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For the acoustic inference of lengths and orientation angles of Antarctic krill (krill), reliable theoretical acoustic scattering models and parameters are necessary. To measure the volume backscattering (SV) spectra, and to clarify if the spectral shapes of target strength (TS) predicted by the stochastic distorted-wave Born approximation-based deformed cylinder model (SDWBA-DCM) are in agreement with those of the measured SV, we conducted simultaneous sampling with a broadband echosounder and a rectangular midwater trawl targeting 9 aggregations in the eastern Indian sector of the Antarctic in the 2018/19 austral summer. The SV spectra were measured at 50–85 kHz and 95–255 kHz. Using the SDWBA-DCM and the length frequency distribution obtained from the trawl samples, the length-averaged TS spectra were predicted. Both spectra were normalized by SV and TS values at 120 kHz, respectively, and the relative frequency responses were compared. The spectral shapes were in reasonable agreement in the case of the aggregations dominated by krill smaller than 35 mm. On the other hand, in the case of the krill larger than 35 mm, the spectral shapes were not in agreement. The possible causes of the discrepancy included the orientation angle distribution and the shape of krill.

Triple-differential cross-sections for the positron impact ionization of argon were calculated using a distorted-wave Born approximation (DWBA) convoluted to the experimental uncertainties. In almost all of the cases studied, our results agree well with the positions and heights of the experimental peaks.

We review our group’s most significant results concerning the collision of positrons and electrons with small molecules. Total and triple differential cross sections for the ionization of these targets were calculated in the distorted wave Born approximation using Gaussian molecular orbitals. Different models were tested. The obtained theoretical results reproduced, in most cases, the features observed in the experimental data.

We built a new pulse-echo system using a small tank (1 × 1 × 1 m) for measuring the broadband target strength of weakly scattering animals such as krill and shrimp. The system transmits a linear frequency modulated signal with a frequency sweep of 20–220 kHz. To increase the signal-to-noise ratio (SNR), a very long (50 ms) signal is used, and pulse compression processing is applied to received echoes. To determine the accuracy and effectiveness of the system and method, the obtained measurements were compared with predictions by theoretical acoustic scattering models. According to the verification experiment for a sphere and cylinders, the mean absolute errors were < 0.30 dB and the correlation coefficients r were > 0.97 in the frequency range above 20-dB SNR (40–210 kHz for the cylinders). Our measurement system was thus very accurate. We then performed the experiment for a commercially important shrimp, sakura shrimp Lucensosergia lucens. The measured spectra of three samples (35–38 mm) were in good agreement with the predicted spectra using an assumed sound-speed contrast. The r values were > 0.88 in the frequency range above 20-dB SNR (approximately 110–190 kHz). The effectiveness of our new method for weakly scattering animals was confirmed.

Grazing-incidence small-angle X-ray scattering (GISAXS) is a powerful technique for measuring the nanostructure of coatings and thin films. However, GISAXS data are plagued by distortions that complicate data analysis. The detector image is a warped representation of reciprocal space because of refraction, and overlapping scattering patterns appear because of reflection. A method is presented to unwarp GISAXS data, recovering an estimate of the true undistorted scattering pattern. The method consists of first generating a guess for the structure of the reciprocal-space scattering by solving for a mutually consistent prediction from the transmission and reflection sub-components. This initial guess is then iteratively refined by fitting experimental GISAXS images at multiple incident angles, using the distorted-wave Born approximation (DWBA) to convert between reciprocal space and detector space. This method converges to a high-quality reconstruction for the undistorted scattering, as validated by comparing with grazing-transmission scattering data. This new method for unwarping GISAXS images will broaden the applicability of grazing-incidence techniques, allowing experimenters to inspect undistorted visualizations of their data and allowing a broader range of analysis methods to be applied to GI data.

Zooplankton can be detected by using acoustic Doppler current profiler (ADCP) instruments through acquiring the mean volume backscattering strength (MVBS) data. However, the precision of the backscattered signal measured by single ADCP measurement has a limitation in the MVBS variation of zooplankton. The objectives of this study were to analyze the MVBS and vertical velocity from ADCPs at the same time and location for zooplankton’s daily vertical migration (DVM) observation. Measurements were conducted in Lembeh Strait, North Sulawesi, Indonesia. Instruments used included a moored ADCP 750 kHz and a mobile ADCP 307.2 kHz. High MVBS value was found at 11.5–16 m depths and was identified as the sound scattering layer (SSL). The DVM patterns in the SSL displayed significant differences over time and had good relationships with the diurnal cycle. Theoretical target strength (TS) from the scattering models based on a distorted-wave Born approximation (DWBA) was estimated for Oithona sp. and Paracalanus sp.; the two dominant species found in the observed area. However, ΔMVBS and ΔTS proved that the dominant zooplankton species were not the main scatterers. The strong signal in SSL was instead caused by the schools of various zooplankton species.

A new 'unwarping' algorithm presented by Liu and Yager in this issue constructs SAXS data consistent with experimental GISAXS data, eliminating many of the complications arising in GISAXS that are commonly modeled within the framework of the distorted-wave Born approximation. The method promises to open new pathways for processing, modeling and analyzing GISAXS data using techniques developed for SAXS.