One-year delayed effect of fog on malaria transmission : a time-series analysis in the rain forest area of Mengla County, south-west China

Background: Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China. Methods: Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Results: At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria. Conclusion: Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide.

Pore formation during dehydration of polycrystalline gypsum observed and quantified in a time-series synchrotron radiation based X-ray micro-tomography experiment

We conducted an in-situ X-ray micro-computed tomography heating experiment at the Advanced Photon Source (USA) to dehydrate an unconfined 2.3 mm diameter cylinder of Volterra Gypsum. We used a purpose-built X-ray transparent furnace to heat the sample to 388 K for a total of 310 min to acquire a three-dimensional time-series tomography dataset comprising nine time steps. The voxel size of 2.2 μm3 proved sufficient to pinpoint reaction initiation and the organization of drainage architecture in space and time. We observed that dehydration commences across a narrow front, which propagates from the margins to the centre of the sample in more than four hours. The advance of this front can be fitted with a square-root function, implying that the initiation of the reaction in the sample can be described as a diffusion process. Novel parallelized computer codes allow quantifying the geometry of the porosity and the drainage architecture from the very large tomographic datasets (20483 voxels) in unprecedented detail. We determined position, volume, shape and orientation of each resolvable pore and tracked these properties over the duration of the experiment. We found that the pore-size distribution follows a power law. Pores tend to be anisotropic but rarely crack-shaped and have a preferred orientation, likely controlled by a pre-existing fabric in the sample. With on-going dehydration, pores coalesce into a single interconnected pore cluster that is connected to the surface of the sample cylinder and provides an effective drainage pathway. Our observations can be summarized in a model in which gypsum is stabilized by thermal expansion stresses and locally increased pore fluid pressures until the dehydration front approaches to within about 100 μm. Then, the internal stresses are released and dehydration happens efficiently, resulting in new pore space. Pressure release, the production of pores and the advance of the front are coupled in a feedback loop.

Nitrous oxide emissions from subtropical horticultural soils : a time series analysis

Time series regression models were used to examine the influence of environmental factors (soil water content and soil temperature) on the emissions of nitrous oxide (N2O) from subtropical soils, by taking into account temporal lagged environmental factors, autoregressive processes, and seasonality for three horticultural crops in a subtropical region of Australia. Fluxes of N2O, soil water content, and soil temperature were determined simultaneously on a weekly basis over a 12-month period in South East Queensland. Annual N2O emissions for soils under mango, pineapple, and custard apple were 1590, 1156, and 2038 g N2O-N/ha, respectively, with most emissions attributed to nitrification. The N2O-N emitted from the pineapple and custard apple crops was equivalent to 0.26 and 2.22%, respectively, of the applied mineral N. The change in soil water content was the key variable for describing N2O emissions at the weekly time-scale, with soil temperature at a lag of 1 month having a significant influence on average N2O emissions (averaged) at the monthly time-scale across the three crops. After accounting for soil temperature and soil water content, both the weekly and monthly time series regression models exhibited significant autocorrelation at lags of 1–2 weeks and 1–2 months, and significant seasonality for weekly N2O emissions for mango crop and for monthly N2O emissions for mango and custard apple crops in this location over this time-frame. Time series regression models can explain a higher percentage of the temporal variation of N2O emission compared with simple regression models using soil temperature and soil water content as drivers. Taking into account seasonal variability and temporal persistence in N2O emissions associated with soil water content and soil temperature may lead to a reduction in the uncertainty surrounding estimates of N2O emissions based on limited sampling effort.

Image based flow visualisation of experimental flow fields inside a gross pollutant trap

Typical flow fields in a stormwater gross pollutant trap (GPT) with blocked retaining screens were experimentally captured and visualised. Particle image velocimetry (PIV) software was used to capture the flow field data by tracking neutrally buoyant particles with a high speed camera. A technique was developed to apply the Image Based Flow Visualization (IBFV) algorithm to the experimental raw dataset generated by the PIV software. The dataset consisted of scattered 2D point velocity vectors and the IBFV visualisation facilitates flow feature characterisation within the GPT. The flow features played a pivotal role in understanding gross pollutant capture and retention within the GPT. It was found that the IBFV animations revealed otherwise unnoticed flow features and experimental artefacts. For example, a circular tracer marker in the IBFV program visually highlighted streamlines to investigate specific areas and identify the flow features within the GPT.

Realistic irrigation visualization in a surgical wound debridement simulator

Wound debridement refers to the removal of necrotic, devitalized, or contaminated tissue and/or foreign material to promote wound healing. Surgical debridement uses sharp instruments to cut dead tissue from a wound and it is the quickest and most efficient method of debridement. A wound debridement simulator [1,2] can ensure that a medical trainee is competent prior to performing a procedure on a genuine patient. Irrigation is performed at different stages of debridement in order to remove debris and reduce the bacteria count through rinsing the wound. This paper presents a novel approach for realistic irrigation visualization based on texture representations of debris. This approach applies image processing techniques to a series of images, which model the cleanliness of the wound. The active texture is generated and updated dynamically based on the irrigation state, location, and range. Presented results demonstrate that texture mapping and image processing techniques can provide effective and efficient solutions for irrigation visualization in the wound debridement simulator.

Porosity of serially sectioned interplanetary dust particles

The application of epoxy embedding and microtomy to individual chondritic interplanetary dust particles (lOP's)(Bradley and Brownlee, 1986a) provides not only higher precision in thin-film elemental analyses (Bradley and Brownlee, 19861:1), but also allows a wealth of other important techniques for the micro-characterization of these primitive extraterrestrial materials. For example, individual sections (e.g. 100 nm thick) or a series of sections, can be examined using image analysis techniques which utilize either transmitted or scanned secondary electron images, or alternatively, secondary X-ray spectra collected concurrently from a given region of sample. Individual particles, or groups of particles with similar image characteristics can then be rapidly identified using conventional grey-scale/particle recognition techniques for each microtomed section of lOP. This type of image analysis provides a suitable method for determination of particle size and shape distribution as well as porosity throughout the aggregate.

Lynch syndrome-associated breast cancers: clinicopathologic characteristics of a case series from the colon cancer family registry

Purpose: The recognition of breast cancer as a spectrum tumor in Lynch syndrome remains controversial. The aim of this study was to explore features of breast cancers arising in Lynch syndrome families. Experimental Design: This observational study involved 107 cases of breast cancer identified from the Colorectal Cancer Family Registry (Colon CFR) from 90 families in which (a) both breast and colon cancer co-occurred, (b) families met either modified Amsterdam criteria, or had at least one early-onset (<50 years) colorectal cancer, and (c) breast tissue was available within the biospecimen repository for mismatch repair (MMR) testing. Eligibility criteria for enrollment in the Colon CFR are available online. Breast cancers were reviewed by one pathologist. Tumor sections were stained for MLH1, PMS2, MSH2, and MSH6, and underwent microsatellite instability testing. Results: Breast cancer arose in 35 mutation carriers, and of these, 18 (51%) showed immunohistochemical absence of MMR protein corresponding to the MMR gene mutation segregating the family. MMR-deficient breast cancers were more likely to be poorly differentiated (P = 0.005) with a high mitotic index (P = 0.002), steroid hormone receptor–negative (estrogen receptor, P = 0.031; progesterone receptor, P = 0.022), and to have peritumoral lymphocytes (P = 0.015), confluent necrosis (P = 0.002), and growth in solid sheets (P < 0.001) similar to their colorectal counterparts. No difference in age of onset was noted between the MMR-deficient and MMR-intact groups. Conclusions: MMR deficiency was identified in 51% of breast cancers arising in known mutation carriers. Breast cancer therefore may represent a valid tissue option for the detection of MMR deficiency in which spectrum tumors are lacking

Finitude (V03)

WHAT: An interactive installation with full body interface, digital projection, multi-touch sensitive screen surfaces, interactive 3D gaming software, motorised dioramas, 4.1 spatial sound & new furniture forms - investigating the cultural dimensions of sustainability through the lens of 'time'. “Time is change, time is finitude. Humans are a finite species. Every decision we make today brings that end closer, or alternatively pushes it further away. Nothing can be neutral”. Tony Fry DETAILS: Each participant/viewer lies comfortably on their back. Directly above them is a semi-transparent Perspex screen that displays projected 3D imagery and is simultaneously sensitive to the lightest of finger touches. Depending upon the ever changing qualities of the projected image on this screen the participant can see through its surface to a series of physical dioramas suspended above, lit by subtle LED spotlighting. This diorama consists of a slowly rotating series of physical environments, which also include several animatronic components, allowing the realtime composition of whimsical ‘landscapes’ of both 'real' and 'virtual' media. Through subtle, non-didactic touch-sensitive interactivity the participant then has influence over both the 3D graphic imagery, the physical movements of the diorama and the 4 channel immersive soundscape, creating an uncanny blend of physical and virtual media. Five speakers positioned around the room deliver a rich interactive soundscape that responds both audibly and physically to interactions.

Learning hierarchical prototypes of motion time series for interactive systems

Abstract. For interactive systems, recognition, reproduction, and generalization of observed motion data are crucial for successful interaction. In this paper, we present a novel method for analysis of motion data that we refer to as K-OMM-trees. K-OMM-trees combine Ordered Means Models (OMMs) a model-based machine learning approach for time series with an hierarchical analysis technique for very large data sets, the K-tree algorithm. The proposed K-OMM-trees enable unsupervised prototype extraction of motion time series data with hierarchical data representation. After introducing the algorithmic details, we apply the proposed method to a gesture data set that includes substantial inter-class variations. Results from our studies show that K-OMM-trees are able to substantially increase the recognition performance and to learn an inherent data hierarchy with meaningful gesture abstractions.

Shift

Shift was an exhibition held in October 2008, and was the culmination of a 10 month artist in residence held at Metro Arts, Brisbane in 2008. A number of works were produced and exhibited, and were a response to the ambient urban landscape of inner city Brisbane. The research component contributes to the discussion of the form and display of digital animation, and builds upon strategies of presentation developed from series of works completed in 2005-2007 as part of an MA (research) at QUT, Brisbane. For the two week exhibition, one interactive kiosk and several large scale digital prints were produced, and also a site specific digital animation sequence was projected onto urban landscape features next to the gallery.

Order conditions of stochastic Runge-Kutta methods by B-series

In this paper, general order conditions and a global convergence proof are given for stochastic Runge Kutta methods applied to stochastic ordinary differential equations ( SODEs) of Stratonovich type. This work generalizes the ideas of B-series as applied to deterministic ordinary differential equations (ODEs) to the stochastic case and allows a completely general formalism for constructing high order stochastic methods, either explicit or implicit. Some numerical results will be given to illustrate this theory.

Image Region Salience for Improving Appearance-Based Place Recognition using a Supervised Classifier System

Many state of the art vision-based Simultaneous Localisation And Mapping (SLAM) and place recognition systems compute the salience of visual features in their environment. As computing salience can be problematic in radically changing environments new low resolution feature-less systems have been introduced, such as SeqSLAM, all of which consider the whole image. In this paper, we implement a supervised classifier system (UCS) to learn the salience of image regions for place recognition by feature-less systems. SeqSLAM only slightly benefits from the results of training, on the challenging real world Eynsham dataset, as it already appears to filter less useful regions of a panoramic image. However, when recognition is limited to specific image regions performance improves by more than an order of magnitude by utilising the learnt image region saliency. We then investigate whether the region salience generated from the Eynsham dataset generalizes to another car-based dataset using a perspective camera. The results suggest the general applicability of an image region salience mask for optimizing route-based navigation applications.

Diurnal temperature range and childhood asthma : a time-series study

BACKGROUND: Hot and cold temperatures have been associated with childhood asthma. However, the relationship between daily temperature variation and childhood asthma is not well understood. This study aimed to examine the relationship between diurnal temperature range (DTR) and childhood asthma. METHODS: A Poisson generalized linear model combined with a distributed lag non-linear model was used to examine the relationship between DTR and emergency department admissions for childhood asthma in Brisbane, from January 1st 2003 to December 31st 2009. RESULTS: There was a statistically significant relationship between DTR and childhood asthma. The DTR effect on childhood asthma increased above a DTR of 10[degree sign]C. The effect of DTR on childhood asthma was the greatest for lag 0--9 days, with a 31% (95% confidence interval: 11% -- 58%) increase of emergency department admissions per 5[degree sign]C increment of DTR. Male children and children aged 5--9 years appeared to be more vulnerable to the DTR effect than others. CONCLUSIONS: Large DTR may trigger childhood asthma. Future measures to control and prevent childhood asthma should include taking temperature variability into account. More protective measures should be taken after a day of DTR above10[degree sign]C.

Licensed to sell : product placement in the James Bond film series

As one of the longest running franchises in cinema history, and with its well-established use of product placements, the James Bond film series provides an ideal framework within which to measure and catalogue the number and types of products used within a particular timeframe. This case study will draw upon extensive content analysis of the James Bond film series in order to chart the evolution of product placement across the franchise's 50 year history.