Monitoring protected areas using remote sensing technology

Due to irrational use of natural resources, human society is facing unprecedented threats. Remote sensing is one of the essential tools to determine changes in various forms of biological diversity over time. There are many methods to determine changes in protected areas, using satellite images. In this paper after introducing different change detection methods and their advantages and disadvantages, a hybrid method is used to analyse changes in forests and protected areas in a national park. Two Landsat images of Golestan National Park in Iran (taken in 1998 and 2010) were used. This hybrid approach combines Change Vector Analysis (CVA) for flagging the occurrence of changes, followed by signature extension to assign labels to changedpixels. The main objective of this paper is to propose a method for discovering and assessing environmental threats to natural treasures.

A new perspective of storm bite on sandy beaches using unmanned aerial vehicles

Aerial imagery collected before and after major storm events is ideal for the assessment of coastal landscape change driven by individual high-magnitude events. Using traditional satellite sensors and manned aerial systems can be challenging due to issues related to cloud cover, mobilization expenses and resolution. Rapid advances in unmanned aerial vehicle (UAV) technology allow for the cost-effective collection of aerial imagery and topography at centimetre resolution suitable for assessing change in coastal ecosystems. In this study we demonstrate the utility of UAV-based photogrammetry to quantify storm-driven sediment dynamics on a sandy beach on the open-coast shoreline of Victoria, Australia. UAV-based aerial photography was collected before and after a major storm event. High-resolution (< 5 cm) aerial imagery and digital surface models were acquired and change-detection techniques were applied to quantify changes in the beachface. An average beach erosion of 12.24 m3/m with a maximum of 28.05 m3/m was observed, and the volume of sand cut from the beachface and retreat of the foredune are clearly illustrated. Following the storm event, erosion was estimated at 7259.94 ± 503.69 m3 along 550 m of beach. By combining the aerial imagery and derived topographic datasets we demonstrate the advantage of UAV-based photogrammetry techniques for rapid high-resolution data collection in semi-remote locations. Its utility in setting unlimited virtual vantage points is also illustrated and the valuable perspective it provides for tracking landscape change discussed.

An association rule analysis framework for complex physiological and genetic data

Physiological and genetic information has been critical to the successful diagnosis and prognosis of complex diseases. In this paper, we introduce a support-confidence-correlation framework to accurately discover truly meaningful and interesting association rules between complex physiological and genetic data for disease factor analysis, such as type II diabetes (T2DM). We propose a novel Multivariate and Multidimensional Association Rule mining system based on Change Detection (MMARCD). Given a complex data set u i (e.g. u 1 numerical data streams, u 2 images, u 3 videos, u 4 DNA/RNA sequences) observed at each time tick t, MMARCD incrementally finds correlations and hidden variables that summarise the key relationships across the entire system. Based upon MMARCD, we are able to construct a correlation network for human diseases. © 2012 Springer-Verlag.

Blood pressure change with weight loss is affected by diet type in men

Background: Weight loss reduces blood pressure, and the Dietary Approaches to Stop Hypertension (DASH) diet has also been shown to lower blood pressure.

Objective: Our goal was to assess the effect on blood pressure of 2 weight-reduction diets: a low-fat diet (LF diet) and a moderate-sodium, high-potassium, high-calcium, low-fat DASH diet (WELL diet).

Design: After baseline measurements, 63 men were randomly assigned to either the WELL or the LF diet for 12 wk, and both diet groups undertook 0.5 h of moderate physical activity on most days of the week.

Results: Fifty-four men completed the study. Their mean (±SD) age was 47.9 ± 9.3 y (WELL diet, n = 27; LF diet, n = 27), and their mean baseline home systolic and diastolic blood pressures were 129.4 ± 11.3 and 80.6 ± 8.6 mm Hg, respectively. Body weight decreased by 4.9 ± 0.6 kg (±SEM) in the WELL group and by 4.6 ± 0.6 kg in the LF group (P < 0.001 for both). There was a greater decrease in blood pressure in the WELL group than in the LF group [between-group difference (week 12 –baseline) in both SBP (5.5 ± 1.9 mm Hg; P = 0.006) and DBP (4.4 ± 1.2 mm Hg; P = 0.001)].

Conclusions: For a comparable 5-kg weight loss, a diet high in low-fat dairy products, vegetables, and fruit (the WELL diet) resulted in a greater decrease in blood pressure than did the LF diet. This dietary approach to achieving weight reduction may confer an additional benefit in reducing blood pressure in those who are overweight.

A video-based real-time vehicle detection method by classified background learning

A new two-level real-time vehicle detection method is proposed in order to meet the robustness and efficiency requirements of real world applications. At the high level, pixels of the background image are classified into three categories according to the characteristics of Red, Green, Blue (RGB) curves. The robustness of the classification is further enhanced by using
line detection and pattern connectivity. At the lower level, an exponential forgetting algorithm with adaptive parameters for different categories is utilised to calculate the background and reduce the distortion by the small motion of video cameras. Scene tests show that the proposed method is more robust and faster than previous methods, which is very suitable for real-time vehicle detection in outdoor environments, especially concerning locations where the level of illumination changes frequently and speed detection is important.

Depth estimation using multi-wavelet analysis based stereo vision approach

The problem of dimensional defects in aluminum die- casting is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. Due to the unpredictable factory environment and metallic, with highly reflective, nature of aluminum die-castings, it is extremely hard to estimate true dimensionality of the die-casting, autonomously. In this work, we propose a novel robust 3D reconstruction algorithm capable of reconstructing dimensionally accurate 3D depth models of the aluminum die-castings. The developed system is very simple and cost effective as it consists of only a stereo cameras pair and a simple fluorescent light. The developed system is capable of estimating surface depths within the tolerance of 1.5 mm. Moreover, the system is invariant to illuminative variations and orientation of the objects in the input image space, which makes the developed system highly robust. Due to its hardware simplicity and robustness, it can be implemented in different factory environments without a significant change in the setup.

Depth estimation using multiwavelet analysis based stereo vision approach

The problem of dimensional defects in aluminum die-casting is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. Due to the unpredictable factory environment and metallic, with highly reflective, nature of aluminum die-castings, it is extremely hard to estimate true dimensionality of the die-casting, autonomously. In this work, we propose a novel robust 3D reconstruction algorithm capable of reconstructing dimensionally accurate 3D depth models of the aluminum die-castings. The developed system is very simple and cost effective as it consists of only a stereo camera pair and a simple fluorescent light. The developed system is capable of estimating surface depths within the tolerance of 1.5 mm. Moreover, the system is invariant to illuminative variations and orientation of the objects in the input image space, which makes the developed system highly robust. Due to its hardware simplicity and robustness, it can be implemented in different factory environments without a significant change in the setup.

Absolute versus relative difference measures of priming: Which is appropriate when baseline scores change with age?

It is often of theoretical interest to know if implicit memory (repetition priming) develops across childhood under a given circumstance. Methodologically, however, it is difficult to determine whether development is present when baseline performance for unstudied items improves with age. Calculation of priming in absolute (priming=studied - unstudied) or relative-to-baseline terms can lead to different conclusions. In first noting this problem, Parkin (1993) suggested using the Snodgrass (1989a) calculation of relative priming [priming=(studied - unstudied)/(maximum - unstudied)], and most developmental studies have since adopted this procedure. Here, we question the Snodgrass method because the Snodgrass method's results are not replicated in the picture identification task when baselines are equated experimentally across age groups. Instead, results support an absolute measure of priming. Theoretically, we argue against its core assumption; namely, that children and adults always lie on the same learning curve, with an equal maximum performance level and equal rate of learning.

Weight, physical activity and dietary behavior change in young mothers : short term results of the HeLP-her cluster randomized controlled trial

Background
Preventing weight gain rather than treating established obesity is an important economic and public health response to the rapidly increasing rates of obesity worldwide. Treatment of established obesity is complex and costly requiring multiple resources. Preventing weight gain potentially requires fewer resources to reach broad population groups, yet there is little evidence for successful interventions to prevent weight gain in the community. Women with children are an important target group because of high rates of weight gain and the potential to influence the health behaviors in family members.

Methods
The aim of this cluster randomized controlled trial was to evaluate the short term effect of a community-based self-management intervention to prevent weight gain. Two hundred and fifty mothers of young children (mean age 40 years ± 4.5, BMI 27.9 kg/m2 ± 5.6) were recruited from the community in Melbourne, Australia. The intervention group (n = 127) attended four interactive group sessions over 4 months, held in 12 local primary schools in 2006, and was compared to a group (n = 123) receiving a single, non-interactive, health education session. Data collection included self-reported weight (both groups), measured weight (intervention only), self-efficacy, dietary intake and physical activity.

Results
Mean measured weight decreased significantly in the intervention group (-0.78 kg 95% CI; -1.22 to -0.34, p < 0.001). Comparing groups using self-reported weight, both the intervention and comparison groups decreased weight, -0.75 kg (95% CI; -1.57 to 0.07, p = 0.07) and -0.72 kg (95% CI; -1.59 to 0.14 p = 0.10) respectively with no significant difference between groups (-0.03 kg, 95% CI; -1.32 to 1.26, p = 0.95). More women lost or maintained weight in the intervention group. The intervention group tended to have the greatest effect in those who were overweight at baseline and in those who weighed themselves regularly. Intervention women who rarely self-weighed gained weight (+0.07 kg) and regular self-weighers lost weight (-1.66 kg) a difference of -1.73 kg (95% CI; -3.35 to -0.11 p = 0.04). The intervention reported increased physical activity although the difference between groups did not reach significance. Both groups reported replacing high fat foods with low fat alternatives and self-efficacy deteriorated in the comparison group only.

Conclusion
Both a single health education session and interactive behavioral intervention will result in a similar weight loss in the short term, although more participants in the interactive intervention lost or maintained weight. There were small non-significant changes to physical activity and changes to fat intake specifically replacing high fat foods with low fat alternatives such as fruit and vegetables. Self-monitoring appears to enhance weight loss when part of an intervention.

Options for change in the Australian cervical cancer screening program in context of HPV detection and vaccination

Introduction:
Cervical cancer screening has been implemented for over a decade in Australia and has significantly reduced the mortality and morbidity of the disease. The emergence of new technologies for cervical cancer, such as the Human Papillomavirus (HPV) vaccine and DNA testing has encouraged debate regarding the effective use of resources in cervical cancer prevention. The present study evaluates the cost-effectiveness, from a health sector perspective, of various screening strategies in the era of these new technologies.

Methods:
A stochastic epidemiological model using a discrete event and continuous algorithm was developed to describe the natural history of cervical cancer. By allowing one member of the cohort into the model at a time, this micro-simulation model encompasses the characteristics of heterogeneity and can track individual life histories. To evaluate the cost-effectiveness of the HPV vaccine a Markov model was built to simulate the effect on the incidence of HPV and subsequent cervical cancer. A number of proposed screening strategies were evaluated with the stochastic model for the application of HPV DNA testing, with changes in the screening interval and target population. Health outcomes were measured by Disability-Adjusted Life-Years (DALYs), adjusted for application within an evaluation setting (i.e. the mortality component of the DALY was adjusted by a disability weight when early mortality due to cervical cancer is avoided). Costs in complying with the Australian updated guidelines were assessed by pathway analysis to estimate the resources associated with cervical cancer and its pre-cancerous lesion treatment. Sensitivity analyses were performed to investigate the key parameters that influenced the cost-effectiveness results.

Results:
Current practice has already brought huge health gain by preventing more than 4,000 deaths and saving more than 86,000 life-years in a cohort of a million women. Any of the alternative screening strategies alter the total amount of health gain by a small margin compared to current practice. The results of incremental analyses of the alternative screening strategies compared to current practice suggest the adoption of the HPV DNA test as a primary screening tool every 3 years commencing at age 18, or the combined pap smear/HPV test every 3 years commencing at age 25, are more costly than current practice but with reasonable ICERs (AUD$1,810 per DALY and AUD$18,600 per DALY respectively). Delaying commencement of Pap test screening to age 25 is less costly than current practice, but involves considerable health loss. The sensitivity analysis shows, however, that the screening test accuracy has a significant impact on these conclusions. Threshold analysis indicates that a sensitivity ranging from 0.80 to 0.86 for the combined test in women younger than 30 is required to produce an acceptable incremental cost-effectiveness ratio.

Conclusions:
The adoption of HPV and combined test with an extended screening interval is more costly but affordable, resulting in reasonable ICERs. They appear good value for money for the Australian health care system, but need more information on test accuracy to make an informed decision. Potential screening policy change under current Australian HPV Vaccination Program is current work in progress. A Markov model is built to simulate the effect on the incidence of HPV and subsequent cervical cancer. Adoption of HPV DNA test as a primary screening tool in the context of HPV vaccination is under evaluation.

Five-year change in cardiovascular risk factors according to education level : the Australian diabetes, obesity and lifestyle (AusDiab) study

Background: Lower socioeconomic status (SES) is strongly associated with a higher prevalence of major cardiovascular risk factors, but few studies have examined changes in these risk factors over time according to SES. We aimed to determine whether SES is a predictor of the change in cardiovascular risk factor levels in a contemporary Australian adult cohort

Methods: Participants in the population-based AusDiab study aged 25+ years who attended both baseline and 5-year follow-up examinations (n=5 954) were categorised according to their level of education at baseline. Cardiovascular risk factor data at both time points were ascertained through questionnaire and physical measurement. Analysis was stratified by gender.

Results: The mean levels of systolic blood pressure, total cholesterol and the prevalence of smoking decreased between the two time points across all educational categories. Increases were also seen in mean BMI and the prevalence of diabetes. For blood pressure, the smallest decrease was seen among men with lower education (age-adjusted difference from higher education 2.8 mmHg, 95% CI 1.0 to 4.6). For total cholesterol, the decrease was greatest among women with lower education (age-adjusted difference from higher education 0.11 mmol/l, 95% CI 0.19 to 0.02). Among those "not at risk" at baseline for each risk factor, women with lower education were more likely than those with higher education to progress to being "at risk" for BMI (age-adjusted odds ratio 1.60, 95% CI 1.09 to 2.35).

Conclusion: Educational gradients narrowed for total cholesterol in women, but widened for systolic blood pressure in men and remained static for other risk factors. Lower education was also associated with an earlier onset of overweight or obesity in women. Given current socioeconomic gradients in risk factors levels, these findings suggest that social inequalities in CVD will persist and may even widen in the future.

Seabird and marine mammal management options in the face of climate change

Climate change is already impacting Australia’s oceans. Responses by marine life to both climate variability and change have been documented for low trophic levels, however, responses for Australia’s iconic higher trophic level marine taxa are poorly understood, including for many conservation-dependent seabirds and marine mammals. We report initial results from a national study evaluating impacts an adaptation options. Individual time series and combined analyses show consistent responses to historical climate signals, however, improved monitoring protocols are needed to maximize detection of any climate-related demographic signals. Despite difference in sampling , the development of regional multi-species-indices of environmental change provides robust climate indicators over large regions.

Rapid detection of SMARCB1 sequence variation using high resolution melting

Background : Rhabdoid tumors are rare cancers of early childhood arising in the kidney, central nervous system and other organs. The majority are caused by somatic inactivating mutations or deletions affecting the tumor suppressor locus SMARCB1 [OMIM 601607]. Germ-line SMARCB1 inactivation has been reported in association with rhabdoid tumor, epitheloid sarcoma and familial schwannomatosis, underscoring the importance of accurate mutation screening to ascertain recurrence and transmission risks. We describe a rapid and sensitive diagnostic screening method, using high resolution melting (HRM), for detecting sequence variations in SMARCB1. Methods : Amplicons, encompassing the nine coding exons of SMARCB1, flanking splice site sequences and the 5' and 3' UTR, were screened by both HRM and direct DNA sequencing to establish the reliability of HRM as a primary mutation screening tool. Reaction conditions were optimized with commercially available HRM mixes. Results : The false negative rate for detecting sequence variants by HRM in our sample series was zero. Nine amplicons out of a total of 140 (6.4%) showed variant melt profiles that were subsequently shown to be false positive. Overall nine distinct pathogenic SMARCB1 mutations were identified in a total of 19 possible rhabdoid tumors. Two tumors had two distinct mutations and two harbored SMARCB1 deletion. Other mutations were nonsense or frame-shifts. The detection sensitivity of the HRM screening method was influenced by both sequence context and specific nucleotide change and varied from 1: 4 to 1:1000 (variant to wild-type DNA). A novel method involving digital HRM, followed by re-sequencing, was used to confirm mutations in tumor specimens containing associated normal tissue. Conclusions : This is the first report describing SMARCB1 mutation screening using HRM. HRM is a rapid, sensitive and inexpensive screening technology that is likely to be widely adopted in diagnostic laboratories to facilitate whole gene mutation screening.

Reproducibility of aortic intima-media thickness in infants using edge-detection software and manual caliper measurements

Background: Aortic intima-media thickness measured by transabdominal ultrasound (aIMT) is an intermediate phenotype of cardiovascular risk. We aimed to (1) investigate the reproducibility of aIMT in a population-derived cohort of infants; (2) establish the distribution of aIMT in early infancy; (3) compare measurement by edge-detection software to that by manual sonographic calipers; and (4) assess the effect of individual and environmental variables on image quality. Methods. Participants were term infants recruited to a population-derived birth cohort study. Transabdominal ultrasound was performed at six weeks of age by one of two trained operators. Thirty participants had ultrasounds performed by both operators on the same day. Data were collected on environmental (infant sleeping, presence of a sibling, use of sucrose, timing during study visit) and individual (post-conception age, weight, gender) variables. Two readers assessed image quality and measured aIMT by edge-detection software and a subset by manual sonographic calipers. Measurements were repeated by the same reader and between readers to obtain intra-observer and inter-observer reliability. Results: Aortic IMT was measured successfully using edge-detection in 814 infants, and 290 of these infants also had aIMT measured using manual sonographic calipers. The intra-reader intra-class correlation (ICC) (n = 20) was 0.90 (95% CI 0.76, 0.96), mean difference 1.5 μm (95% LOA -39, 59). The between reader ICC using edge-detection (n = 20) was 0.92 (95% CI 0.82, 0.97) mean difference 2 μm (95% LOA -45.0, 49.0) and with manual caliper measurement (n = 290) the ICC was 0.84 (95% CI 0.80, 0.87) mean difference 5 μm (95% LOA -51.8, 61.8). Edge-detection measurements were greater than those from manual sonographic calipers (mean aIMT 618 μm (50) versus mean aIMT 563 μm (49) respectively; p < 0.001, mean difference 44 μm, 95% LOA -54, 142). With the exception of infant crying (p = 0.001), no associations were observed between individual and environmental variables and image quality. Conclusion: In a population-derived cohort of term infants, aIMT measurement has a high level of intra and inter-reader reproducibility. Measurement of aIMT using edge-detection software gives higher inter-reader ICC than manual sonographic calipers. Image quality is not substantially affected by individual and environmental factors. © 2014 McCloskey et al.; licensee BioMed Central Ltd.

Marine object detection using background modelling and blob analysis

Monitoring marine object is important for understanding the marine ecosystem and evaluating impacts on different environmental changes. One prerequisite of monitoring is to identify targets of interest. Traditionally, the target objects are recognized by trained scientists through towed nets and human observation, which cause much cost and risk to operators and creatures. In comparison, a noninvasive way via setting up a camera and seeking objects in images is more promising. In this paper, a novel technique of object detection in images is presented, which is applicable to generic objects. A robust background modelling algorithm is proposed to extract foregrounds and then blob features are introduced to classify foregrounds. Particular marine objects, box jellyfish and sea snake, are successfully detected in our work. Experiments conducted on image datasets collected by the Australian Institute of Marine Science (AIMS) demonstrate the effectiveness of the proposed technique.