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Climate change is increasing the frequency, intensity, and duration of extreme weather events across the globe. Understanding the capacity for ecological communities to withstand and recover from such events is critical. Typhoons are extreme weather events that are expected to broadly homogenise ecosystems through structural damage to vegetation and longer-term effects of salinization. Given their unpredictable nature, monitoring ecological responses to typhoons is challenging, particularly for mobile animals such as birds. Here, we report spatially variable ecological responses to typhoons across terrestrial landscapes. Using a high temporal resolution passive acoustic monitoring network across 24 sites on the subtropical island of Okinawa, Japan, we found that typhoons elicit divergent ecological responses among Okinawa’s pristine forests, as indicated by increased spatial variability of biological sound production (biophony) among forested sites. However, no such post-typhoon shift in variability was observed among developed urban or agricultural sites. This indicates that natural forests have a diversity of pathways through which communities can respond to typhoons, whereas land use development produces communities more constrained in their disturbance responses. That is, spatial insurance effects among forest communities may provide resilience to typhoons at the landscape scale, but this spatial insurance was diminished by habitat degradation through land use development. Though site-level typhoon impacts on soundscapes and bird detections were not particularly strong, we nevertheless revealed spatial heterogeneity in typhoon responses, owing to the data resolution afforded to us by monitoring at scale (high temporal resolution, broad spatial extent). Our findings underscore the importance of natural forests in insuring ecosystems against disturbance, and demonstrate the potential of landscape-scale acoustic sensor networks for documenting the understudied ecological impacts of unpredictable extreme weather events.

A recent study by Van Dyke et al.1paired experimental drought manipulations with demographic models and trait measurements to project major shifts in coexistence among a number of annual plant taxa. However, re-analysis of the data under alternative, more predictive competition models reveals that the authors’ original conclusions are very sensitive to slight variations in model form. Furthermore, propagating model parameter error into coexistence predictions results in relatively weak support for the majority of coexistence shifts predicted by the authors’ original model. These results highlight the need for increased statistical rigor when treating binary predictions of species coexistence as observed experimental outcomes, as is commonly practiced in empirical coexistence studies.

Negative impacts of discrete, short‐term disturbances to wildlife populations are well‐documented. The consequences of more gradual environmental change are less apparent and harder to study because they play out over longer periods and are often indirect in their action. Yet, they can drive the decline of wildlife populations even in seemingly pristine and currently well‐protected habitats. One such environmental change is a successional shift in a community's species composition as it regenerates from disturbance caused by past human land use. Early and middle successional tree species often provide key foods to folivores and frugivores, but the abundance of these resources drops as the forest matures, with adverse repercussions for these consumers. Our 44‐year record (1974–2018) of howler monkey (Alouatta palliata) group sizes and demographic composition from Barro Colorado Island, Panama, a protected reserve, documents an example of this phenomenon. After 70 years of relative stability, the mean size of howler monkey groups exhibited a marked decline, beginning in 2003. This downward trajectory in group size has continued through the most recent census in 2018. The composition of howler groups also changed significantly during the study period, with the patterns of decline differing among age/sex classes. There is no evidence that these changes were caused by increased rates of emigration, group fission, predation, parasitism, or disease. Rather, they are best explained by an island‐wide, succession‐driven decline in the densities of two species of free‐standing fig trees, Ficus yoponensis and F. insipida, which together were providing ~36% of BCI howlers’ annual diet. Abstract in Spanish is available with online material.

Exotic invasive plants possess the capacity to disrupt and extirpate populations of native species. Native plants' increased sensitivity to invaders' allelochemicals is a mechanism by which this can occur. However, it is not clear whether and how the allelopathic effects of invasive plants affect members of the soil faunal community - particularly the important functional guild of earthworms. We used the model earthworm Eisenia fetida to investigate the responses to extracts from the widely invasive Asterids (Ageratina adenophora, Bidens pilosa, Erigeron annuus) and closely-related native species in a greenhouse experiment. We observed declines in body mass and respiration, and increases in oxidative and DNA damage biomarkers in the native earthworm E. fetida when grown under root and leaf extracts from these invasive plants. These effects were concentration-dependent, and worm growth and physiology was most negatively affected under the highest concentrations of leaf extracts. Most importantly, extracts from invasive plants caused significantly more negative effects on E. fetida than did extracts from native plant species, indicating allelopathy from invasive plants may inhibit earthworm physiological functioning. These results expand the domain of the novel weapons hypothesis to the earthworm guild and demonstrate the utility of E. fetida as a bioindicator for plant allelochemicals.

In the study of factors shaping species' poleward range boundaries, climatic constraints are often assigned greater importance than biotic interactions such as competition. However, theory suggests competition can truncate a species' fundamental niche in harsh environments. We test this by challenging a mechanistic niche model - containing explicit competition terms - to predict the poleward range boundaries of two globally distributed, ecologically similar aquatic plant species. Mechanistic competition models accurately predicted the northern range limits of our study species, outperforming competition-free mechanistic models and matching the predictive ability of statistical niche models fit to occurrence records. Using the framework of modern coexistence theory, we found that relative nonlinearity in competitors' responses to temperature fluctuations maintains their coexistence boundary, highlighting the importance of this fluctuation-dependent mechanism. Our results support a more nuanced, interactive role of climate and competition in determining range boundaries, and illustrate a practical, process-based approach to understanding the determinants of range limits.

Species’ poleward ranges are thought to be primarily limited by climatic constraints rather than biotic interactions such as competition. However, theory suggests that a species’ tolerance to competition is reduced in harsh environments, such as at the extremes of its climatic niche. This implies that under certain conditions, interspecific competition near species’ range margins can prevent the establishment of populations into otherwise tolerable environments and results in geographic distributions being shaped by the interaction of climate and competition. We test this prediction by challenging an experimentally-parameterized mechanistic competition model to predict the poleward range boundaries of two widely co-occurring and ecologically-similar aquatic duckweed plants. We show that simple, mechanistic ecological niche models which include competition and thermal response terms best predict the northern range limits of our study species, outperforming competition-free mechanistic models and matching the predictive ability of popular statistical niche models fit to occurrence records. Next, using the theoretical framework of modern coexistence theory, we show that relative nonlinearity in competitors’ responses to temperature fluctuations maintains coexistence at the subordinate competitor’s poleward range boundary, highlighting the importance of this underappreciated fluctuation-dependent coexistence mechanism. Our results demonstrate the predictive utility of mechanistic niche models and support a more nuanced, interactive role of climate and species interactions in determining range boundaries, which may help explain the conflicting results from previous tests of classic range limit theory and contribute to a more mechanistic understanding of range dynamics under global change.

Microbial community data are commonly subjected to computational tools such as correlation networks, null models, and dynamic models, with the goal of identifying the ecological processes structuring microbial communities. Researchers applying these methods assume that the signs and magnitudes of species interactions and vital rates can be reliably parsed from observational data on species’ (relative) abundances. However, we contend that this assumption is violated when sample units contain any underlying spatial structure. Here, we show how three phenomena — Simpson’s paradox, context-dependence, and nonlinear averaging — can lead to erroneous conclusions about population parameters and species interactions when samples contain heterogeneous mixtures of populations or communities. At the root of this issue is the fundamental mismatch between the spatial scales of species interactions (micrometres) and those of typical microbial community samples (millimetres to centimetres). These issues can be overcome by measuring and accounting for spatial heterogeneity at very small scales, which will lead to more reliable inference of the ecological mechanisms structuring natural microbial communities.

Author(s): Monson, Tesla A.; Armitage, David W.; Hlusko, Leslea J. | Abstract: Machine learning is a formidable tool for pattern recognition in large datasets. We developed and expanded on these methods, applying machine learning pattern recognition to a problem in paleoanthropology and evolution. For decades, paleontologists have used the chimpanzee as a model for the chimpanzee-human last common ancestor (LCA) because they are our closest living primate relative. Using a large sample of extant and extinct primates, we tested the hypothesis that machine learning methods can accurately classify extant apes based on dental data. We then used this classification tool to observe the affinities between extant apes and Miocene hominoids. We assessed the discrimination accuracy of supervised learning algorithms when tasked with the classification of extant apes (n=175), using three types of data from the postcanine dentition: linear, 2-dimensional, and the morphological output of two genetic patterning mechanisms that are independent of body size: molar module component (MMC) and premolar-molar module (PMM) ratios. We next used the trained algorithms to classify a sample of fossil hominoids (n=95), treated as unknowns. Machine learning classifies extant apes with greater than 92% accuracy with linear and 2-dimensional dental measurements, and greater than 60% accuracy with the MMC and PMM ratios. Miocene hominoids are morphologically most similar in dental size and shape to extant chimpanzees. However, relative dental proportions of Miocene hominoids are more similar to extant gorillas and follow a strong trajectory through evolutionary time. Machine learning is a powerful tool that can discriminate between the dentitions of extant apes with high accuracy and quantitatively compare fossil and extant morphology. Beyond detailing applications of machine learning to vertebrate paleontology, our study highlights the impact of phenotypes of interest and the importance of comparative samples in paleontological studies.

Magnetic Induction Tomography (MIT) is a newly developing technique of electrical tomography that in principle is able to map the electrical conductivity distribution in the volume of objects. The image reconstruction problem in MIT is similar to electrical impedance tomography (EIT) in the sense that both seek to recover the conductivity map, but differ remarkably in the fact that data being inverted in MIT is derived from induction theory and related sources of noise are different. Progress in MIT image reconstruction is still limited, and so far mainly linear algorithms have been implemented. In difference imaging, step inversion was demonstrated for recovering perturbations within conductive media, but at the cost of producing qualitative images, whilst in absolute imaging, linear iterative algorithms have mostly been employed but mainly offering encouraging results for imaging isolated high conductive targets. In this paper, we investigate the possibility of absolute imaging in 3D MIT of a target within conductive medium for low conductivity application ( σ< 5S m −1 ). For this class of problems, the MIT image reconstruction exhibits non-linearity and ill-posedness that cannot be treated with linear algorithms. We propose to implement for the first time in MIT two effective inversion methods known in non-linear optimization as Levenberg Marquardt (LMM) and Powell's Dog Leg (PDLM) methods. These methods employ damping and trust region techniques for controlling convergence and improving minimization of the objective function. An adaptive version of Gauss Newton is also presented (AGNM), which implements a damping mechanism to the regularization parameter. Here, the level of penalty is varied during the iterative process. As a comparison between the methods, different criteria are examined from image reconstructions using the LMM, PDLM and AGNM. For test examples, volumetric image reconstruction of a perturbation within homogeneous cylindrical background is considered. For inversion, an independent finite element FEM software package Maxwell by Ansys is employed to generate simulated data using a model of a 16 channel MIT system. Numerical results are employed to show different performance characteristics between the methods based on convergence, stability and sensitivity to the choice of the regularization parameter. To demonstrate the effect of scalability of absolute imaging in MIT for more realistic problems, a human head model with an internal anomaly is used to produce reconstructions for different finer resolutions. AGNM is adopted here and employs the Krylov subspace method to replace the computationally demanding direct inversion of the regularized Hessian.

Identifying and quantifying the mechanisms influencing species coexistence remains a major challenge for the study of community ecology. These mechanisms, which stem from species' differential responses to competition and their environments, promote coexistence if they give each species a growth advantage when rare. Yet despite the widespread assumption that co-occurring species stably coexist, there have been few empirical demonstrations in support of this claim. Likewise, coexistence is often assumed to result from interspecific differences in life-history traits, but the relative contributions of these trait differences to coexistence are rarely quantified, particularly across environmental gradients. Using two widely co-occurring and ecologically similar species of freshwater duckweed plants (Spirodela polyrhiza and Lemna minor), we tested hypotheses that interspecific differences in facultative dormancy behaviors, thermal reaction norms, and density-dependent growth promote coexistence between these species, and that their relative influences on coexistence change as average temperatures and fluctuations around them vary. In competition experiments, we found strong evidence for negative frequency-dependent growth across a range of both static and fluctuating temperatures, suggesting a critical role of fluctuation-independent stabilization in coexistence. This negative frequency dependence could be explained by our observation that for both species, intraspecific competition was over 1.5 times stronger than interspecific competition, granting each species a low-density growth advantage. Using an empirically parameterized competition model, we found that while coexistence was facilitated by environmental fluctuations, fluctuation-independent stabilization via negative frequency dependence was crucial for coexistence. Conversely, the temporal storage effect, an important fluctuation-dependent mechanism, was relatively weak in comparison. Contrary to expectations, differences in the species' thermal reaction norms and dormancy behaviors did not significantly promote coexistence in fluctuating environments. Our results highlight how coexistence in two ubiquitous and ostensibly similar aquatic plants is not necessarily a product of their most obvious interspecific differences, and instead results from subtle niche differences causing negative frequency-dependent growth, which acts consistently on both species across environmental gradients.

Ecosystem development theory predicts that successional turnover in community composition can influence ecosystem functioning. However, tests of this theory in natural systems are made difficult by a lack of replicable and tractable model systems. Using the microbial digestive associates of a carnivorous pitcher plant, I tested hypotheses linking host age-driven microbial community development to host functioning. Monitoring the yearlong development of independent microbial digestive communities in two pitcher plant populations revealed a number of trends in community succession matching theoretical predictions. These included mid-successional peaks in bacterial diversity and metabolic substrate use, predictable and parallel successional trajectories among microbial communities, and convergence giving way to divergence in community composition and carbon substrate use. Bacterial composition, biomass, and diversity positively influenced the rate of prey decomposition, which was in turn positively associated with a host leaf’s nitrogen uptake efficiency. Overall digestive performance was greatest during late summer. These results highlight links between community succession and ecosystem functioning and extend succession theory to host-associated microbial communities.Statement of authorshipDWA conceived this work, performed data collection and analysis, and wrote the manuscript

This paper describes the design, assembly and fleld testing of a LHCP (Left Hand Circularly Polarized) high gain helical antenna. The antenna is to be utilized for the reception of re∞ected Global Positioning System (GPS) signals, which are correlated with the direct signals to form an image of the area of interest. Thus the antenna forms a constituent element of a remote imaging system. Owing to the low power of the re∞ected GPS signals the major design parameter was obviously high gain, while maintaining the polarization integrity of re∞ected GPS signals.

Bacteria are hypothesized to provide a variety of beneficial functions to plants. Many carnivorous pitcher plants, for example, rely on bacteria for digestion of captured prey. This bacterial community may also be responsible for the low surface tensions commonly observed in pitcher plant digestive fluids, which might facilitate prey capture. I tested this hypothesis by comparing the physical properties of natural pitcher fluid from the pitcher plant Darlingtonia californica and cultured 'artificial' pitcher fluids and tested these fluids' prey retention capabilities. I found that cultures of pitcher leaves' bacterial communities had similar physical properties to raw pitcher fluids. These properties facilitated the retention of insects by both fluids and hint at a previously undescribed class of plant-microbe interaction.

The historical exclusion of fire from the longleaf pine–wiregrass (sandhills) ecosystem has resulted in a tremendous net loss of this important habitat. Prescribed fire is recognized as an essential tool for the maintenance of natural successional dynamics in this system, and its positive effects on native tree, shrub, and ground-layer plant communities are well documented. However, little is known about the influence of fire periodicity on many of the wildlife species occupying these forests. Our goal was to determine the relative degree to which a forest’s structural characteristics and insect abundance and biomass influence the activity of different ecomorphological guilds of insectivorous bats and whether either of these factors was influenced by the periodicity of prescribed fire. We conducted a 2-year echolocation-monitoring study of bats in sandhills forests experiencing 3 categories of fire periodicity: 1–2 years, 3–5 years, and .8 years. We found significant differences in tree, shrub, and ground-layer characteristics among these burn-frequency categories, but few differences in abundance or biomass of most orders of nocturnal insects. However, the biomass of Lepidoptera was greatest at sites with the longest time between burns and was positively associated with fire-dependent deciduous tree and shrub densities. Bat activity below the canopy was significantly lower in the sites with .8year burn frequencies than in either of the other treatments and was positively associated with height of canopy closure (a fire-dependent variable). Species-specific activity patterns confirmed ecomorphological predictions. Small-bodied species with low wing loadings and aspect ratios replaced larger, less-maneuverable species below the canopy at sites with .8-year burn frequencies. We provide support for the hypothesis that the structural characteristics of a habitat have primacy over prey availability in habitat choice by large and fastflying species of bats. We suggest that frequency of fire is an important indirect determinant in structuring the communities of bats that forage in forests.

The two main graphite ageing processes in advanced gas-cooled reactors (AGRs) are fast neutron damage and radiolytic graphite oxidation. These processes change the properties of the graphite core and lead to a reduction in the graphite density, ie a weight loss. Electrical conductivity measurement of the graphite material is among the possible methods for estimating the weight loss and hence provides a measure of the graphite ageing. The inductance spectroscopy technique using eddy current sensors has been implemented in a wide variety of NDT applications, since it enables the possibility of extracting the electrical parameters variation from eddy current measurements and examining more fully the internal material structure. In this paper we present a non-contact eddy current method for determining non-destructively the electrical conductivity gradient through 100 mm-thick graphite sections using inductive spectroscopic measurements collected by a gradiometer. The method employs the commercial finite element software COMSOL to generate the data from a model of a real profile distribution. This data is translated to the profile conductivity of the graphite test object via the solution of an inverse problem. The linear Tikhonov regularisation method and the non-linear regularised Gauss Newton technique are employed in the solution of the inverse problem. During the optimisation, the forward problem is evaluated using COMSOL. Numerical optimisation tests have been carried out for different cases of step conductivity profiles. Initial results using simulated data show that representative estimates of the conductivity profile of the modelled graphite sections have been obtained.

This research endeavor reveals a method for utilizing reflected Global Positioning System (GPS) signals to form an image of targets within a region of interest. The principle is based upon a type of bistatic synthetic aperture radar (SAR) in which a matched filter technique is employed to perform the image reconstruction. A major challenge was the appalling signal to noise ratio associated with the received reflected GPS signals. Moreover, the reconstruction method resulted in an undesirable point spread function (PSF) which degraded the reconstructed image. The entire GPS signal generation and image reconstruction process was simulated as faithfully as possible and it has been demonstrated that a spatial resolution of the order of the GPS L1 frequency (wavelength of 19 cm) is possible. The smeared image obtained due to poor quality PSF was improved by means of a Wiener filter based deconvolution method. An imaging system based on a stationary receiver has been practically demonstrated with the successful identification of a 0.5 m 2 spherical target.

Premise of study Carnivorous pitcher plants employ a variety of putative adaptations for prey attraction and capture. One example is the peculiar forked "fishtail appendage", a foliar structure widely presumed to function as a prey attractant on adult leaves of Darlingtonia californica (Sarraceniaceae). This study tests the prediction that the presence of the appendage facilitates prey capture and can be considered an example of an adaptation to the carnivorous syndrome. Methods In a field experiment following a cohort of Darlingtonia leaves over their growing season, before the pitcher traps opened, the fishtail appendages from half of the leaves were removed. Additionally, all appendages were removed from every plant at two small, isolated populations. After 54 and 104 d, prey items were collected to determine whether differences in prey composition and biomass existed between experimental and unmanipulated control leaves. Key results Removal of the fishtail appendage did not reduce pitcher leaves' prey biomass nor alter their prey composition at either the level of individual leaves or entire populations. Fishtail appendages on plants growing in shaded habitats contained significantly greater chlorophyll concentrations than those on plants growing in full sun. Conclusions These results call into question the longstanding assumption that the fishtail appendage on Darlingtonia is an adaptation critical for the attraction and capture of prey. I suggest alternative evolutionary explanations for the role of the fishtail structure and repropose a hypothesis on the mutualistic nature of pitcher plant-arthropod trophic interactions.

Landmines and explosive remnants of war (ERW) are a serious problem in many countries around the world. In 2012, there were, on average, ten casualties per day globally [1]. Anti-Personnel (AP) landmines have been developed to have only a small amount of metal content, thus making them harder to find with metal detectors. Often there is less metal in a landmine than in “clutter” metallic objects, which are also found during the de-mining process. One reason landmine removal is a time-consuming task using the conventional metal detector is that it is not possible to classify the objects very accurately; consequently all positive signals must be investigated with equal caution. However, the dielectric material (e.g. main charge and plastic case) surrounding the metal detonator components generally occurs in landmines, and less so in clutter. Metal objects detected by a dual sensor without an associated detection of plastic objects can be ignored unless they are metal AP mines. One way to detect the plastic is to add a Ground Penetrating Radar system (GPR) to the conventional metal detector. Developments over the last decade combining GPR with traditional inductive metal detection have demonstrated the value of this approach [2]. GPR data is generally analysed by collating a series of reflection responses (A-Scans), collected over an evenly spaced series of positions in a single direction. This data set is termed a B-Scan. On conventional geotechnical GPR systems, a position encoder is attached to one of the wheels, in order to capture the data at regular intervals. Metal-detector type AP landmine detection systems are handheld devices without wheels, so some other way of detecting position needs to be found other than the operator's location. This paper describes an investigation into a positioning system for a handheld scanner. It describes how inertial measurements combined with a camera can determine the antenna position during the sensor sweep and how this information can be used to create the conventional B-Scan data sets. The paper compares the antenna-to-ground separation measurement extracted from both time and frequency domain GPR measurement systems to that given by an ultrasound distance sensor.

This paper presents an apparatus to measure the spectroscopic magnetic response of small metallic objects and deduce the magnetic polarizability tensor. The measured transimpedances of a .222 Remington rifle cartridge and titanium cube are compared to simulated results and are found to match well providing verification of the method. The eigenvalues of the two objects are calculated and discussed highlighting the potential discriminatory aspect. The results support the proposed use of the eigenvalue spectra to provide subsurface classification and discrimination between landmines and clutter.

This paper presents a method for the simulation of sensitivity maps from an array of coils. Some of the criteria necessary for designing a coil array capable of inversion of the magnetic polarisability are examined, and sensitivity maps are analysed with this in mind. The summarised sensitivity map for a single optimised array is presented, as well as the results of noise testing of an inversion algorithm using simulated measurements.Finally, a method for the construction and testing of such an array is presented.

The characteristic bio-impedance spectra of a biological sample can provide important information about its cellular structure, and further, infer useful information about the physical and chemical condition of the sample. In this paper, we present the background detail of a magnetic induction spectroscopy system for non-contact bio-impedance measurements, and some results using this system to obtain the relative permittivity spectra of a range of fruit and vegetable samples, over a frequency range from 160 kHz to 2.5 MHz. Relative permittivity is found to decrease with respect to frequency for each sample tested. This shows clear evidence of dispersion occurring within the samples across the investigated bandwidth.

This paper presents an apparatus to measure the spectroscopic magnetic response of small metallic objects and deduce the magnetic polarizability tensor. The measured transimpedances of a .222 Remington rifle cartridge and titanium cube are compared to simulated results and are found to match well providing verification of the method. The eigenvalues of the two objects are calculated and discussed highlighting the potential discriminatory aspect. The results support the proposed use of the eigenvalue spectra to provide subsurface classification and discrimination between landmines and clutter.

This paper presents a method for the simulation of sensitivity maps from an array of coils. Some of the criteria necessary for designing a coil array capable of inversion of the magnetic polarisability are examined, and sensitivity maps are analysed with this in mind. The summarised sensitivity map for a single optimised array is presented, as well as the results of noise testing of an inversion algorithm using simulated measurements. Finally, a method for the construction and testing of such an array is presented.

A walk-through metal detector system has been used for measuring the magnetic polarisability tensor for a variety of metallic objects. We propose a method for classifying objects by their metallic composition using features of the tensor. Furthermore, we investigate the potential of using the tensor representation as an indication geometric properties of the object. The method used is shown to be accurate for classification of material composition. Furthermore, the results suggest that it is possible to use the tensor to distinguish between similar objects of different sizes in limited scenarios. These findings demonstrate the potential for this method, but also suggest the need for further studies.

Biological tissues have a complex impedance, or bio-impedance, profile which changes with respect to frequency. This is caused by dispersion mechanisms which govern how the electromagnetic field interacts with the tissue at the cellular and molecular level. Measuring the bio-impedance spectra of a biological sample can potentially provide insight into the sample's properties and its cellular structure. This has obvious applications in the medical, pharmaceutical and food-based industrial domains. However, measuring the bio-impedance spectra non-destructively and in a way which is practical at an industrial scale presents substantial challenges. The low conductivity of the sample requires a highly sensitive instrument, while the demands of industrial-scale operation require a fast high-throughput sensor of rugged design. In this paper, we describe a multi-frequency magnetic induction spectroscopy (MIS) system suitable for industrial-scale, non-contact, spectroscopic bio-impedance measurement over a bandwidth of 156kHz-2.5MHz. The system sensitivity and performance are investigated using calibration and known reference samples. It is shown to yield rapid and consistently sensitive results with good long-term stability. The system is then used to obtain conductivity spectra of a number of biological test samples, including yeast suspensions of varying concentration and a range of agricultural produce, such as apples, pears, nectarines, kiwis, potatoes, oranges and tomatoes. © 2015 IOP Publishing Ltd.

Degradation of images due to atmospheric scattering is a phenomenon that causes problems in a number of imaging applications. By using knowledge of the scene geometry and a physical model of scattering, it is possible to apply a correction to remove the systematic effects of scattering. This paper describes a system that can perform atmospheric correction of colour PAL video in real time. Examples of the processed output are given for a static and an aircraft‐mounted camera, both in hazy conditions.

Sub-surface cracks present difficulties for eddy current methods as the skin effect causes currents to flow preferentially near the surface. This work examines graphite as a case study for the qualitative assessment of sub-surface cracks and employs multi-frequency eddy current techniques. The research has particular relevance to Advanced Gas-Cooled Reactors (AGRs) as during their operation there is the potential for cracks to develop within moderator bricks. This work reports that subsurface slots of 18% brick thickness can be detected. This work confirms these results with a parametric 3D finite element study. ?? 2014 Elsevier Ltd. cited By (since 1996)0

Walk-through metal detectors are used at check points for preventing personnel and passengers from carrying threatening metallic objects, such as knives and guns, into a secure area. These systems are capable of detecting small metallic items, such as handcuff keys and blades, but are unable to distinguish accurately between threatening objects and innocuous items. This paper studies the extent to which a K-nearest-neighbour classifier can distinguish various kinds of metallic objects, such as knives, shoe shanks, belts and containers. The classifier uses features extracted from the magnetic polarizability tensor, which represents the electromagnetic properties of the object. The tests include distinguishing threatening objects from innocuous ones, classifying a set of objects into 13 classes, and distinguishing between several similar objects within an object class. A walk-through metal detection system is used as source for the test data, which consist of 835 scans and 67 objects. The results presented show a typical success rate of over 95% for recognizing threats, and over 85% for correct classification. In addition, we have shown that the system is capable of distinguishing between similar objects reliably. Overall, the method shows promise for the field of security screening and suggests the need for further research. ?? 2014 IOP Publishing Ltd. cited By (since 1996)0

This chapter addresses the problem of identifying metallic objects in buried land mines and discriminating them from clutter using low-frequency electromagnetic induction (EMI) techniques. From dipolar fields, the magnetic polarizability tensor extracted from the target response can be used as a basis for identification. Here, a deterministic nonlinear optimization method is presented to estimate target polarizability matrix and location by fitting a dipole model to EMI data collected above target in a least squares sense. Using finite element simulated data with added synthetic low-frequency noise (10 dB SNR), results show initial guess misestimating target position with few centimeters in the transversal (x, y) plane can be corrected very close to the true location. The method is also able to estimate the polarizability tensor to within 12 % error of the true tensor.

Electromagnetic systems for imaging concealed objects at checkpoints typically employ radiation at millimetre and terahertz frequencies. These systems have been shown to be effective and provide a sufficiently high resolution image. However there are difficulties and current electromagnetic systems have limitations particularly in accurately differentiating between threat and innocuous objects based on shape, surface emissivity or reflectivity, which are indicative parameters. In addition, water has a high absorption coefficient at millimetre wavelength and terahertz frequencies, which makes it more difficult for these frequencies to image through thick damp clothing. This paper considers the potential of using ultra wideband (UWB) in the low gigahertz range. The application of this frequency band to security screening appears to be a relatively new field. The business case for implementing the UWB system has been made financially viable by the recent availability of low-cost integrated circuits operating at these frequencies. Although designed for the communication sector, these devices can perform the required UWB radar measurements as well. This paper reports the implementation of a 2 to 5 GHz bandwidth linear array scanner. The paper describes the design and fabrication of transmitter and receiver antenna arrays whose individual elements are a type of antipodal Vivaldi antenna. The antenna's frequency and angular response were simulated in CST Microwave Studio and compared with laboratory measurements. The data pre-processing methods of background subtraction and deconvolution are implemented to improve the image quality. The background subtraction method uses a reference dataset to remove antenna crosstalk and room reflections from the dataset. The deconvolution method uses a Wiener filter to sharpen the returned echoes which improves the resolution of the reconstructed image. The filter uses an impulse response reference dataset and a signal-to-noise parameter to determine how the frequencies contained in the echo dataset are normalised. The chosen image reconstruction algorithm is based on the back-projection method. The algorithm was implemented in MATLAB and uses a pre-calculated sensitivity matrix to increase the computation speed. The results include both 2D and 3D image datasets. The 3D datasets were obtained by scanning the dual sixteen element linear antenna array over the test object. The system has been tested on both humans and mannequin test objects. The front surface of an object placed on the human/mannequin torso is clearly visible, but its presence is also seen from a tell-tale imaging characteristic. This characteristic is caused by a reduction in the wave velocity as the electromagnetic radiation passes through the object, and manifests as an indentation in the reconstructed image that is readily identifiable. The prototype system has been shown to easily detect a 12 mm x 30 mm x70 mm plastic object concealed under clothing. ?? 2013 SPIE. cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@14aeb45e ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@59c391ed Through org.apache.xalan.xsltc.dom.DOMAdapter@36a18ca5; Conference Code:101239

A tomographic metal detection and characterization system has been designed and built for recovering information about magnetic and/or conductive objects within the detector space. This information is gathered as a result of a 'walk-through' scan of a candidate in the same manner as for a typical security metal detector archway. Following the passage of the candidate, the system uses measurements from an array of coils to calculate the polarizability tensor, which describes the low frequency electromagnetic characteristic of a small metallic object when it interacts with an ac magnetic field. In addition to the magnetic polarizability dyadic tensor, the position of the perturbation is also determined as a product of the inversion algorithm. The system has been tested and is capable of inverting object tensors with

The present application is a detection system for locating and characterizing an object placed in a detection area in a three dimensional space. The detection system includes a plurality of magnetic field generators and magnetic field detectors arranged on opposite sides of the detection area and a control system for enabling generation of a magnetic field in the detection area by the magnetic field generators and for measuring of the magnetic field modified by the object at each of the magnetic field detectors. The detection system also includes a processor for processing the measured magnetic field to obtain a data set characterizing the object and a location of the object. The processor applies a reconstruction process on a predefined number of measurements of the modified magnetic field.

Bacteria are hypothesized to provide a variety of beneficial functions to plants. Many carnivorous pitcher plants, for example, rely on bacteria for digestion of captured prey. This bacterial community may also be responsible for the low surface tensions commonly observed in pitcher plant digestive fluids, which might facilitate prey capture. I tested this hypothesis by comparing the physical properties of natural pitcher fluid from the pitcher plant Darlingtonia californica and cultured ‘artificial’ pitcher fluids and tested these fluids' prey retention capabilities. I found that cultures of pitcher leaves' bacterial communities had similar physical properties to raw pitcher fluids. These properties facilitated the retention of insects by both fluids and hint at a previously undescribed class of plant–microbe interaction.