Observations of radiocarbon (14C) in Earth’s atmosphere and other carbon reservoirs are important to quantify exchanges of CO2 between reservoirs. The amount of 14C is commonly reported in the so-called Delta notation, i.e., Δ14C, the decay- and fractionation-corrected departure of the ratio of 14C to total C from that ratio in an absolute international standard; this Delta notation permits direct comparison of 14C/C ratios in the several reservoirs. However, as Δ14C of atmospheric CO2, Δ14CO2 is based on the ratio of 14CO2 to total atmospheric CO2, its value can and does change not just because of change in the amount of atmospheric14CO2 but also because of change in the amount of total atmospheric CO2, complicating ascription of change in Δ14CO2 to change in one or the other quantity. Here we suggest that presentation of atmospheric 14CO2 amount as mole fraction relative to dry air (moles of 14CO2 per moles of dry air in Earth’s atmosphere), or as moles or molecules of 14CO2 in Earth’s atmosphere, all readily calculated from Δ14CO2 and the amount of atmospheric CO2 (with slight dependence on δ13CO2), complements presentation only as Δ14CO2, and can provide valuable insight into the evolving budget and distribution of atmospheric 14CO2.

Clinical outcomes of repetitive transcranial magnetic stimulation (rTMS) for treatment of treatment-resistant depression (TRD) vary widely and there is no mood rating scale that is standard for assessing rTMS outcome. It remains unclear whether TMS is as efficacious in older adults with late-life depression (LLD) compared to younger adults with major depressive disorder (MDD). This study examined the effect of age on outcomes of rTMS treatment of adults with TRD. Self-report and observer mood ratings were measured weekly in 687 subjects ages 16–100 years undergoing rTMS treatment using the Inventory of Depressive Symptomatology 30-item Self-Report (IDS-SR), Patient Health Questionnaire 9-item (PHQ), Profile of Mood States 30-item, and Hamilton Depression Rating Scale 17-item (HDRS). All rating scales detected significant improvement with treatment; response and remission rates varied by scale but not by age (response/remission ≥ 60: 38%–57%/25%–33%; <60: 32%–49%/18%–25%). Proportional hazards models showed early improvement predicted later improvement across ages, though early improvements in PHQ and HDRS were more predictive of remission in those < 60 years (relative to those ≥ 60) and greater baseline IDS burden was more predictive of non-remission in those ≥ 60 years (relative to those < 60). These results indicate there is no significant effect of age on treatment outcomes in rTMS for TRD, though rating instruments may differ in assessment of symptom burden between younger and older adults during treatment.

Emergency departments are high-risk settings for severe acute respiratory coronavirus virus 2 (SARS-CoV-2) surface contamination. Environmental surface samples were obtained in rooms with patients suspected of having COVID-19 who did or did not undergo aerosol-generating procedures (AGPs). SARS-CoV-2 RNA surface contamination was most frequent in rooms occupied by coronavirus disease 2019 (COVID-19) patients who received no AGPs.

The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.

A closed-form solution is presented for internal compressible flows with an arbitrary combination of area change, heat addition, friction and non-uniform flow. The approach assumes steady flow of a calorically perfect ideal gas using the integral form of the governing equations. It is shown that the equations reduce to a simple, bi-quadratic equation in exit Mach number. This solution is compared to previously known solutions for Rayleigh flow, Fanno flow, isentropic flow and normal shock relations. Theoretical solutions for sudden expansion, sudden contraction, and supersonic–supersonic two-stream constant area mixing are also presented. These solutions were found to be in agreement with data available in the literature.

Despite extensive paleoenvironmental research on the postglacial history of the Kenai Peninsula, Alaska, uncertainties remain regarding the region's deglaciation, vegetation development, and past hydroclimate. To elucidate this complex environmental history, we present new proxy datasets from Hidden and Kelly lakes, located in the eastern Kenai lowlands at the foot of the Kenai Mountains, including sedimentological properties (magnetic susceptibility, organic matter, grain size, and biogenic silica), pollen and macrofossils, diatom assemblages, and diatom oxygen isotopes. We use a simple hydrologic and isotope mass balance model to constrain interpretations of the diatom oxygen isotope data. Results reveal that glacier ice retreated from Hidden Lake's headwaters by ca. 13.1 cal ka BP, and that groundwater was an important component of Kelly Lake's hydrologic budget in the Early Holocene. As the forest developed and the climate became wetter in the Middle to Late Holocene, Kelly Lake reached or exceeded its modern level. In the last ca. 75 years, rising temperature caused rapid changes in biogenic silica content and diatom oxygen isotope values. Our findings demonstrate the utility of mass balance modeling to constrain interpretations of paleolimnologic oxygen isotope data, and that groundwater can exert a strong influence on lake water isotopes, potentially confounding interpretations of regional climate.

Crystalline materials used in technological applications are often complex assemblies composed of multiple phases and differently oriented grains. Robust identification of the phases and orientation relationships from these samples is crucial, but the information extracted from the diffraction condition probed by an electron beam is often incomplete. We have developed an automated crystal orientation mapping (ACOM) procedure which uses a converged electron probe to collect diffraction patterns from multiple locations across a complex sample. We provide an algorithm to determine the orientation of each diffraction pattern based on a fast sparse correlation method. We demonstrate the speed and accuracy of our method by indexing diffraction patterns generated using both kinematical and dynamical simulations. We have also measured orientation maps from an experimental dataset consisting of a complex polycrystalline twisted helical AuAgPd nanowire. From these maps we identify twin planes between adjacent grains, which may be responsible for the twisted helical structure. All of our methods are made freely available as open source code, including tutorials which can be easily adapted to perform ACOM measurements on diffraction pattern datasets.

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

The Late Formative period immediately precedes the emergence of Tiwanaku, one of the earliest South American states, yet it is one of the most poorly understood periods in the southern Lake Titicaca Basin (Bolivia). In this article, we refine the ceramic chronology of this period with large sets of dates from eight sites, focusing on temporal inflection points in decorated ceramic styles. These points, estimated here by Bayesian models, index specific moments of change: (1) cal AD 120 (60–170, 95% probability): the first deposition of Kalasasaya red-rimmed and zonally incised styles; (2) cal AD 240 (190–340, 95% probability): a tentative estimate of the final deposition of Kalasasaya zonally incised vessels; (3) cal AD 420 (380–470, 95% probability): the final deposition of Kalasasaya red-rimmed vessels; and (4) cal AD 590 (500–660, 95% probability): the first deposition of Tiwanaku Redwares. These four modeled boundaries anchor an updated Late Formative chronology, which includes the Initial Late Formative phase, a newly identified decorative hiatus between the Middle and Late Formative periods. The models place Qeya and transitional vessels between inflection points 3 and 4 based on regionally consistent stratigraphic sequences. This more precise chronology will enable researchers to explore the trajectories of other contemporary shifts during this crucial period in Lake Titicaca Basin's prehistory.