Identification of New Zealand bats in flight from analysis of echolocation calls by artificial neural networks.

Time-expanded and heterodyned echolocation calls of the New Zealand long-tailed Chalinolobus tuberculatus and lesser short-tailed bat Mystacina tuberculata were recorded and digitally analysed. Temporal and spectral parameters were measured from time-expanded calls and power spectra generated for both time-expanded and heterodyned calls. Artificial neural networks were trained to classify the calls of both species using temporal and spectral parameters and power spectra as input data. Networks were then tested using data not previously seen. Calls could be unambiguously identified using parameters and power spectra from time-expanded calls. A neural network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 40 kHz (the frequency with the most energy of the fundamental of C. tuberculatus call), could identify 99% and 84% of calls of C. tuberculatus and M. tuberculata, respectively. A second network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 27 kHz (the frequency with the most energy of the fundamental of M. tuberculata call), could identify 34% and 100% of calls of C. tuberculatus and M. tuberculata, respectively. This study represents the first use of neural networks for the identification of bats from their echolocation calls. It is also the first study to use power spectra of time-expanded and heterodyned calls for identification of chiropteran species. The ability of neural networks to identify bats from their echolocation calls is discussed, as is the ecology of both species in relation to the design of their echolocation calls.

Reliable Fault Diagnosis for Low-Speed Bearings Using Individually Trained Support Vector Machines With Kernel Discriminative Feature Analysis

This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The proposed approach first extracts wavelet-based fault features that represent diverse symptoms of multiple low-speed bearing defects. The most useful fault features for diagnosis are then selected by utilizing a genetic algorithm (GA)-based kernel discriminative feature analysis cooperating with one-against-all multicategory support vector machines (OAA MCSVMs). Finally, each support vector machine is individually trained with its own feature vector that includes the most discriminative fault features, offering the highest classification performance. In this study, the effectiveness of the proposed GA-based kernel discriminative feature analysis and the classification ability of individually trained OAA MCSVMs are addressed in terms of average classification accuracy. In addition, the proposedGA- based kernel discriminative feature analysis is compared with four other state-of-the-art feature analysis approaches. Experimental results indicate that the proposed approach is superior to other feature analysis methodologies, yielding an average classification accuracy of 98.06% and 94.49% under rotational speeds of 50 revolutions-per-minute (RPM) and 80 RPM, respectively. Furthermore, the individually trained MCSVMs with their own optimal fault features based on the proposed GA-based kernel discriminative feature analysis outperform the standard OAA MCSVMs, showing an average accuracy of 98.66% and 95.01% for bearings under rotational speeds of 50 RPM and 80 RPM, respectively.

The global burden attributable to low bone mineral density

Introduction The Global Burden of Disease Study 2010 estimated the worldwide health burden of 291 diseases and injuries and 67 risk factors by calculating disability-adjusted life years (DALYs). Osteoporosis was not considered as a disease, and bone mineral density (BMD) was analysed as a risk factor for fractures, which formed part of the health burden due to falls. Objectives To calculate (1) the global distribution of BMD, (2) its population attributable fraction (PAF) for fractures and subsequently for falls, and (3) the number of DALYs due to BMD. Methods A systematic review was performed seeking population-based studies in which BMD was measured by dual-energy X-ray absorptiometry at the femoral neck in people aged 50 years and over. Age- and sex-specific mean ± SD BMD values (g/cm2) were extracted from eligible studies. Comparative risk assessment methodology was used to calculate PAFs of BMD for fractures. The theoretical minimum risk exposure distribution was estimated as the age- and sex-specific 90th centile from the Third National Health and Nutrition Examination Survey (NHANES III). Relative risks of fractures were obtained from a previous meta-analysis. Hospital data were used to calculate the fraction of the health burden of falls that was due to fractures. Results Global deaths and DALYs attributable to low BMD increased from 103 000 and 3 125 000 in 1990 to 188 000 and 5 216 000 in 2010, respectively. The percentage of low BMD in the total global burden almost doubled from 1990 (0.12%) to 2010 (0.21%). Around one-third of falls-related deaths were attributable to low BMD. Conclusions Low BMD is responsible for a growing global health burden, only partially representative of the real burden of osteoporosis.

Estimating the burden of disease attributable to low fruit and vegetable intake in South Africa in 2000

Objectives To estimate the burden of disease attributed to low fruit and vegetable intake by sex and age group in South Africa for the year 2000. Design The analysis follows the World Health Organization comparative risk assessment (CRA) methodology. Populationattributable fractions were calculated from South African prevalence data from dietary surveys and applied to the revised South African burden of disease estimates for 2000. A theoretical maximum distribution of 600 g per day for fruit and vegetable intake was chosen. Monte Carlo simulationmodelling techniques were used for uncertainty analysis. Setting South Africa. Subjects Adults ≥ 15 years. Outcome measures Mortality and disability-adjusted life years (DALYs), from ischaemic heart disease, ischaemic stroke, lung cancer, gastric cancer, colorectal cancer and oesophageal cancer. Results Low fruit and vegetable intake accounted for 3.2% of total deaths and 1.1% of the 16.2 million attributable DALYs. For both males and females the largest proportion of total years of healthy life lost attributed to low fruit and vegetable intake was for ischaemic heart disease (60.6% and 52.2%, respectively). Ischaemic stroke accounted for 17.8% of attributable DALYs for males and 32.7% for females. For the related cancers, the leading attributable DALYs for men and women were oesophageal cancer (9.8% and 7.0%, respectively) and lung cancer (7.8% and 4.7%, respectively). Conclusions A high intake of fruit and vegetables can make a significant contribution to decreasing mortality from certain diseases. The challenge lies in creating the environment that facilitates changes in dietary habits such as the increased intake of fruit and vegetables.

The influence of flight speed on the ranging performance of bats using frequency modulated echolocation pulses

Many species of bat use ultrasonic frequency modulated (FM) pulses to measure the distance to objects by timing the emission and reception of each pulse. Echolocation is mainly used in flight. Since the flight speed of bats often exceeds 1% of the speed of sound,Doppler effects will lead to compression of the time between emission and reception as well as an elevation of the echo frequencies, resulting in a distortion of the perceived range. This paper describes the consequences of these Doppler effects on the ranging performance of bats using different pulse designs. The consequences of Doppler effects on ranging performance described in this paper assume bats to have a very accurate ranging resolution, which is feasible with a filterbank receiver. By modeling two receiver types, it was first established that the effects of Doppler compression are virtually independent of the receiver type. Then, used a cross-correlation model was used to investigate the effect of flight speed on Doppler tolerance and range–Doppler coupling separately. This paper further shows how pulse duration, bandwidth, function type, and harmonics influence Doppler tolerance and range–Doppler coupling. The influence of each signal parameter is illustrated using calls of several bat species. It is argued that range–Doppler coupling is a significant source of error in bat echolocation, and various strategies bats could employ to deal with this problem, including the use of range rate information are discussed.

Power quality improvements in low voltage distribution networks containing distributed energy resources

In this thesis various schemes using custom power devices for power quality improvement in low voltage distribution network are studied. Customer operated distributed generators makes a typical network non-radial and affect the power quality. A scheme considering different algorithm of DSTATCOM is proposed for power circulation and islanded operation of the system. To compensate reactive power overflow and facilitate unity power factor, a UPQC is introduced. Stochastic analysis is carried out for different scenarios to get a comprehensive idea about a real life distribution network. Combined operation of static compensator and voltage regulator is tested for the optimum quality and stability of the system.

High and low fear phenotypes show differences in phosphorylated (p44/42 ERK) MAPK-expressing neurons in the lateral amygdala

Post traumatic stress disorder (PTSD) is a serious medical condition effecting both military and civilian populations. While its etiology remains poorly understood it is characterized by high and prolonged levels of fear responding. One biological unknown is whether individuals expressing high or low conditioned fear memory encode the memory differently and if that difference underlies fear response. In this study we examined cellular mechanisms that underlie high and low conditioned fear behavior by using an advanced intercrossed mouse line (B6D2F1) selected for high and low Pavlovian fear response. A known requirement for consolidation of fear memory, phosphorylated mitogen activated protein kinase (p44/42 (ERK) MAPK (pMAPK)) in the lateral amygdala (LA) is a reliable marker of fear learning-related plasticity. In this study, we asked whether high and low conditioned fear behavior is associated with differential pMAPK expression in the LA and if so, is it due to an increase in neurons expressing pMAPK or increased pMAPK per neuron. To examine this, we quantified pMAPK-expressing neurons in the LA at baseline and following Pavlovian fear conditioning. Results indicate that high fear phenotype mice have more pMAPK-expressing neurons in the LA. This finding suggests that increased endogenous plasticity in the LA may be a component of higher conditioned fear responses and begins to explain at the cellular level how different fear responders encode fear memories. Understanding how high and low fear responders encode fear memory will help identify novel ways in which fear-related illness risk can be better predicted and treated.

Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

The origin of cyclical high- and low-Cr basalts with continental crust trace element signatures in the Kalkarindji Large Igneous Province

The 510 million year old Kalkarindji Large Igneous Province correlates in time with the first major extinction event after the Cambrian explosion of life. Large igneous provinces correlate with all major mass extinction events in the last 500 million years. The genetic link between large igneous provinces and mass extinction remains unclear. My work is a contribution towards understanding magmatic processes involved in the generation of Large Igneous Provinces. I concentrate on the origin of variation in Cr in magmas and have developed a model in which high temperature melts intrude into and assimilate large amounts of upper continental crust.

The rise of low-cost sensing for managing air pollution in cities

Ever growing populations in cities are associated with a major increase in road vehicles and air pollution. The overall high levels of urban air pollution have been shown to be of a significant risk to city dwellers. However, the impacts of very high but temporally and spatially restricted pollution, and thus exposure, are still poorly understood. Conventional approaches to air quality monitoring are based on networks of static and sparse measurement stations. However, these are prohibitively expensive to capture tempo-spatial heterogeneity and identify pollution hotspots, which is required for the development of robust real-time strategies for exposure control. Current progress in developing low-cost micro-scale sensing technology is radically changing the conventional approach to allow real-time information in a capillary form. But the question remains whether there is value in the less accurate data they generate. This article illustrates the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, whilst addressing the major challenges for their effective implementation.

The mechanical and inflammatory low back pain (MIL) index: development and validation

Abstract Background The purpose of this study was the development of a valid and reliable “Mechanical and Inflammatory Low Back Pain Index” (MIL) for assessment of non-specific low back pain (NSLBP). This 7-item tool assists practitioners in determining whether symptoms are predominantly mechanical or inflammatory. Methods Participants (n = 170, 96 females, age = 38 ± 14 years-old) with NSLP were referred to two Spanish physiotherapy clinics and completed the MIL and the following measures: the Roland Morris Questionnaire (RMQ), SF-12 and “Backache Index” (BAI) physical assessment test. For test-retest reliability, 37 consecutive patients were assessed at baseline and three days later during a non-treatment period. Face and content validity, practical characteristics, factor analysis, internal consistency, discriminant validity and convergent validity were assessed from the full sample. Results A total of 27 potential items that had been identified for inclusion were subsequently reduced to 11 by an expert panel. Four items were then removed due to cross-loading under confirmatory factor analysis where a two-factor model yielded a good fit to the data (χ2 = 14.80, df = 13, p = 0.37, CFI = 0.98, and RMSEA = 0.029). The internal consistency was moderate (α = 0.68 for MLBP; 0.72 for ILBP), test-retest reliability high (ICC = 0.91; 95%CI = 0.88-0.93) and discriminant validity good for either MLBP (AUC = 0.74) and ILBP (AUC = 0.92). Convergent validity was demonstrated through similar but weak correlations between the ILBP and both the RMQ and BAI (r = 0.34, p < 0.001) and the MLBP and BAI (r = 0.38, p < 0.001). Conclusions The MIL is a valid and reliable clinical tool for patients with NSLBP that discriminates between mechanical and inflammatory LBP. Keywords: Low back pain; Psychometrics properties; Pain measurement; Screening tool; Inflammatory; Mechanical

Automatic UAV forced landing site detection using machine learning

The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine learning approaches including the Gaussian Mixture Model and the Support Vector Machine. A range of learning parameters are analysed including the number of Guassian mixtures, support vector kernels including linear, radial basis function Kernel (RBF) and polynormial kernel (poly), and the order of RBF kernel and polynormial kernel. Moreover, a modified footprint operator is employed during feature extraction to better describe the geometric characteristics of the local area surrounding a pixel. The performance of the presented system is compared to a baseline UAV forced landing site detection system which uses edge features and an Artificial Neural Network (ANN) region type classifier. Experiments conducted on aerial image datasets captured over typical urban environments reveal improved landing site detection can be achieved with an SVM classifier with an RBF kernel using a combination of colour and texture features. Compared to the baseline system, the proposed system provides significant improvement in term of the chance to detect a safe landing area, and the performance is more stable than the baseline in the presence of changes to the UAV altitude.