Confocal microscopic image sequence compression using vector quantization and 3D pyramids

The 3D pyramid compressor project at the University of Glasgow has developed a compressor for images obtained from CLSM device. The proposed method using a combination of image pyramid coder and vector quantization techniques has good performance at compressing confocal volume image data. An experiment was conducted on several kinds of CLSM data using the presented compressor compared to other well-known volume data compressors, such as MPEG-1. The results showed that the 3D pyramid compressor gave higher subjective and objective image quality of reconstructed images at the same compression ratio and presented more acceptable results when applying image processing filters on reconstructed images

‘‘There’s so much more to it than what I initially thought’’: Stepping into researchers’ shoes with a class activity in a first year psychology survey course

In psychology, it is widely agreed that research methods, although central to the discipline, are particularly challenging to learn and teach, particularly at introductory level. This pilot study explored the potential of embedding a student-conducted research activity in a one-semester undergraduate Introduction to Psychology survey course, with the aims of (a) engaging students with the topic of research methods; (b) developing students’ comprehension and application of research methods concepts; and (c) building students’ ability to link research with theory. The research activity explored shoe ownership, examining gender differences and relationships with age, and linking to theories of gender difference and of consumer identity. The process of carrying out the research and reflecting on it created a contextualized, active learning environment in which students themselves raised many issues that research methods lectures seek to cover. Students also wrote richer assignments than standard first year mid-term essay

Helicopter tail rotor thrust and main rotor wake coupling in crosswind flight

The tail rotor of a helicopter with a single main rotor configuration can experience a significant reduction in thrust when the aircraft operates in crosswind flight. Brown’s vorticity transport model has been used to simulate a main rotor and tail rotor system translating at a sideslip angle that causes the tail rotor to interact with the main rotor tip vortices as they propagate downstream at the lateral extremities of the wake. The tail rotor is shown to exhibit a distinct directionally dependent mode during which tail rotors that are configured so that the blades travel forward at the top of the disk develop less thrust than tail rotors with the reverse sense of rotation. The range of flight speeds over which this mode exists is shown to vary considerably with the vertical location of the tail rotor. At low flight speeds, the directionally dependent mode occurs because the tail rotor is immersed within not only the downwash from the main rotor but also the rotational flow associated with clusters of largely disorganized vorticity within the main rotor wake. At higher flight speeds, however, the tail rotor is immersed within a coherent supervortex that strongly influences the velocity field surrounding the tail rotor

A gray-box model for a probabilistic estimate of regional ground magnetic perturbations: Enhancing the NOAA operational Geospace model with machine learning

We present a novel algorithm that predicts the probability that the time derivative of the horizontal component of the ground magnetic field $dB/dt$ exceeds a specified threshold at a given location. This quantity provides important information that is physically relevant to Geomagnetically Induced Currents (GIC), which are electric currents { associated to} sudden changes in the Earth's magnetic field due to Space Weather events. The model follows a 'gray-box' approach by combining the output of a physics-based model with machine learning. Specifically, we combine the University of Michigan's Geospace model that is operational at the NOAA Space Weather Prediction Center, with a boosted ensemble of classification trees. We discuss the problem of re-calibrating the output of the decision tree to obtain reliable probabilities. The performance of the model is assessed by typical metrics for probabilistic forecasts: Probability of Detection and False Detection, True Skill Statistic, Heidke Skill Score, and Receiver Operating Characteristic curve. We show that the ML enhanced algorithm consistently improves all the metrics considered.Comment: under revie

Low-energy elastic electron scattering by acetylene

We report measurements and first-principles calculations of the differential cross sections for elastic scattering of low-energy electrons by acetylene, C_2H_2, at collision energies from 1 to 100 eV, with an emphasis on energies near and below that of the π* shape resonance. The measurements cover angles from 5° to 130°. We compare our results to previous experimental and theoretical values

A technique for short‐term warning of solar energetic particle events based on flare location, flare size, and evidence of particle escape

We have developed a technique to provide short‐term warnings of solar energetic proton (SEP) events that meet or exceed the Space Weather Prediction Center threshold of J (>10 MeV) = 10 pr cm−2 s−1 sr−1. The method is based on flare location, flare size, and evidence of particle acceleration/escape as parameterized by flare longitude, time‐integrated soft X‐ray intensity, and time‐integrated intensity of type III radio emission at ∼1 MHz, respectively. In this technique, warnings are issued 10 min after the maximum of ≥M2 soft X‐ray flares. For the solar cycle 23 (1995–2005) data on which it was developed, the method has a probability of detection of 63% (47/75), a false alarm rate of 42% (34/81), and a median warning time of ∼55 min for the 19 events successfully predicted by our technique for which SEP event onset times were provided by Posner (2007). These measures meet or exceed verification results for competing automated SEP warning techniques but, at the present stage of space weather forecasting, fall well short of those achieved with a human (aided by techniques such as ours) making the ultimate yes/no SEP event prediction. We give some suggestions as to how our method could be improved and provide our flare and SEP event database in the auxiliary material to facilitate quantitative comparisons with techniques developed in the future