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Abstract Dialect differences between African American English (AAE) and Mainstream American English (MAE) impact how children comprehend sentences. However, research on real-time sentence processing has the potential to reveal the underlying causes of these differences. This study used eye tracking, which measures how children interpret linguistic features as a sentence unfolds, and examined how AAE- and MAE-speaking children processed “was” and “were,” a morphology feature produced differently in MAE and AAE. Fifty-nine participants, ages 7;8 to 11;0 years, completed standardized measures of dialect density and receptive vocabulary. In the eye tracking task, participants heard sentences in MAE with either unambiguous (e.g., “Jeremiah”) or ambiguous (e.g., “Carolyn May”), subjects and eye movements were measured to singular (image of one person) or plural referents (image of two people). After the onset of the auxiliary verb, AAE-speaking children were sensitive to “was” and “were” when processing sentences but were less likely than MAE-speaking children to use “was” as a basis for updating initial predictions of plural referents. Among African American children, dialect density was predictive of sensitivity to “was” when processing sentences. Results suggest that linguistic mismatch impacts how contrastive verb morphology is used to update initial interpretations of MAE sentences. 

Abstract A sensitive (1σrms ≤ 3 mK; 2 MHz resolution) 1 mm spectral survey (214.5–285.5 GHz) of the envelope of the oxygen-rich supergiant star NML Cygni (NML Cyg) has been conducted using the 10 m Submillimeter Telescope of the Arizona Radio Observatory. These data represent the first spectral line survey of NML Cyg and are complementary to a previous 1 mm survey of the envelope of a similar hypergiant, VY Canis Majoris (VY CMa). The complete NML Cyg data set is presented here. In the survey, 104 emission lines were observed, arising from 17 different molecules and 4 unidentified features. Many of the observed features have complex line profiles, arising from asymmetric outflows characteristic of hypergiant stars. While most of the lines in the survey arise from SiO, SO, SO₂, and SiS, CO had the strongest emission. Five other C-bearing species are identified in the survey (HCN, CN, HCO⁺, CS, and HNC), demonstrating an active carbon chemistry despite the O-rich environment. Moreover, NS was observed, but not NO, although favorable transitions of both molecules lie in the surveyed region. Sulfur chemistry appears to be prominent in NML Cyg and plays an important role in the collimated outflows. The refractory species observed, NaCl and AlO, have narrow emission lines, indicating that these molecules do not reach the terminal expansion velocity. NaCl and AlO likely condense into dust grains at r < 50R_*. From NaCl, the chlorine isotope ratio was determined to be³⁵Cl/³⁷Cl = 3.85 ± 0.30. 

Previous work identified an anthropogenic fingerprint pattern in 𝑇AC (𝑥, 𝑡), the amplitude of the seasonal cycle of mid- to upper tropospheric temperature (TMT), but did not explicitly consider whether fingerprint identification in satellite 𝑇AC(𝑥,𝑡) data could have been influenced by real-world multidecadal internal variability (MIV). We address this question here using large ensembles (LEs) performed with five climate models. LEs provide many different sequences of internal variability noise superimposed on an underlying forced signal. Despite differences in historical external forcings, climate sensitivity, and MIV properties of the five models, their 𝑇AC (𝑥, 𝑡) fingerprints are similar and statistically identifiable in 239 of the 240 LE realizations of historical climate change. Comparing simulated and observed variability spectra reveals that consistent fingerprint identification is unlikely to be biased by model underestimates of observed MIV. Even in the presence of large (factor of 3-4) inter-model and inter-realization differences in the amplitude of MIV, the anthropogenic fingerprints of seasonal cycle changes are robustly identifiable in models and satellite data. This is primarily due to the fact that the distinctive, global-scale fingerprint patterns are spatially dissimilar to the smaller-scale patterns of internal 𝑇AC(𝑥,𝑡) variability associated with the Atlantic Multidecadal Oscillation and the El Niño~Southern Oscillation. The robustness of the seasonal cycle D&A results shown here, taken together with the evidence fromidealized aquaplanet simulations, suggest that basic physical processes are dictating a common pattern of forced𝑇AC(𝑥,𝑡) changes in observations and in the five LEs. The key processes involved include GHG-induced expansion of the tropics, lapse-rate changes, land surface drying, and sea ice decrease.