Scott Sommerfeldt Elected ASA President

The role of nozzle configuration on rocket noise radiation is not well understood, particularly for multi-core vehicles where plume interactions may introduce azimuthal asymmetry. While tightly clustered engines are often assumed to radiate axisymmetrically, configurations with spaced nozzles may exhibit directionally dependent acoustic fields. This paper presents results from a measurement campaign conducted during the final Delta IV Heavy launch (NROL-70), supplemented by data from a previous launch (NROL-82), to investigate azimuthal variation in radiated noise. Measurements spanning a wide range of azimuthal angles show a consistent increase in sound pressure and sound power levels along the jet midplane relative to the jet plane. In sound pressure levels, differences of 5 dB are observed near the dominant spectral frequency (~30 Hz). In sound power, differences of ~2.5 dB are observed, particularly around the peak frequency, with smaller but persistent differences at higher frequencies. Strouhal number analysis indicates that the effective source length scale lies between the limits of fully independent and fully merged plumes, suggesting a partially merged interaction regime. These results provide field-scale evidence that multi-core rocket plumes do not behave as independent or fully merged sources but instead form partially coupled turbulent structures that produce directionally dependent acoustic radiation. The findings demonstrate that azimuthal asymmetry in large rocket noise is both angle and frequency dependent and should be considered in modeling of launch acoustics.

AB  - The role of nozzle configuration on rocket noise radiation is not well understood, particularly for multi-core vehicles where plume interactions may introduce azimuthal asymmetry. While tightly clustered engines are often assumed to radiate axisymmetrically, configurations with spaced nozzles may exhibit directionally dependent acoustic fields. This paper presents results from a measurement campaign conducted during the final Delta IV Heavy launch (NROL-70), supplemented by data from a previous launch (NROL-82), to investigate azimuthal variation in radiated noise. Measurements spanning a wide range of azimuthal angles show a consistent increase in sound pressure and sound power levels along the jet midplane relative to the jet plane. In sound pressure levels, differences of 5 dB are observed near the dominant spectral frequency (~30 Hz). In sound power, differences of ~2.5 dB are observed, particularly around the peak frequency, with smaller but persistent differences at higher frequencies. Strouhal number analysis indicates that the effective source length scale lies between the limits of fully independent and fully merged plumes, suggesting a partially merged interaction regime. These results provide field-scale evidence that multi-core rocket plumes do not behave as independent or fully merged sources but instead form partially coupled turbulent structures that produce directionally dependent acoustic radiation. The findings demonstrate that azimuthal asymmetry in large rocket noise is both angle and frequency dependent and should be considered in modeling of launch acoustics.

Vertically aligned carbon nanotube forest growth uses a thin-film iron catalyst on an alumina support. The iron catalyst thickness (typically, 1–10 nm) strongly affects forest morphology. We explored the use of spectroscopic ellipsometry (SE) as a rapid, sensitive, and nondestructive metrology method for these films. SE does have challenges, however, as it is difficult to break the correlation in the analysis between fitted optical constants and thickness of ultrathin films. Partial oxidation and optical absorption in the iron–iron oxide films add further complexity. We performed a multisample SE analysis of thermally evaporated iron films with target thicknesses of 1–14 nm. To improve sensitivity, we used interference enhancement by incorporating a 350 nm silica film on a silicon substrate beneath the iron film and alumina support. We used a consecutive-layer approach, collecting SE data and fitting the optical constants and thickness of each film before depositing the next. The iron–iron oxide film was modeled with an effective medium approximation layer. The model fit the data well with a mean squared error of 25. From the SE results, we estimated the thickness of the iron film before oxidation (“equivalent iron thickness”). We found that SE is highly sensitive to equivalent iron thickness and yields repeatable thickness measurements (ca. ±0.015 nm). We determined that the equivalent iron thickness variation we observed across different measurement locations on the same sample can be explained by error propagation from uncertainty in the underlying alumina thickness.

Background

Recent personalized nutrition research has reported large inter-individual differences in postprandial glucose responses to identical foods, raising questions about whether these differences reflect food-specific personal effects or normal day-to-day variability in glucose tolerance.

Objectives

To quantify the relative contributions of measurement variability vs person-specific effects to inter-individual glycemic variation, and to define substitution thresholds for when glycemic index (GI) differences produce distinct physiological effects.

Methods

In this secondary analysis with simulated validation, data from 382 healthy adults (1,022 glucose reference tests, 1,116 food tests across 9 carbohydrate-rich foods) were analyzed using a direct comparison scaling model, in which an individual's food response equals their glucose reference response scaled by the food's average GI. Sensitivity analyses included single-reference predictions, restriction to participants with ≥3 reference tests, and exclusion of a protocol-deviating food.

Results

Predicted errors did not exceed the observed glucose reference test-retest variability (mean root mean square deviation [RMSD]: 0.78 vs. 1.02 mmol/L; Cohen's d = 0.54 [0.45, 0.63]), with ∼90% of predictions falling within each participant's own test-retest range. Bland-Altman analysis confirmed negligible systematic bias (-0.01 mmol/L). Synthetic datasets generated from glucose variability and average GI values reproduced observed response distributions without person-specific parameters. GI differences of ≥15 units produced reliably distinguishable responses in a given individual. All sensitivity analyses yielded equal or stronger effect sizes.

Conclusions

In healthy adults under standardized conditions, inter-individual variation in glycemic responses is predominantly accounted for by variability in day-to-day glucose tolerance, propagating through the GI ratio. The GI concept performs within the reproducibility limits of input data.

We present the ground-based imaging campaign and light curves of Markarian 817 as part of the multiwavelength monitoring program AGN STORM 2. Observations were carried out over 1.4 yr in the uBgVriz filters, with a median cadence of 0.4 day in the g band. Reverberation lags are measured using three methods (interpolated cross-correlation function (ICCF), Just Another Vehicle for Estimating Lags In Nuclei, and PyROA) with the Swift UVW2 band (1928 Å) as the reference light curve. The ICCF centroid lags range from 3.0 ± 0.8 days for the u band up to 7.9 ± 1.5 days for z, and are consistent with a τ ∝ λ^4/3 dependence, the relation expected for lamppost reprocessing by a Shakura–Sunyaev disk. Lags measured with the other methods are systematically shorter, and deviate from a λ^4/3 power-law spectrum at long wavelengths. The lags exceed thin-disk reprocessing predictions by factors of ∼3–6, similar to the “disk size discrepancy” seen in other Seyfert galaxies. We divide the campaign into three epochs with different levels of mean luminosity and X-ray obscuring column density and find that the lags vary by as much as a factor of 2 between epochs. The intrinsic spectral energy distribution is bluer and brighter during the first third of the campaign, and the longest continuum reverberation lags are obtained during that period. These results suggest that changes in ionizing luminosity can produce large variations in continuum lags on short timescales by altering the diffuse continuum luminosity emitted by the broad-line region (BLR) and/or obscuring outflow, although changes in obscuration between the central engine and BLR may also contribute to the lag variations.

We report on the observation and measurement of astrometry, photometry, morphology, and activity of the interstellar object 3I/ATLAS, also designated C/2025 N1 (ATLAS) with the NSF-DOE Vera C. Rubin Observatory. Comet 3I/ATLAS, the third known interstellar object, was discovered on UT 2025 July 1. Rubin Observatory had coincidentally collected images of the object’s region of the sky during routine commissioning. Facilitated by Rubin’s high resolution and large aperture, we successfully recovered object detections from Rubin observations spanning UT 2025 June 21 (10 days before discovery, when 3I/ATLAS was 4.5 au from the Sun) through the date of discovery, and we acquired additional images through UT 2025 July 20 as part of commissioning. We measure on-sky locations of 3I/ATLAS in Rubin ugrizy bands, with a typical precision of ∼70 mas, and briefly describe the reason this is coarser than our measured static source astrometric precision of ∼3 mas in Rubin images. We measure grizy magnitudes of 3I/ATLAS photometry at ∼0.01 mag precision, detecting no short-term photometric variability above 0.01 mag. We derive an estimated near-nucleus dust-to-nucleus scattering cross-sectional ratio of η ≳ 13 on UT 2025 July 2 based on Rubin photometry and an upper limit nucleus size computed from Hubble Space Telescope observations. We find Rubin colors of g − r =  (0.657 ± 0.013) mag, r − i =  (0.235 ± 0.018) mag, i − z = (0.147 ±  0.042) mag, and z − y =  (0.047 ± 0.052) mag. These data represent the earliest observations of this object by a large (≳8 m class) telescope and illustrate the type of measurements (and discoveries) Rubin’s Legacy Survey of Space and Time will provide after it begins in early 2026.

Artificial intelligence foundation models are increasingly deployed for prostate cancer Gleason grading, where GP3/GP4 distinction directly impacts treatment decisions (active surveillance vs. intervention). However, these models may achieve high validation accuracy by learning specimen-specific artifacts rather than generalizable biological features, limiting real-world clinical utility. We introduce PANDA-PLUS-Bench, a curated benchmark dataset derived from expertly annotated prostate biopsies designed specifically to quantify this failure mode. The benchmark comprises nine carefully selected whole slide images from nine unique patients containing diverse Gleason patterns, with non-overlapping tissue patches extracted at both 512 × 512 and 224 × 224-pixel resolutions across eight augmentation conditions. Using this benchmark, we evaluate seven foundation models (Virchow, Virchow2, UNI, UNI2, Phikon, Phikon-v2, and HistoEncoder) on their ability to separate biological signals from slide-level confounders. Our results reveal substantial variation in robustness across models: the Virchow models achieved the lowest slide-level encoding among large-scale models (slide ID accuracy: 80.7–81.0%), yet Virchow2 exhibited the lowest cross-slide accuracy (47.2%). HistoEncoder, trained specifically on prostate tissue, demonstrated the highest cross-slide accuracy (59.7%) and the strongest slide-level encoding (slide ID accuracy: 90.3%), suggesting tissue-specific training may enhance both biological feature capture and slide-specific signatures. All models exhibited measurable within-slide vs. cross-slide accuracy gaps, though the magnitude varied from 19.9 percentage points (HistoEncoder) to 26.9 percentage points (Phikon). We provide an open-source Google Colab notebook enabling researchers to evaluate additional foundation models against our benchmark using standardized metrics. PANDA-PLUS-Bench addresses a critical gap in foundation model evaluation by providing a purpose-built resource for robustness assessment in the clinically important context of Gleason grading.