Identifying weak linear features with the "coalescing shortest path image transform"

The detection of line-like features in images finds many applications in microanalysis. Actin fibers, microtubules, neurites, pilis, DNA, and other biological structures all come up as tenuous curved lines in microscopy images. A reliable tracing method that preserves the integrity and details of these structures is particularly important for quantitative analyses. We have developed a new image transform called the "Coalescing Shortest Path Image Transform" with very encouraging properties. Our scheme efficiently combines information from an extensive collection of shortest paths in the image to delineate even very weak linear features. © Copyright Microscopy Society of America 2011.

Tubule detection in testis images using boundary weighting and circular shortest path

In studies of germ cell transplantation, measureing tubule diameters and counting cells from different populations using antibodies as markers are very important. Manual measurement of tubule sizes and cell counts is a tedious and sanity grinding work. In this paper, we propose a new boundary weighting based tubule detection method. We first enhance the linear features of the input image and detect the approximate centers of tubules. Next, a boundary weighting transform is applied to the polar transformed image of each tubule region and a circular shortest path is used for the boundary detection. Then, ellipse fitting is carried out for tubule selection and measurement. The algorithm has been tested on a dataset consisting of 20 images, each having about 20 tubules. Experiments show that the detection results of our algorithm are very close to the results obtained manually. © 2013 IEEE.

User preferences for text message-delivered skin cancer prevention and early detection

Evidence is needed for the acceptability and user preferences of receiving skin cancer-related text messages. We prepared 27 questions to evaluate attitudes, satisfaction with program characteristics such as timing and spacing, and overall satisfaction with the Healthy Text program in young adults. Within this randomised controlled trial (age 18-42 years), 546 participants were assigned to one of three Healthy Text message groups; sun protection, skin self-examination, or attention-control. Over a 12-month period, 21 behaviour-specific text messages were sent to each group. Participants’ preferences were compared between the two interventions and control group at the 12-month follow-up telephone interview. In all three groups, participants reported the messages were easy to understand (98%), provided good suggestions or ideas (88%), and were encouraging (86%) and informative (85%) with little difference between the groups. The timing of the texts was received positively (92%); however, some suggestions for frequency or time of day the messages were received from 8% of participants. Participants in the two intervention groups found their messages more informative, and triggering behaviour change compared to control. Text messages about skin cancer prevention and early detection are novel and acceptable to induce behaviour change in young adults.

Effects of magnetite on high-frequency ground-penetrating radar

Large concentrations of magnetite in sedimentary deposits and soils with igneous parent material have been reported to affect geophysical sensor performance. We have undertaken the first systematic experimental effort to understand the effects of magnetite for ground-penetrating radar (GPR) characterization of the shallow subsurface. Laboratory experiments were conducted to study how homogeneous magnetite-sand mixtures and magnetite concentrated in layers affect the propagation behavior (velocity, attenuation) of high-frequency GPR waves and the reflection characteristics of a buried target. Important observations were that magnetite had a strong effect on signal velocity and reflection, at magnitudes comparable to what has been observed in small-scale laboratory experiments that measured electromagnetic properties of magnetite-silica mixtures. Magnetite also altered signal attenuation and affected the reflection characteristics of buried targets. Our results indicated important implications for several fields, including land mine detection, Martian exploration, engineering, and moisture mapping using satellite remote sensing and radiometers.

Toward a model for predicting magnetic susceptibility of bedrock regolith and soils

One of the Department of Defense's most pressing environmental problems is the efficient detection and identification of unexploded ordnance (UXO). In regions of highly magnetic soils, magnetic and electromagnetic sensors often detect anomalies that are of geologic origin, adding significantly to remediation costs. In order to develop predictive models for magnetic susceptibility, it is crucial to understand modes of formation and the spatial distribution of different iron oxides. Most rock types contain iron and their magnetic susceptibility is determined by the amount and form of iron oxides present. When rocks weather, the amount and form of the oxides change, producing concomitant changes in magnetic susceptibility. The type of iron oxide found in the weathered rock or regolith is a function of the duration and intensity of weathering, as well as the original content of iron in the parent material. The rate of weathering is controlled by rainfall and temperature; thus knowing the climate zone, the amount of iron in the lithology and the age of the surface will help predict the amount and forms of iron oxide. We have compiled analyses of the types, amounts, and magnetic properties of iron oxides from soils over a wide climate range, from semi arid grasslands, to temperate regions, and tropical forests. We find there is a predictable range of iron oxide type and magnetic susceptibility according to the climate zone, the age of the soil and the amount of iron in the unweathered regolith.

Soil Magnetism Research: State of the Art and Future Directions

Magnetic properties of soils have been highlighted as a primary detrimental environmental effect on the performance of geophysical systems for detection of unexploded ordnance (UXO) and mine targets. A recent workshop at Cranfield University, U.K., aimed to identify knowledge gaps related to soil magnetism. Eight invited speakers from multidisciplinary areas provided briefings on state‐of‐the‐art research linked to soil magnetism and geophysical sensing. Contributions from other participants provided additional insights from a range of disciplines through case studies and applications. The workshop included break‐out sessions to identify current gaps in knowledge and to determine priority areas for investment in research to further developments in UXO and mine detection in magnetic soil environments. Key recommendations for future research investments have been grouped in categories including soils, theory and modeling, instrumentation, and communication.

Structural damage detection method using frequency response functions

Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.

Physical, chemical, biological and ecotoxicological properties of wastewater discharged from Davis Station, Antarctica

The properties and toxicity of untreatedwastewater at Davis Station, East Antarctica,were investigated to inform decisions regarding the appropriate level of treatment for local discharge purposes and more generally, to better understand the risk associated with dispersal and impact of wastewaters in Antarctica. Suspended solids, nutrients (nitrogen, phosphorus), biological oxygen demand (BOD), metals, organic contaminants, surfactants and microbiological load were measured at various locations throughout the wastewater discharge system. Wastewater quality and properties varied greatly between buildings on station, each ofwhich has separate holding tanks. Nutrients, BOD and settleable solid levelswere higher than standard municipal wastewaters. Microbiological loads were typical of untreated wastewater. Contaminants detected in the wastewater included metals and persistent organic compounds, mainly polybrominated diphenyl ethers (PBDEs). The toxicity of wastewater was also investigated in laboratory bioassays using two local Antarctic marine invertebrates, the amphipod Paramoera walkeri and the microgastropod Skenella paludionoides. Animals were exposed to a range of wastewater concentrations from3% to 68% (test 1) or 63% (test 2) over 21 days with survival monitored daily. Significant mortality occurred in all concentrations of wastewater after 14 to 21 days, and at higher concentrations (50–68% wastewater) mortality occurred after only one day. Results indicate that the local receiving marine environment at Davis Station is at risk from existing wastewater discharges, and that advanced treatment is required both to remove contaminants shown to cause toxicity to biota, as well as to reduce the environmental risks associated with non-native micro-organisms in wastewater.