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With a diverse sample of community college (CC) students (n = 94), we investigated how the working memory (WM)-math relation may be moderated by aspects of acculturation, including cultural adoption and cultural maintenance. We predicted that higher levels of each of the above acculturation factors would improve math performance by way of reducing WM load (via cognitive load). Conversely, we expected a weaker WM-math correlation at lower levels of acculturation due to the increased variability in cultural factors and the adverse effect of lower acculturation on WM through heightened cognitive load. In this cohort, WM correlated with math performance, but acculturation did not significantly influence this relationship. Neither cultural adoption nor cultural maintenance moderated the WM-math association. Results suggest that individualized educational interventions based on acculturation status alone may not be an effective strategy. Instead, institutions such as schools and governmental agencies may focus on providing a better foundation for educational success by enhancing academic and non-academic support systems to promote equitable educational opportunities for all students. Further research should explore additional individual and/or demographic factors (e.g. socioeconomic status, experiences of discrimination, cultural background) to better understand these complex relations. 

Abstract In dryland ecosystems, vegetation within different plant functional groups exhibits distinct seasonal phenologies that are affected by the prevailing hydroclimatic forcing. The seasonal variability of precipitation, atmospheric evaporative demand, and streamflow influences root-zone water availability to plants in water-limited environments. Increasing interannual variations in climate forcing of the local water balance and uncertainty regarding climate change projections have raised the potential for phenological shifts and changes to vegetation dynamics. This poses significant risks to plant functional types across large areas, especially in drylands and within riparian ecosystems. Due to the complex interactions between climate, water availability, and seasonal plant water use, the timing and amplitude of phenological responses to specific hydroclimate forcing cannot be determined a priori , thus limiting efforts to dynamically predict vegetation greenness under future climate change. Here, we analyze two decades (1994–2021) of remote sensing data (soil adjusted vegetation index (SAVI)) as well as contemporaneous hydroclimate data (precipitation, potential evapotranspiration, depth to groundwater, and air temperature), to identify and quantify the key hydroclimatic controls on the timing and amplitude of seasonal greenness. We focus on key phenological events across four different plant functional groups occupying distinct locations and rooting depths in dryland SE Arizona: semi-arid grasses and shrubs, xeric riparian terrace and hydric riparian floodplain trees. We find that key phenological events such as spring and summer greenness peaks in grass and shrubs are strongly driven by contributions from antecedent spring and monsoonal precipitation, respectively. Meanwhile seasonal canopy greenness in floodplain and terrace vegetation showed strong response to groundwater depth as well as antecedent available precipitation (aaP = P − PET) throughout reaches of perennial and intermediate streamflow permanence. The timings of spring green-up and autumn senescence were driven by seasonal changes in air temperature for all plant functional groups. Based on these findings, we develop and test a simple, empirical phenology model, that predicts the timing and amplitude of greenness based on hydroclimate forcing. We demonstrate the feasibility of the model by exploring simple, plausible climate change scenarios, which may inform our understanding of phenological shifts in dryland plant communities and may ultimately improve our predictive capability of investigating and predicting climate-phenology interactions in the future. 

Abstract Slow slip is part of the earthquake cycle, but the processes controlling this phenomenon in space and time are poorly constrained. Hematite, common in continental fault zones, exhibits unique textures and (U-Th)/He thermochronometry data patterns reflecting different slip rates. We investigated networks of small hematite-coated slip surfaces in basement fault damage of exhumed strike-slip faults that connect to the southern San Andreas fault in a flower structure in the Mecca Hills, California, USA. Scanning electron microscopy shows these millimeter-thick surfaces exhibit basal hematite injection veins and layered veinlets comprising nanoscale, high-aspect-ratio hematite plates akin to phyllosilicates. Combined microstructural and hematite (U-Th)/He data (n = 64 new, 24 published individual analyses) record hematite mineralization events ca. 0.8 Ma to 0.4 Ma at <1.5 km depth. We suggest these hematite faults formed via fluid overpressure, and then hematite localized repeated subseismic slip, creating zones of shallow off-fault damage as far as 4 km orthogonal to the trace of the southern San Andreas fault. Distributed hematite slip surfaces develop by, and then accommodate, transient slow slip, potentially dampening or distributing earthquake energy in shallow continental faults. 

Abstract The eccentricity of a substellar companion is an important tracer of its formation history. Directly imaged companions often present poorly constrained eccentricities. A recently developed prior framework for orbit fitting called “observable-based priors” has the advantage of improving biases in derived orbit parameters for objects with minimal phase coverage, which is the case for the majority of directly imaged companions. We use observable-based priors to fit the orbits of 21 exoplanets and brown dwarfs in an effort to obtain the eccentricity distributions with minimized biases. We present the objects’ individual posteriors compared to their previously derived distributions, showing in many cases a shift toward lower eccentricities. We analyze the companions’ eccentricity distribution at a population level, and compare this to the distributions obtained with the traditional uniform priors. We fit a Beta distribution to our posteriors using observable-based priors, obtaining shape parametersα= ${1.09}_{-0.22}^{+0.30}$andβ= ${1.42}_{-0.25}^{+0.33}$. This represents an approximately flat distribution of eccentricities. The derivedαandβparameters are consistent with the values obtained using uniform priors, though uniform priors lead to a tail at high eccentricities. We find that separating the population into high- and low-mass companions yields different distributions depending on the classification of intermediate-mass objects. We also determine via simulation that the minimal orbit coverage needed to give meaningful posteriors under the assumptions made for directly imaged planets is ≈15% of the inferred period of the orbit. 

Three protein targets from SARS-CoV-2, the viral pathogen that causes COVID-19, are studied: the main protease, the 2′-O-RNA methyltransferase, and the nucleocapsid (N) protein. For the main protease, the nucleophilicity of the catalytic cysteine C145 is enabled by coupling to three histidine residues, H163 and H164 and catalytic dyad partner H41. These electrostatic couplings enable significant population of the deprotonated state of C145. For the RNA methyltransferase, the catalytic lysine K6968 that serves as a Brønsted base has significant population of its deprotonated state via strong coupling with K6844 and Y6845. For the main protease, Partial Order Optimum Likelihood (POOL) predicts two clusters of biochemically active residues; one includes the catalytic H41 and C145 and neighboring residues. The other surrounds a second pocket adjacent to the catalytic site and includes S1 residues F140, L141, H163, E166, and H172 and also S2 residue D187. This secondary recognition site could serve as an alternative target for the design of molecular probes. From in silico screening of library compounds, ligands with predicted affinity for the secondary site are reported. For the NSP16-NSP10 complex that comprises the RNA methyltransferase, three different sites are predicted. One is the catalytic core at the conserved K-D-K-E motif that includes catalytic residues D6928, K6968, and E7001 plus K6844. The second site surrounds the catalytic core and consists of Y6845, C6849, I6866, H6867, F6868, V6894, D6895, D6897, I6926, S6927, Y6930, and K6935. The third is located at the heterodimer interface. Ligands predicted to have high affinity for the first or second sites are reported. Three sites are also predicted for the nucleocapsid protein. This work uncovers key interactions that contribute to the function of the three viral proteins and also suggests alternative sites for ligand design.