on the impacts of global change on terrestrial ecosystems including:key processes of the earth system such as the CO2 fertilization effect, shifts in disturbances and biome distribution, the saturation of the terrestrial carbon sink, and changes in functional biodiversity,ecosystem services such the production of wheat, pest control, and carbon storage in croplands, and sensitive regions in the world threaten by rapid changes in climate and land use such as high latitudes ecosystems, tropical forest in Southeast Asia, and ecosystems dominated by Monsoon climate.The book also explores new research developments on spatial thresholds and nonlinearities, the key role of urban development in global biogeochemical processes, and the integration of natural and social sciences to address complex problems of the human-environment system.

Wide-baseline keypoint detection and matching with wide-angle images for vision based localisation

This thesis addresses the problem of detecting and describing the same scene points in different wide-angle images taken by the same camera at different viewpoints. This is a core competency of many vision-based localisation tasks including visual odometry and visual place recognition. Wide-angle cameras have a large field of view that can exceed a full hemisphere, and the images they produce contain severe radial distortion. When compared to traditional narrow field of view perspective cameras, more accurate estimates of camera egomotion can be found using the images obtained with wide-angle cameras. The ability to accurately estimate camera egomotion is a fundamental primitive of visual odometry, and this is one of the reasons for the increased popularity in the use of wide-angle cameras for this task. Their large field of view also enables them to capture images of the same regions in a scene taken at very different viewpoints, and this makes them suited for visual place recognition. However, the ability to estimate the camera egomotion and recognise the same scene in two different images is dependent on the ability to reliably detect and describe the same scene points, or ‘keypoints’, in the images. Most algorithms used for this purpose are designed almost exclusively for perspective images. Applying algorithms designed for perspective images directly to wide-angle images is problematic as no account is made for the image distortion. The primary contribution of this thesis is the development of two novel keypoint detectors, and a method of keypoint description, designed for wide-angle images. Both reformulate the Scale- Invariant Feature Transform (SIFT) as an image processing operation on the sphere. As the image captured by any central projection wide-angle camera can be mapped to the sphere, applying these variants to an image on the sphere enables keypoints to be detected in a manner that is invariant to image distortion. Each of the variants is required to find the scale-space representation of an image on the sphere, and they differ in the approaches they used to do this. Extensive experiments using real and synthetically generated wide-angle images are used to validate the two new keypoint detectors and the method of keypoint description. The best of these two new keypoint detectors is applied to vision based localisation tasks including visual odometry and visual place recognition using outdoor wide-angle image sequences. As part of this work, the effect of keypoint coordinate selection on the accuracy of egomotion estimates using the Direct Linear Transform (DLT) is investigated, and a simple weighting scheme is proposed which attempts to account for the uncertainty of keypoint positions during detection. A word reliability metric is also developed for use within a visual ‘bag of words’ approach to place recognition.

Human and bovine adenoviruses for the detection of source-specific fecal pollution in coastal waters in Australia

In this study, the host-specificity and -sensitivity of human- and bovine-specific adenoviruses (HS-AVs and BS-AVs) were evaluated by testing wastewater/fecal samples from various animal species in Southeast, Queensland, Australia. The overall specificity and sensitivity of the HS-AVs marker were 1.0 and 0.78, respectively. These figures for the BS-AVs were 1.0 and 0.73, respectively. Twenty environmental water samples were colleted during wet conditions and 20 samples were colleted during dry conditions from the Maroochy Coastal River and tested for the presence of fecal indicator bacteria (FIB), host-specific viral markers, zoonotic bacterial and protozoan pathogens using PCR/qPCR. The concentrations of FIB in water samples collected after wet conditions were generally higher compared to dry conditions. HS-AVs was detected in 20% water samples colleted during wet conditions and whereas BS-AVs was detected in both wet (i.e., 10%) and dry (i.e., 10%) conditions. Both, C. jejuni mapA and Salmonella invA genes were detected in 10% and 10% of samples, respectively collected during dry conditions. The concentrations of Salmonella invA ranged between 3.5 × 102 to 4.3 × 102 genomic copies per 500 ml of water G. lamblia β-giardin gene was detected only in one sample (5%) collected during the dry conditions. Weak or significant correlations were observed between FIB with viral markers and zoonotic pathogens. However, during dry conditions, no significant correlations were observed between FIB concentrations with viral markers and zoonotic pathogens. The prevalence of HS-AVs in samples collected from the study river suggests that the quality of water is affected by human fecal pollution and as well as bovine fecal pollution. The results suggest that HS-AVs and BS-AVs detection using PCR could be a useful tool for the identification of human sourced fecal pollution in coastal waters.

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.

Deriving grassland management factors for a carbon accounting method developed by the intergovernmental panel on climate change

Grassland management affects soil organic carbon (SOC) storage and can be used to mitigate greenhouse gas emissions. However, for a country to assess emission reductions due to grassland management, there must be an inventory method for estimating the change in SOC storage. The Intergovernmental Panel on Climate Change (IPCC) has developed a simple carbon accounting approach for this purpose, and here we derive new grassland management factors that represent the effect of changing management on carbon storage for this method. Our literature search identified 49 studies dealing with effects of management practices that either degraded or improved conditions relative to nominally managed grasslands. On average, degradation reduced SOC storage to 95% +/- 0.06 and 97% +/- 0.05 of carbon stored under nominal conditions in temperate and tropical regions, respectively. In contrast, improving grasslands with a single management activity enhanced SOC storage by 14% 0.06 and 17% +/- 0.05 in temperate and tropical regions, respectively, and with an additional improvement(s), storage increased by another 11% +/- 0.04. We applied the newly derived factor coefficients to analyze C sequestration potential for managed grasslands in the U.S., and found that over a 20-year period changing management could sequester from 5 to 142 Tg C yr(-1) or 0.1 to 0.9 Mg C ha(-1) yr(-1), depending on the level of change. This analysis provides revised factor coefficients for the IPCC method that can be used to estimate impacts of management; it also provides a methodological framework for countries to derive factor coefficients specific to conditions in their region.

Spatial variability of soil organic carbon in grasslands: implications for detecting change at different scales

Extensive data used to quantify broad soil C changes (without information about causation), coupled with intensive data used for attribution of changes to specific management practices, could form the basis of an efficient national grassland soil C monitoring network. Based on variability of extensive (USDA/NRCS pedon database) and intensive field-level soil C data, we evaluated the efficacy of future sample collection to detect changes in soil C in grasslands. Potential soil C changes at a range of spatial scales related to changes in grassland management can be verified (alpha=0.1) after 5 years with collection of 34, 224, 501 samples at the county, state, or national scales, respectively. Farm-level analysis indicates that equivalent numbers of cores and distinct groups of cores (microplots) results in lowest soil C coefficients of variation for a variety of ecosystems. Our results suggest that grassland soil C changes can be precisely quantified using current technology at scales ranging from farms to the entire nation. (C) 2001 Elsevier Science Ltd. All rights reserved.

Assessing the vulnerability of eco-environmental health to climate change

There is an urgent need to assess the vulnerability of eco-environmental health to climate change. This paper aims to provide an overview of current research, to identify knowledge gaps, and to propose future research needs in this challenging area. Evidence shows that climate change is affecting and will, in the future, have more (mostly adverse) impacts on ecosystems. Ecosystem degradation, particularly the decline of the life support systems, will undoubtedly affect human health and wellbeing. Therefore, it is important to develop a framework to assess the vulnerability of eco-environmental health to climate change, and to identify appropriate adaptation strategies to minimize the impact of climate change.

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.

Beyond a battery hen model? : a computer laboratory, micropolitics and educational change

This paper investigates what happened in one Australian primary school as part of the establishment, use and development of a computer laboratory over a period of two years. As part of a school renewal project, the computer lab was introduced as an ‘innovative’ way to improve the skills of teachers and children in information and communication technologies (ICT) and to lead to curriculum change. However, the way in which the lab was conceptualised and used worked against achieving these goals. The micropolitics of educational change and an input-output understanding of computers meant that change remained structural rather pedagogical or philosophical.

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.