Direct and indirect effects of egg parasitism by Neopolyscystus Girault sp. (Hymenoptera: Pteromalidae) on Paropsis atomaria Olivier (Coleoptera: Chrysomelidae)

Abstract Neopolycystus sp. is the only primary egg parasitoid associated with the pest beetle Paropsis atomaria in subtropical eucalypt plantations, but its impact on its host populations is unknown. The simplified ecosystem represented by the plantation habitat, lack of interspecific competition for host and parasitoid, and the multivoltinism of the host population makes this an ideal system for quantifying the direct and indirect effects of egg parasitism, and hence, effects on host population dynamics. Within-, between- and overall-egg-batch parasitism rates were determined at three field sites over two field seasons, and up to seven host generations. The effect of exposure time (egg batch age), host density proximity to native forest and water sources on egg parasitism rates was also tested. Neopolycystus sp. exerts a significant influence on P. atomaria populations in Eucalyptus cloeziana. plantations in south-eastern Queensland, causing the direct (13%) and indirect (15%) mortality of almost one-third of all eggs in the field. Across seasons and generations, 45% of egg batches were parasitised, with a within-batch parasitism rate of around 30%. Between-batch parasitism increased up to 5–6 days after oviposition in the field, although within-batch parasitism rates generally did not. However, there were few apparent patterns to egg parasitism, with rates often varying significantly between sites and seasons.

Thermal requirements, field mortality and population phenology modelling of Paropsis atomaria Olivier, an emergent pest in subtropical hardwood plantations

Paropsis atomaria is a recently emerged pest of eucalypt plantations in subtropical Australia. Its broad host range of at least 20 eucalypt species and wide geographical distribution provides it the potential to become a serious forestry pest both within Australia and, if accidentally introduced, overseas. Although populations of P. atomaria are genetically similar throughout its range, population dynamics differ between regions. Here, we determine temperature-dependent developmental requirements using beetles sourced from temperate and subtropical zones by calculating lower temperature thresholds, temperature-induced mortality, and day-degree requirements. We combine these data with field mortality estimates of immature life stages to produce a cohort-based model, ParopSys, using DYMEX™ that accurately predicts the timing, duration, and relative abundance of life stages in the field and number of generations in a spring–autumn (September–May) field season. Voltinism was identified as a seasonally plastic trait dependent upon environmental conditions, with two generations observed and predicted in the Australian Capital Territory, and up to four in Queensland. Lower temperature thresholds for development ranged between 4 and 9 °C, and overall development rates did not differ according to beetle origin. Total immature development time (egg–adult) was approximately 769.2 ± S.E. 127.8 DD above a lower temperature threshold of 6.4 ± S.E. 2.6 °C. ParopSys provides a basic tool enabling forest managers to use the number of generations and seasonal fluctuations in abundance of damaging life stages to estimate the pest risk of P. atomaria prior to plantation establishment, and predict the occurrence and duration of damaging life stages in the field. Additionally, by using local climatic data the pest potential of P. atomaria can be estimated to predict the risk of it establishing if accidentally introduced overseas. Improvements to ParopSys’ capability and complexity can be made as more biological data become available.

Heparan sulfate mediates the proliferation and differentiation of rat mesenchymal stem cells

The growth and differentiation of mesenchymal stem cells is controlled by various growth factors, the activities of which can be modulated by heparan sulfates. We have previously underscored the necessity of sulfated glycosaminoglycans for the FGF-2-stimulated differentiation of osteoprogenitor cells. Here we show that exogenous application of heparan sulfate to cultures of primary rat MSCs stimulates their proliferation leading to increased expression of osteogenic markers and enhanced bone nodule formation. FGF-2 can also increase the proliferation and osteogenic differentiation of rMSCs when applied exogenously during their linear growth. However, as opposed to exogenous HS, the continuous use of FGF-2 during in vitro differentiation completely blocked rMSC mineralization. Furthermore, we show that the effects of both FGF-2 and HS are mediated through FGF receptor 1 (FGFR1) and that inhibition of signaling through this receptor arrests cell growth resulting in the cells being unable to reach the critical density necessary to induce differentiation. Interestingly, blocking FGFR1 signaling in post-confluent osteogenic cultures significantly increased calcium deposition. Taken together our data clearly suggests that FGFR1 signaling plays an important role during osteogenic differentiation, firstly by stimulating cell growth that is closely followed by an inhibitory affect once the cells have reached confluence. It also underlines the importance of HS as a co-receptor for the signaling of endogenous FGF-2 and suggests that purified glycosaminoglycans may be attractive alternatives to growth factors for improved ex vivo growth and differentiation of MSCs.

Combining electrospun scaffolds with electrosprayed hydrogels leads to three-dimensional cellularization of hybrid constructs

A common problem in the design of tissue engineered scaffolds using electrospun scaffolds is the poor cellular infiltration into the structure. To tackle this issue, three approaches to scaffold design using electrospinning were investigated: selective leaching of a water-soluble fiber phase (poly ethylene oxide (PEO) or gelatin), the use of micron-sized fibers as the scaffold, and a combination of micron-sized fibers with codeposition of a hyaluronic acid-derivative hydrogel, Heprasil. These designs were achieved by modifying a conventional electrospinning system with two charged capillaries and a rotating mandrel collector. Three types of scaffolds were fabricated: medical grade poly(epsilon-caprolactone)/collagen (mPCL/Col) cospun with PEO or gelatin, mPCL/Col meshes with micron-sized fibers, and mPCL/Col microfibers cosprayed with Heprasil. All three scaffold types supported attachment and proliferation of human fetal osteoblasts. However, selective leaching only marginally improved cellular infiltration when compared to meshes obtained by conventional electrospinning. Better cell penetration was seen in mPCL/Col microfibers, and this effect was more pronounced when Heprasil regions were present in the structure. Thus, such techniques could be further exploited for the design of cell permeable fibrous meshes for tissue engineering applications.

Robust real time multi-layer foreground segmentation

Many surveillance applications (object tracking, abandoned object detection) rely on detecting changes in a scene. Foreground segmentation is an effective way to extract the foreground from the scene, but these techniques cannot discriminate between objects that have temporarily stopped and those that are moving. We propose a series of modifications to an existing foreground segmentation system\cite{Butler2003} so that the foreground is further segmented into two or more layers. This yields an active layer of objects currently in motion and a passive layer of objects that have temporarily ceased motion which can itself be decomposed into multiple static layers. We also propose a variable threshold to cope with variable illumination, a feedback mechanism that allows an external process (i.e. surveillance system) to alter the motion detectors state, and a lighting compensation process and a shadow detector to reduce errors caused by lighting inconsistencies. The technique is demonstrated using outdoor surveillance footage, and is shown to be able to effectively deal with real world lighting conditions and overlapping objects.

Abandoned object detection using multi-layer motion detection

Abandoned object detection (AOD) systems are required to run in high traffic situations, with high levels of occlusion. Systems rely on background segmentation techniques to locate abandoned objects, by detecting areas of motion that have stopped. This is often achieved by using a medium term motion detection routine to detect long term changes in the background. When AOD systems are integrated into person tracking system, this often results in two separate motion detectors being used to handle the different requirements. We propose a motion detection system that is capable of detecting medium term motion as well as regular motion. Multiple layers of medium term (static) motion can be detected and segmented. We demonstrate the performance of this motion detection system and as part of an abandoned object detection system.

Multi-sensor tracking using a scalable condensation filter

Surveillance and tracking systems typically use a single colour modality for their input. These systems work well in controlled conditions but often fail with low lighting, shadowing, smoke, dust, unstable backgrounds or when the foreground object is of similar colouring to the background. With advances in technology and manufacturing techniques, sensors that allow us to see into the thermal infrared spectrum are becoming more affordable. By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using visible light only for surveillance and tracking. Thermal images are not affected by lighting or shadowing and are not overtly affected by smoke, dust or unstable backgrounds. We propose and evaluate three approaches for fusing visual and thermal images for person tracking. We also propose a modified condensation filter to track and aid in the fusion of the modalities. We compare the proposed fusion schemes with using the visual and thermal domains on their own, and demonstrate that significant improvements can be achieved by using multiple modalities.

Multi-spectral fusion for surveillance systems

Surveillance systems such as object tracking and abandoned object detection systems typically rely on a single modality of colour video for their input. These systems work well in controlled conditions but often fail when low lighting, shadowing, smoke, dust or unstable backgrounds are present, or when the objects of interest are a similar colour to the background. Thermal images are not affected by lighting changes or shadowing, and are not overtly affected by smoke, dust or unstable backgrounds. However, thermal images lack colour information which makes distinguishing between different people or objects of interest within the same scene difficult. ----- By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using either modality individually. We evaluate four approaches for fusing visual and thermal images for use in a person tracking system (two early fusion methods, one mid fusion and one late fusion method), in order to determine the most appropriate method for fusing multiple modalities. We also evaluate two of these approaches for use in abandoned object detection, and propose an abandoned object detection routine that utilises multiple modalities. To aid in the tracking and fusion of the modalities we propose a modified condensation filter that can dynamically change the particle count and features used according to the needs of the system. ----- We compare tracking and abandoned object detection performance for the proposed fusion schemes and the visual and thermal domains on their own. Testing is conducted using the OTCBVS database to evaluate object tracking, and data captured in-house to evaluate the abandoned object detection. Our results show that significant improvement can be achieved, and that a middle fusion scheme is most effective.

Object tracking using multiple motion modalities

This paper presents an object tracking system that utilises a hybrid multi-layer motion segmentation and optical flow algorithm. While many tracking systems seek to combine multiple modalities such as motion and depth or multiple inputs within a fusion system to improve tracking robustness, current systems have avoided the combination of motion and optical flow. This combination allows the use of multiple modes within the object detection stage. Consequently, different categories of objects, within motion or stationary, can be effectively detected utilising either optical flow, static foreground or active foreground information. The proposed system is evaluated using the ETISEO database and evaluation metrics and compared to a baseline system utilising a single mode foreground segmentation technique. Results demonstrate a significant improvement in tracking results can be made through the incorporation of the additional motion information.

Scene invariant crowd counting for real-time surveillance

Automated crowd counting allows excessive crowding to be detected immediately, without the need for constant human surveillance. Current crowd counting systems are location specific, and for these systems to function properly they must be trained on a large amount of data specific to the target location. As such, configuring multiple systems to use is a tedious and time consuming exercise. We propose a scene invariant crowd counting system which can easily be deployed at a different location to where it was trained. This is achieved using a global scaling factor to relate crowd sizes from one scene to another. We demonstrate that a crowd counting system trained at one viewpoint can achieve a correct classification rate of 90% at a different viewpoint.

Dynamic Performance Measures for Object Tracking Systems

Performance evaluation of object tracking systems is typically performed after the data has been processed, by comparing tracking results to ground truth. Whilst this approach is fine when performing offline testing, it does not allow for real-time analysis of the systems performance, which may be of use for live systems to either automatically tune the system or report reliability. In this paper, we propose three metrics that can be used to dynamically asses the performance of an object tracking system. Outputs and results from various stages in the tracking system are used to obtain measures that indicate the performance of motion segmentation, object detection and object matching. The proposed dynamic metrics are shown to accurately indicate tracking errors when visually comparing metric results to tracking output, and are shown to display similar trends to the ETISEO metrics when comparing different tracking configurations.