Design and flight testing of an integrated solar powered UAV and WSN for greenhouse gas monitoring emissions in agricultural farms

There is an increased interest in measuring the amount of greenhouse gases produced by farming practices . This paper describes an integrated solar powered Unmanned Air Vehicles (UAV) and Wireless Sensor Network (WSN) gas sensing system for greenhouse gas emissions in agricultural lands. The system uses a generic gas sensing system for CH4 and CO2 concentrations using metal oxide (MoX) and non-dispersive infrared sensors, and a new solar cell encapsulation method to power the unmanned aerial system (UAS)as well as a data management platform to store, analyze and share the information with operators and external users. The system was successfully field tested at ground and low altitudes, collecting, storing and transmitting data in real time to a central node for analysis and 3D mapping. The system can be used in a wide range of outdoor applications at a relatively low operational cost. In particular, agricultural environments are increasingly subject to emissions mitigation policies. Accurate measurements of CH4 and CO2 with its temporal and spatial variability can provide farm managers key information to plan agricultural practices. A video of the bench and flight test performed can be seen in the following link: https://www.youtube.com/watch?v=Bwas7stYIxQ

Evidence-based recommendations for the monitoring and treatment of ankylosing spondylitis: Results from the Australian 3E initiative in rheumatology

Aim: To develop a set of Australian recommendations for the monitoring and treatment of ankylosing spondylitis (AS) through systematic literature review combined with the opinion of practicing rheumatologists. Methods: A set of eight questions, four in each domain of monitoring and treatment, were formulated by voting and the Delphi method. The results of a systematic literature review addressing each question were presented to the 23 participants of the Australian 3E meeting. All participants were clinical rheumatologists experienced in the daily management of AS. Results: After three rounds of breakout sessions to discuss the findings of the literature review, a set of recommendations was finalized after discussion and voting. The category of evidence and strength of recommendation were determined for each proposal. The level of agreement among participants was excellent (mean 84%, range 64-100%). Conclusions: The 12 recommendations developed from evidence and expert opinion provide guidance for the daily management of AS patients. For most recommendations, we found a paucity of supportive evidence in the literature highlighting the need for additional clinical studies.

Detection of anuran calling activity in long field recordings for bio-acoustic monitoring

This paper presents a system to analyze long field recordings with low signal-to-noise ratio (SNR) for bio-acoustic monitoring. A method based on spectral peak track, Shannon entropy, harmonic structure and oscillation structure is proposed to automatically detect anuran (frog) calling activity. Gaussian mixture model (GMM) is introduced for modelling those features. Four anuran species widespread in Queensland, Australia, are selected to evaluate the proposed system. A visualization method based on extracted indices is employed for detection of anuran calling activity which achieves high accuracy.

Noninvasive imaging of atheromatous carotid plaques

Atherothrombosis is a systemic disease of the arterial wall that affects the carotid, coronary, and peripheral vascular beds, and the aorta. This condition is associated with complications such as stroke, myocardial infarction, and peripheral vascular disease, which usually result from unstable atheromatous plaques. The study of atheromatous plaques can provide useful information about the natural history and progression of the disease, and aid in the selection of appropriate treatment. Plaque imaging can be crucial in achieving this goal. In this Review, we focus on the various noninvasive imaging techniques that are being used for morphological and functional assessment of carotid atheromatous plaques in the clinical setting.

Perylene-based profluorescent nitroxides for the rapid monitoring of polyester degradation upon weathering: An assessment

A profluorescent nitroxide possessing an isoindoline nitroxide moiety linked to a perylene fluorophore was developed to monitor radical mediated degradation of melamine-formaldehyde crosslinked polyester coil coatings in an industry standard accelerated weathering tester. Trapping of polyester-derived radicals (most likely C-radicals) that are generated during polymer degradation leads to fluorescent closed-shell alkoxy amines, which was used to obtain time-dependent degradation profiles to assess the relative stability of different polyesters towards weathering. The nitroxide probe couples excellent thermal stability and satisfactory photostability with high sensitivity and enables detection of free radical damage in polyesters under conditions that mimic exposure to the environment on a time scale of hours rather than months or years required by other testing methods. There are indications that the profluorescent nitroxide undergoes partial photo-degradation in the absence of polymer-derived radicals. Unexpectedly, it was also found that UV-induced fragmentation of the NO–C bond in closed-shell alkoxy amines leads to regeneration of the profluorescent nitroxide and the respective C-radical. The maximum fluorescence intensity that could be achieved with a given probe concentration is therefore not only determined by the amount of polyester radicals formed during accelerated weathering, but also by the light-driven side reactions of the profluorescent nitroxide and the corresponding alkoxy amine radical trapping products. Studies to determine the optimum probe concentration in the polymer matrix revealed that aggregation and re-absorption effects lowered the fluorescence intensity at higher concentrations of the profluorescent nitroxide, but too low probe concentrations, where these effects would be avoided, were not sufficient to trap the amount of polyester radicals formed upon weathering. The optimized experimental conditions were used to assess the impact of temperature and UV irradiance on polymer degradation during accelerated weathering.

Home monitoring for infants at risk of the sudden infant death syndrome

This study evaluates the effectiveness and social implications of home monitoring of 31 infants at risk of sudden infant death syndrome (SIDS). Thirteen siblings of children dying of SIDS, nine near miss SIDS infants and nine preterm infants with apnoea persisting beyond 40 weeks post conceptual age were monitored from a mean age of 15 days to a mean of 10 months. Chest movement detection monitors were used in 27 and thoracic impedance monitors in four. Genuine apnoeic episodes were reported by 21 families, and 13 infants required resuscitation. Apnoeic episodes occurred in all nine preterm infants but in only five (38%) of the siblings of SIDS (P<0.05). Troublesome false alarms were a major problem occurring with 61% of the infants and were more common with the preterm infants than the siblings of SIDS. All but two couples stated that the monitor decreased anxiety and improved their quality of life. Most parents accepted that the social restrictions imposed by the monitor were part of the caring process but four couples were highly resentful of the changes imposed on their lifestyle. The monitors used were far from ideal with malfunction occurring in 17, necessitating replacement in six, repair in six and cessation of monitoring in three. The parents became ingenious in modifying the monitors to their own individual requirements Although none of these 31 ‘at risk’ infants died the study sample was far too small to conclude whether home monitoring prevented any cases of SIDS.

Complex symbolic sequence clustering and multiple classifiers for predictive process monitoring

This paper addresses the following predictive business process monitoring problem: Given the execution trace of an ongoing case,and given a set of traces of historical (completed) cases, predict the most likely outcome of the ongoing case. In this context, a trace refers to a sequence of events with corresponding payloads, where a payload consists of a set of attribute-value pairs. Meanwhile, an outcome refers to a label associated to completed cases, like, for example, a label indicating that a given case completed “on time” (with respect to a given desired duration) or “late”, or a label indicating that a given case led to a customer complaint or not. The paper tackles this problem via a two-phased approach. In the first phase, prefixes of historical cases are encoded using complex symbolic sequences and clustered. In the second phase, a classifier is built for each of the clusters. To predict the outcome of an ongoing case at runtime given its (uncompleted) trace, we select the closest cluster(s) to the trace in question and apply the respective classifier(s), taking into account the Euclidean distance of the trace from the center of the clusters. We consider two families of clustering algorithms – hierarchical clustering and k-medoids – and use random forests for classification. The approach was evaluated on four real-life datasets.

An effective, economic way of monitoring menstrual cycle hormones in at risk female athletes

PURPOSE: Female athletes, in response to intensive training, competition stress and a lean, athletic physique, are at increased risk of altered hypothalamic-pituitary ovarian (HPO) axis function associated with menstrual cycle disturbance and reduced secretion of the ovarian hormones estrogen and progesterone. Because there is evidence suggesting possible detrimental effects on skeletal health associated with deficiencies in these hormones, a suitable means to asses ovarian hormone concentrations in at risk athletes is needed. The aim of this study was to evaluate a simple, economical means to monitor the ovarian hormone production in athletes, in the setting of intensive training. METHODS: Subjects comprised 14 adolescent rowers, 12 lightweight rowers, and two groups of 10 matched control subjects. Ovarian function was monitored during the competition season by estimation of urinary excretion of estrone glucuronide (E1G) and pregnanediol glucuronide (PdG), enabling the menstrual cycles to be classified as ovulatory or anovulatory. RESULTS: Results indicated 35% and 75% of schoolgirl and lightweight rowers had anovulatory menstrual cycles, respectively. These findings were highlighted by significantly lower excretion of E1G and PdG during phases of intensive training in both the lightweight and schoolgirl rowers, compared with the control subjects. CONCLUSION: It was concluded that the urinary E1G and PdG assays were an effective means to assess the influence of intense training on ovarian hormone concentrations in at risk athletes. It is recommended that this technique be applied more widely as a means of early detection of athletes with low estrogen and progesterone levels, in an attempt to avoid detrimental influences on skeletal health.

Monitoring exposure to polycyclic aromatic hydrocarbons in an Australian population using pooled urine samples

Integrated exposure to polycyclic aromatic hydrocarbons (PAHs) can be assessed through monitoring of urinary mono-hydroxylated PAHs (OH-PAHs). The aim of this study was to provide the first assessment of exposure to PAHs in a large sample of the population in Queensland, Australia including exposure to infant (0-4. years). De-identified urine specimens, obtained from a pathology laboratory, were stratified by age and sex, and pooled (n. =. 24 pools of 100) and OH-PAHs were measured by gas chromatography-isotope dilution-tandem mass spectrometry. Geometric mean (GM) concentrations ranged from 30. ng/L (4-hydroxyphenanthrene) to 9221. ng/L (1-naphthol). GM of 1-hydroxypyrene, the most commonly used PAH exposure biomarker, was 142. ng/L. The concentrations of OH-PAHs found in this study are consistent with those in developed countries and lower than those in developing countries. We observed no association between sex and OH-PAH concentrations. However, we observed lower urinary concentrations of all OH-PAHs in samples from infants (0-4. years), children (5-14. years) and the elderly (>. 60. year old) compared with samples from other age groups (15-29, 30-44 and 45-59. years) which may be attributed to age-dependent behaviour-specific exposure sources.

Monitoring healing progression and characterizing the mechanical environment in preclinical models for bone tissue engineering

The treatment of large segmental bone defects remains a significant clinical challenge. Due to limitations surrounding the use of bone grafts, tissue-engineered constructs for the repair of large bone defects could offer an alternative. Before translation of any newly developed tissue engineering (TE) approach to the clinic, efficacy of the treatment must be shown in a validated preclinical large animal model. Currently, biomechanical testing, histology, and microcomputed tomography are performed to assess the quality and quantity of the regenerated bone. However, in vivo monitoring of the progression of healing is seldom performed, which could reveal important information regarding time to restoration of mechanical function and acceleration of regeneration. Furthermore, since the mechanical environment is known to influence bone regeneration, and limb loading of the animals can poorly be controlled, characterizing activity and load history could provide the ability to explain variability in the acquired data sets and potentially outliers based on abnormal loading. Many approaches have been devised to monitor the progression of healing and characterize the mechanical environment in fracture healing studies. In this article, we review previous methods and share results of recent work of our group toward developing and implementing a comprehensive biomechanical monitoring system to study bone regeneration in preclinical TE studies.

Monitoring temporal changes in use of two cathinones in a large urban catchment in Queensland, Australia

Wastewater analysis was used to examine prevalence and temporal trends in the use of two cathinones, methylone and mephedrone, in an urban population (>200,000 people) in South East Queensland, Australia. Wastewater samples were collected from the inlet of the sewage treatment plant that serviced the catchment from 2011 to 2013. Liquid chromatography coupled with tandem mass spectrometry was used to measure mephedrone and methylone in wastewater sample using direct injection mode. Mephedrone was not detected in any samples while methylone was detected in 45% of the samples. Daily mass loads of methylone were normalized to the population and used to evaluate methylone use in the catchment. Methylone mass loads peaked in 2012 but there was no clear temporal trend over the monitoring period. The prevalence of methylone use in the catchment was associated with the use of MDMA, the more popular analogue of methylone, as indicated by other complementary sources. Methylone use was stable in the study catchment during the monitoring period whereas mephedrone use has been declining after its peak in 2010. More research is needed on the pharmacokinetics of emerging illicit drugs to improve the applicability of wastewater analysis in monitoring their use in the population.

Infrared thermal imaging for automated detection of diabetic foot complications

Background Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the applicability of high-resolution infrared thermal imaging for noninvasive automated detection of signs of diabetic foot disease. Methods The plantar foot surfaces of 15 diabetes patients were imaged with an infrared camera (resolution, 1.2 mm/pixel): 5 patients had no visible signs of foot complications, 5 patients had local complications (e.g., abundant callus or neuropathic ulcer), and 5 patients had difuse complications (e.g., Charcot foot, infected ulcer, or critical ischemia). Foot temperature was calculated as mean temperature across pixels for the whole foot and for specified regions of interest (ROIs). Results No diferences in mean temperature >1.5 °C between the ipsilateral and the contralateral foot were found in patients without complications. In patients with local complications, mean temperatures of the ipsilateral and the contralateral foot were similar, but temperature at the ROI was >2 °C higher compared with the corresponding region in the contralateral foot and to the mean of the whole ipsilateral foot. In patients with difuse complications, mean temperature diferences of >3 °C between ipsilateral and contralateral foot were found. Conclusions With an algorithm based on parameters that can be captured and analyzed with a high-resolution infrared camera and a computer, it is possible to detect signs of diabetic foot disease and to discriminate between no, local, or difuse diabetic foot complications. As such, an intelligent telemedicine monitoring system for noninvasive automated detection of signs of diabetic foot disease is one step closer. Future studies are essential to confirm and extend these promising early findings.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Symposium: Food pricing and affordability of ‘healthy’ versus ‘less healthy’ diets: An international approach to monitoring and surveillance

Symposium co-ordinated by The International Network for Food and Obesity/NCDs Research, Monitoring and Action Support (INFORMAS) Purpose Global monitoring of the price and affordability of foods, meals and diets is urgently needed. There are major methodological challenges in developing robust, cost-effective, standardized, and policy relevant tools, pertinent to nutrition, obesity, and diet-related non-communicable diseases and their inequalities. There is increasing pressure to take into account environmental sustainability. Changes in price differentials and affordability need to be comparable between and within countries and over time. Robust tools could provide baseline data for monitoring and evaluating structural, economic and social policies at the country/regional and household levels. INFORMAS offers one framework for consideration.

Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.