Hand, foot and mouth disease in China: Evaluating an automated system for the detection of outbreaks

Objective To evaluate the performance of China’s infectious disease automated alert and response system in the detection of outbreaks of hand, foot and mouth (HFM) disease. Methods We estimated size, duration and delay in reporting HFM disease outbreaks from cases notified between 1 May 2008 and 30 April 2010 and between 1 May 2010 and 30 April 2012, before and after automatic alert and response included HFM disease. Sensitivity, specificity and timeliness of detection of aberrations in the incidence of HFM disease outbreaks were estimated by comparing automated detections to observations of public health staff. Findings The alert and response system recorded 106 005 aberrations in the incidence of HFM disease between 1 May 2010 and 30 April 2012 – a mean of 5.6 aberrations per 100 days in each county that reported HFM disease. The response system had a sensitivity of 92.7% and a specificity of 95.0%. The mean delay between the reporting of the first case of an outbreak and detection of that outbreak by the response system was 2.1 days. Between the first and second study periods, the mean size of an HFM disease outbreak decreased from 19.4 to 15.8 cases and the mean interval between the onset and initial reporting of such an outbreak to the public health emergency reporting system decreased from 10.0 to 9.1 days. Conclusion The automated alert and response system shows good sensitivity in the detection of HFM disease outbreaks and appears to be relatively rapid. Continued use of this system should allow more effective prevention and limitation of such outbreaks in China.

A nationwide web-based automated system for early outbreak detection and rapid response in China

Timely reporting, effective analyses and rapid distribution of surveillance data can assist in detecting the aberration of disease occurrence and further facilitate a timely response. In China, a new nationwide web-based automated system for outbreak detection and rapid response was developed in 2008. The China Infectious Disease Automated-alert and Response System (CIDARS) was developed by the Chinese Center for Disease Control and Prevention based on the surveillance data from the existing electronic National Notifiable Infectious Diseases Reporting Information System (NIDRIS) started in 2004. NIDRIS greatly improved the timeliness and completeness of data reporting with real time reporting information via the Internet. CIDARS further facilitates the data analysis, aberration detection, signal dissemination, signal response and information communication needed by public health departments across the country. In CIDARS, three aberration detection methods are used to detect the unusual occurrence of 28 notifiable infectious diseases at the county level and to transmit that information either in real-time or on a daily basis. The Internet, computers and mobile phones are used to accomplish rapid signal generation and dissemination, timely reporting and reviewing of the signal response results. CIDARS has been used nationwide since 2008; all Centers for Disease Control and Prevention (CDC) in China at the county, prefecture, provincial and national levels are involved in the system. It assists with early outbreak detection at the local level and prompts reporting of unusual disease occurrences or potential outbreaks to CDCs throughout the country.

Effect of nitrification inhibitors (DMPP and 3MP+ TZ) on soil nitrous oxide emissions from a sub-tropical vegetable production system in Queensland, Australia

The use of nitrification inhibitors, in combination with ammonium based fertilisers, has been promoted recently as an effective method to reduce nitrous oxide (N2O) emissions from fertilised agricultural fields, whilst increasing yield and nitrogen use efficiency. Vegetable cropping systems are often characterised by high inputs of nitrogen fertiliser and consequently elevated emissions of nitrous oxide (N2O) can be expected. However, to date only limited data is available on the use of nitrification inhibitors in sub-tropical vegetable systems. A field experiment investigated the effect of the nitrification inhibitors (DMPP & 3MP+TZ) on N2O emissions and yield from a typical vegetable production system in sub-tropical Australia. Soil N2O fluxes were monitored continuously over an entire year with a fully automated system. Measurements were taken from three subplots for each treatment within a randomized complete blocks design. There was a significant inhibition effect of DMPP and 3MP+TZ on N2O emissions and soil mineral N content directly following the application of the fertiliser over the vegetable cropping phase. However this mitigation was offset by elevated N2O emissions from the inhibitor treatments over the post-harvest fallow period. Cumulative annual N2O emissions amounted to 1.22 kg-N/ha, 1.16 kg-N/ha, 1.50 kg-N/ha and 0.86 kg-N/ha in the conventional fertiliser (CONV), the DMPP treatment, the 3MP+TZ treatment and the zero fertiliser (0N) respectively. Corresponding fertiliser induced emission factors (EFs) were low with only 0.09 - 0.20% of the total applied fertiliser lost as N2O. There was no significant effect of the nitrification inhibitors on yield compared to the CONV treatment for the three vegetable crops (green beans, broccoli, lettuce) grown over the experimental period. This study highlights that N2O emissions from such vegetable cropping system are primarily controlled by post-harvest emissions following the incorporation of vegetable crop residues into the soil. It also shows that the use of nitrification inhibitors can lead to elevated N2O emissions by storing N in the soil profile that is available to soil microbes during the decomposition of the vegetable residues over the post-harvest phase. Hence the use of nitrification inhibitors in vegetable systems has to be treated carefully and fertiliser rates need to be adjusted to avoid excess soil nitrogen during the postharvest phase.

Automating human thought processes for a UAV forced landing

This paper describes the current status of a program to develop an automated forced landing system for a fixed-wing Unmanned Aerial Vehicle (UAV). This automated system seeks to emulate human pilot thought processes when planning for and conducting an engine-off emergency landing. Firstly, a path planning algorithm that extends Dubins curves to 3D space is presented. This planning element is then combined with a nonlinear guidance and control logic, and simulated test results demonstrate the robustness of this approach to strong winds during a glided descent. The average path deviation errors incurred are comparable to or even better than that of manned, powered aircraft. Secondly, a study into suitable multi-criteria decision making approaches and the problems that confront the decision-maker is presented. From this study, it is believed that decision processes that utilize human expert knowledge and fuzzy logic reasoning are most suited to the problem at hand, and further investigations will be conducted to identify the particular technique/s to be implemented in simulations and field tests. The automated UAV forced landing approach presented in this paper is promising, and will allow the progression of this technology from the development and simulation stages through to a prototype system

Force-controlled automatic microassembly of tissue engineering scaffolds

This paper presents an automated system for 3D assembly of tissue engineering (TE) scaffolds made from biocompatible microscopic building blocks with relatively large fabrication error. It focuses on the pin-into-hole force control developed for this demanding microassembly task. A beam-like gripper with integrated force sensing at a 3 mN resolution with a 500 mN measuring range is designed, and is used to implement an admittance force-controlled insertion using commercial precision stages. Visual-based alignment followed by an insertion is complemented by a haptic exploration strategy using force and position information. The system demonstrates fully automated construction of TE scaffolds with 50 microparts whose dimension error is larger than 5%.

Nitrous oxide emissions from irrigated wheat in Australia : impact of irrigation management

Background and Aims: Irrigation management affects soil water dynamics as well as the soil microbial carbon and nitrogen turnover and potentially the biosphere-atmosphere exchange of greenhouse gasses (GHG). We present a study on the effect of three irrigation treatments on the emissions of nitrous oxide (N2O) from irrigated wheat on black vertisols in South-Eastern Queensland, Australia. Methods: Soil N2O fluxes from wheat were monitored over one season with a fully automated system that measured emissions on a sub-daily basis. Measurements were taken from 3 subplots for each treatment within a randomized split-plot design. Results: Highest N2O emissions occurred after rainfall or irrigation and the amount of irrigation water applied was found to influence the magnitude of these “emission pulses”. Daily N2O emissions varied from -0.74 to 20.46 g N2O-N ha-1 day-1 resulting in seasonal losses ranging from 0.43 to 0.75 kg N2O N ha-1 season -1 for the different irrigation treatments. Emission factors (EF = proportion of N fertilizer emitted as N2O) over the wheat cropping season, uncorrected for background emissions, ranged from 0.2 to 0.4% of total N applied for the different treatments. Highest seasonal N2O emissions were observed in the treatment with the highest irrigation intensity; however, the N2O intensity (N2O emission per crop yield) was highest in the treatment with the lowest irrigation intensity. Conclusions: Our data suggest that timing and amount of irrigation can effectively be used to reduce N2O losses from irrigated agricultural systems; however, in order to develop sustainable mitigation strategies the N2O intensity of a cropping system is an important concept that needs to be taken into account.

Validity of the computer science and applications (CSA) activity monitor in children

Purpose The purpose of this study was to evaluate the validity of the CSA activity monitor as a measure of children's physical activity using energy expenditure (EE) as a criterion measure. Methods Thirty subjects aged 10 to 14 performed three 5-min treadmill bouts at 3, 4, and 6 mph, respectively. While on the treadmill, subjects wore CSA (WAM 7164) activity monitors on the right and left hips. (V) over dot O-2 was monitored continuously by an automated system. EE was determined by multiplying the average (V) over dot O-2 by the caloric equivalent of the mean respiratory exchange ratio. Results Repeated measures ANOVA indicated that both CSA monitors were sensitive to changes in treadmill speed. Mean activity counts from each CSA unit were not significantly different and the intraclass reliability coefficient for the two CSA units across all speeds was 0.87. Activity counts from both CSA units were strongly correlated with EE (r = 0.86 and 0.87, P < 0.001). An EE prediction equation was developed from 20 randomly selected subjects and cross-validated on the remaining 10. The equation predicted mean EE within 0.01 kcal.min(-1). The correlation between actual and predicted values was 0.93 (P < 0.01) and the SEE was 0.93 kcal.min(-1). Conclusion These data indicate that the CSA monitor is a valid and reliable tool for quantifying treadmill walking and running in children.

Text mining for screening efficiency? Testing within a Cochrane public health review

Background The requirement for dual screening of titles and abstracts to select papers to examine in full text can create a huge workload, not least when the topic is complex and a broad search strategy is required, resulting in a large number of results. An automated system to reduce this burden, while still assuring high accuracy, has the potential to provide huge efficiency savings within the review process. Objectives To undertake a direct comparison of manual screening with a semi‐automated process (priority screening) using a machine classifier. The research is being carried out as part of the current update of a population‐level public health review. Methods Authors have hand selected studies for the review update, in duplicate, using the standard Cochrane Handbook methodology. A retrospective analysis, simulating a quasi‐‘active learning’ process (whereby a classifier is repeatedly trained based on ‘manually’ labelled data) will be completed, using different starting parameters. Tests will be carried out to see how far different training sets, and the size of the training set, affect the classification performance; i.e. what percentage of papers would need to be manually screened to locate 100% of those papers included as a result of the traditional manual method. Results From a search retrieval set of 9555 papers, authors excluded 9494 papers at title/abstract and 52 at full text, leaving 9 papers for inclusion in the review update. The ability of the machine classifier to reduce the percentage of papers that need to be manually screened to identify all the included studies, under different training conditions, will be reported. Conclusions The findings of this study will be presented along with an estimate of any efficiency gains for the author team if the screening process can be semi‐automated using text mining methodology, along with a discussion of the implications for text mining in screening papers within complex health reviews.

Quantitative genetic modeling of lateral ventricular shape and volume using multi-atlas fluid image alignment in twins

Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.

Mapping genetic influences on ventricular structure in twins

Despite substantial progress in measuring the anatomical and functional variability of the human brain, little is known about the genetic and environmental causes of these variations. Here we developed an automated system to visualize genetic and environmental effects on brain structure in large brain MRI databases. We applied our multi-template segmentation approach termed "Multi-Atlas Fluid Image Alignment" to fluidly propagate hand-labeled parameterized surface meshes, labeling the lateral ventricles, in 3D volumetric MRI scans of 76 identical (monozygotic, MZ) twins (38 pairs; mean age = 24.6 (SD = 1.7)); and 56 same-sex fraternal (dizygotic, DZ) twins (28 pairs; mean age = 23.0 (SD = 1.8)), scanned as part of a 5-year research study that will eventually study over 1000 subjects. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps, derived from path analysis, revealed patterns of heritability, and their significance, in 3D. Path coefficients for the 'ACE' model that best fitted the data indicated significant contributions from genetic factors (A = 7.3%), common environment (C = 38.9%) and unique environment (E = 53.8%) to lateral ventricular volume. Earlier-maturing occipital horn regions may also be more genetically influenced than later-maturing frontal regions. Maps visualized spatially-varying profiles of environmental versus genetic influences. The approach shows promise for automatically measuring gene-environment effects in large image databases.

Validating a novel, low cost, automated malnutrition screening system as a predictor of nutritional risk in the Oncology Day Care Unit

Background Cancer-related malnutrition is associated with increased morbidity, poorer tolerance of treatment, decreased quality of life, increased hospital admissions, and increased health care costs (Isenring et al., 2013). This study’s aim was to determine whether a novel, automated screening system was a useful tool for nutrition screening when compared against a full nutrition assessment using the Patient-Generated Subjective Global Assessment (PG-SGA) tool. Methods A single site, observational, cross-sectional study was conducted in an outpatient oncology day care unit within a Queensland tertiary facility, with three hundred outpatients (51.7% male, mean age 58.6 ± 13.3 years). Eligibility criteria: ≥18 years, receiving anticancer treatment, able to provide written consent. Patients completed the Malnutrition Screening Tool (MST). Nutritional status was assessed using the PG-SGA. Data for the automated screening system was extracted from the pharmacy software program Charm. This included body mass index (BMI) and weight records dating back up to six months. Results The prevalence of malnutrition was 17%. Any weight loss over three to six weeks prior to the most recent weight record as identified by the automated screening system relative to malnutrition resulted in 56.52% sensitivity, 35.43% specificity, 13.68% positive predictive value, 81.82% negative predictive value. MST score 2 or greater was a stronger predictor of nutritional risk relative to PG-SGA classified malnutrition (70.59% sensitivity, 69.48% specificity, 32.14% positive predictive value, 92.02% negative predictive value). Conclusions Both the automated screening system and the MST fell short of the accepted professional standard for sensitivity (80%) or specificity (60%) when compared to the PG-SGA. However, although the MST remains a better predictor of malnutrition in this setting, uptake of this tool in the Oncology Day Care Unit remains challenging.

Virtual fencing applications : Implementing and testing an automated cattle control system

Managing livestock movement in extensive systems has environmental and production benefits. Currently permanent wire fencing is used to control cattle; this is both expensive and inflexible. Cattle are known to respond to auditory and visual cues and we investigated whether these can be used to manipulate their behaviour. Twenty-five Belmont Red steers with a mean live weight of 270kg were each randomly assigned to one of five treatments. Treatments consisted of a combination of cues (audio, tactile and visual stimuli) and consequence (electrical stimulation). The treatments were electrical stimulation alone, audio plus electrical stimulation, vibration plus electrical stimulation, light plus electrical stimulation and electrified electric fence (6kV) plus electrical stimulation. Cue stimuli were administered for 3s followed immediately by electrical stimulation (consequence) of 1kV for 1s. The experiment tested the operational efficacy of an on-animal control or virtual fencing system. A collar-halter device was designed to carry the electronics, batteries and equipment providing the stimuli, including audio, vibration, light and electrical of a prototype virtual fencing device. Cattle were allowed to travel along a 40m alley to a group of peers and feed while their rate of travel and response to the stimuli were recorded. The prototype virtual fencing system was successful in modifying the behaviour of the cattle. The rate of travel of cattle along the alley demonstrated the large variability in behavioural response associated with tactile, visual and audible cues. The experiment demonstrated virtual fencing has potential for controlling cattle in extensive grazing systems. However, larger numbers of cattle need to be tested to derive a better understanding of the behavioural variance. Further controlled experimental work is also necessary to quantify the interaction between cues, consequences and cattle learning.

Changing user behaviour using a digital repository system

Griffith University is developing a digital repository system using HarvestRoad Hive software to better meet the needs of academics and students using institutional learning and teaching, course readings, and institutional intellectual capital systems. Issues with current operations and systems are discussed in terms of user behaviour. New repository systems are being designed in such a way that they address current service and user behaviour issues by closely aligning systems with user needs. By developing attractive online services, Griffith is working to change current user behaviour to achieve strategic priorities in the sharing and reuse of learning objects, improved selection and use of digitised course readings, the development of ePrint and eScience services, and the management of a research portfolio service.

An expressed sequence tag (EST) library for Drosophila serrata, a model system for sexual selection and climatic adaptation studies

The native Australian fly Drosophila serrata belongs to the highly speciose montium subgroup of the melanogaster species group. It has recently emerged as an excellent model system with which to address a number of important questions, including the evolution of traits under sexual selection and traits involved in climatic adaptation along latitudinal gradients. Understanding the molecular genetic basis of such traits has been limited by a lack of genomic resources for this species. Here, we present the first expressed sequence tag (EST) collection for D. serrata that will enable the identification of genes underlying sexually-selected phenotypes and physiological responses to environmental change and may help resolve controversial phylogenetic relationships within the montium subgroup.