Idealized Antenna Patterns for Use in Communication-satellite Interference Studies

Idealized antenna patterns for communication satellite interference studie

Expected-value bias in routine third-trimester growth scans.

OBJECTIVES: Operators performing fetal growth scans are usually aware of the gestational age of the pregnancy, which may lead to expected-value bias when performing biometric measurements. We aimed to evaluate the incidence of expected-value bias in routine fetal growth scans and assess its impact on standard biometric measurements. METHODS: We collected prospectively full-length video recordings of routine ultrasound growth scans coupled with operator eye tracking. Expected value was defined as the gestational age at the time of the scan, based on the estimated due date that was established at the dating scan. Expected-value bias was defined as occurring when the operator looked at the measurement box on the screen during the process of caliper adjustment before saving a measurement. We studied the three standard biometric planes on which measurements of head circumference (HC), abdominal circumference (AC) and femur length (FL) are obtained. We evaluated the incidence of expected-value bias and quantified the impact of biased measurements. RESULTS: We analyzed 272 third-trimester growth scans, performed by 16 operators, during which a total of 1409 measurements (354 HC, 703 AC and 352 FL; including repeat measurements) were obtained. Expected-value bias occurred in 91.4% of the saved standard biometric plane measurements (85.0% for HC, 92.9% for AC and 94.9% for FL). The operators were more likely to adjust the measurements towards the expected value than away from it (47.7% vs 19.7% of measurements; P < 0.001). On average, measurements were corrected by 2.3 ± 5.6, 2.4 ± 10.4 and 3.2 ± 10.4 days of gestation towards the expected gestational age for the HC, AC, and FL measurements, respectively. Additionally, we noted a statistically significant reduction in measurement variance once the operator was biased (P = 0.026). Comparing the lowest and highest possible estimated fetal weight (using the smallest and largest biased HC, AC and FL measurements), we noted that the discordance, in percentage terms, was 10.1% ± 6.5%, and that in 17% (95% CI, 12-21%) of the scans, the fetus could be considered as small-for-gestational age or appropriate-for-gestational age if using the smallest or largest possible measurements, respectively. Similarly, in 13% (95% CI, 9-16%) of scans, the fetus could be considered as large-for-gestational age or appropriate-for-gestational age if using the largest or smallest possible measurements, respectively. CONCLUSIONS: During routine third-trimester growth scans, expected-value bias frequently occurs and significantly changes standard biometric measurements obtained. © 2019 the Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology

Efficient Ultrasound Image Analysis Models with Sonographer Gaze Assisted Distillation.

Recent automated medical image analysis methods have attained state-of-the-art performance but have relied on memory and compute-intensive deep learning models. Reducing model size without significant loss in performance metrics is crucial for time and memory-efficient automated image-based decision-making. Traditional deep learning based image analysis only uses expert knowledge in the form of manual annotations. Recently, there has been interest in introducing other forms of expert knowledge into deep learning architecture design. This is the approach considered in the paper where we propose to combine ultrasound video with point-of-gaze tracked for expert sonographers as they scan to train memory-efficient ultrasound image analysis models. Specifically we develop teacher-student knowledge transfer models for the exemplar task of frame classification for the fetal abdomen, head, and femur. The best performing memory-efficient models attain performance within 5% of conventional models that are 1000× larger in size

Note: estimating the charge size in explosive forming of sheet metal

Note: Estimating the charge size in explosive forming of sheet metal In the explosive forming of sheet metal some relatively easy method of estimating the size of the charge is needed. This short note describes a method in which the size of the charge is found by equating the work done in forming the component to that part of the explosive energy available for doing work on the component … [cont]

If you can't be with the one you love, love the one you're with: How individual habituation of agent interactions improves global utility

Simple distributed strategies that modify the behaviour of selfish individuals in a manner that enhances cooperation or global efficiency have proved difficult to identify. We consider a network of selfish agents who each optimise their individual utilities by coordinating (or anti-coordinating) with their neighbours, to maximise the pay-offs from randomly weighted pair-wise games. In general, agents will opt for the behaviour that is the best compromise (for them) of the many conflicting constraints created by their neighbours, but the attractors of the system as a whole will not maximise total utility. We then consider agents that act as 'creatures of habit' by increasing their preference to coordinate (anti-coordinate) with whichever neighbours they are coordinated (anti-coordinated) with at the present moment. These preferences change slowly while the system is repeatedly perturbed such that it settles to many different local attractors. We find that under these conditions, with each perturbation there is a progressively higher chance of the system settling to a configuration with high total utility. Eventually, only one attractor remains, and that attractor is very likely to maximise (or almost maximise) global utility. This counterintutitve result can be understood using theory from computational neuroscience; we show that this simple form of habituation is equivalent to Hebbian learning, and the improved optimisation of global utility that is observed results from wellknown generalisation capabilities of associative memory acting at the network scale. This causes the system of selfish agents, each acting individually but habitually, to collectively identify configurations that maximise total utility

Sampling the Uppermost Surface of Airless Bodies

The uppermost surface of an airless body is a critical source of ground-truth information for the various remote sensing techniques that only penetrate nanometers to micrometers into the surface. Such samples will also be vital for understanding conditions at the surface and acquiring information about how the body interacts with its environment, including solar wind interaction, grain charging and levitation [1]. Sampling the uppermost surface while preserving its structure (e.g. porosity, grain-to-grain contacts) however, is a daunting task that has not been achieved on any sample return mission to date

Comparison of the telegraph and hyperdiffusion approximations in cosmic-ray transport

The telegraph equation and its generalizations have been repeatedly considered in the models of diffusive cosmic-ray transport. Yet the telegraph model has well-known limitations, and analytical arguments suggest that a hyperdiffusion model should serve as a more accurate alternative to the telegraph model, especially on the timescale of a few scattering times. We present a detailed side-by-side comparison of an evolving particle density profile, predicted by the telegraph and hyperdiffusion models in the context of a simple but physically meaningful initial-value problem, compare the predictions with the solution based on the Fokker–Planck equation, and discuss the applicability of the telegraph and hyperdiffusion approximations to the description of strongly anisotropic particle distributions

Nanoscale Compositional Relations in Lunar Rock Patina: Deciphering Sources for Patina Components on an Apollo 17 Station 6 Boulder

Space weathering on the Moon and other airless bodies modifies the surfaces of regolith grains as well as the space-exposed surfaces of larger rocks and boulders. As space weathering witness plates, rocks and boulders are distinguished from regolith grains based on their ability to persist as physically intact substrates over longer time scales before being disaggregated by impact processes. Because lunar surfaces, including exposed rocks, quickly develop an optically thick layer of patina, it is important to understand the compositional relationship between patinas and their underlying rock substrates, particularly to support remote-sensing of rocky lunar terrains. Based on analytical TEM techniques, supported by focused ion beam (FIB) cross-sectioning, we have begun to systematize the multi-layer microstructural complexity of patinas on rock samples with a range of space exposure histories. Our on-going work has particularly focused on lunar rock 76015, both because it has a long (approx. 22 my) exposure history, and because its surface was exposed to patina development approximately 1 m off the regolith surface on a boulder in the Apollo 17 Station 6 boulder field. Potential sources for the 76015 patina therefore include impact-melted and vaporized material derived from the local rock substrate, as well as from the mix of large boulders and regolith in the Station 6 area. While similar, there are differences in the mineralogy and chemistry of the rocks and regolith at Station 6. We were interested to see if these, or other sources, could be distinguished in the average composition, as well as the compositional nanostratigraphy of the 76015 patina. To date we have acquired a total of 9 TEM FIB cross-sections from the 76015 patina, giving us reasonable confidence of being able to arrive at an integrated average for the patina major element composition based on analytical TEM methods