Background: Interventions targeting urine culture stewardship can improve diagnostic accuracy for urinary tract infections (UTI) and decrease inappropriate antibiotic treatment of asymptomatic bacteriuria. We aimed to determine if a clinical decision support (CDS) tool which provided guidance on and required documentation of the indications would decrease inappropriately ordered urine cultures in an academic healthcare network that already uses conditional (e.g. reflex) urine testing. Methods: In October 2022, four hospitals within one academic healthcare network transitioned to a new electronic health record (EHR). We developed an embedded CDS tool that provided guidance on ordering either a urinalysis (UA) with reflex to urine culture or a non-reflex urine culture (e.g. for pregnant patients) based on the indication for testing (Figure 1). We compared median monthly UA with reflex culture and non-reflex urine culture order rates pre- (8/2017–9/2022) and post- (10/2022–9/2023) intervention using the Wilcoxon rank-sum test. We used interrupted time-series analyses allowing a one-month time window for the intervention effect to assess changes in monthly UA with reflex culture, non-reflex urine culture, and total urine culture order rates associated with the intervention. Using SAS 9.4, we generated Durbin-Watson statistics to assess for autocorrelation and adjusted for this using a stepwise autoregressive model. Result: The median monthly UA with reflex culture order rates per 1000 patient-days were similar pre- and post- intervention at 36.7 (interquartile range [IQR]: 31.0–39.7) and 35.4 (IQR: 32.8–37.0), respectively (Figure 2). Non-reflex and total urine culture rates per 1000 patient-days decreased from 8.5 (IQR: 8.1–9.1) to 4.9 (IQR: 4.7–5.1) and from 20.0 (IQR: 18.9–20.7) to 14.4 (IQR: 14.0–14.6) post-intervention, respectively. Interrupted time-series analyses revealed that the intervention was associated with a decrease in the monthly non-reflex urine culture by 4.8 cultures/1000 patient-days (p< 0.001) and in the total urine culture monthly order rates by 5.0 cultures/ 1000 patient-days (p < 0 .001) [Figures 3a and b]. The UA with reflex order rate did not significantly change with the intervention (not pictured). Conclusion: In an academic healthcare network that already employed conditional urine testing, the implementation of an EHR-based diagnostic stewardship tool led to additional decreases in both non-reflex and total urine cultures ordered.

Background: Central line-associated bloodstream infections (CLABSI) and catheter-associated urinary tract infections (CAUTI) are key healthcare-associated infection (HAI) quality metrics. In this qualitative analysis, we aimed to identify common issues contributing to CLABSIs and CAUTIs occurring during the COVID-19 pandemic. Methods: In an academic healthcare network in Atlanta, GA, four hospitals perform real-time, apparent cause analyses (ACAs) for all CLABSIs and CAUTIs. Contributing factors are entered as free text into an electronic database. We analyzed data from 8/2020–8/2022. We first performed a qualitative open card sort of all reported contributing factors to CLABSI and created a novel framework based on mutually defined critical tasks (e.g., line insertion) and cross-cutting issues (e.g., communication breakdown). Contributing factors could describe ≥1 critical task and/or ≥1 cross-cutting issue. After establishing interrater reliability, a multidisciplinary group applied this framework to classify each contributing factor. For CAUTI, we used the same set of cross-cutting issues but identified new critical tasks via open card sorting. We then used the framework to classify each CAUTI contributing factor. We used descriptive statistics to identify frequent critical tasks and cross-cutting issues. Results: We reviewed 350 CLABSI ACAs with 602 contributing factors and 240 CAUTI ACAs with 405 contributing factors (Figure 1). Our classification framework comprised 11 cross-cutting issues and 9 critical tasks for CLABSI and 7 critical tasks for CAUTI (Figure 2). CLABSI: The critical tasks most often reported were bathing (19%), central line dressing maintenance (15%), and assessing central line indication (8%; Figure 3). Within these tasks, the most frequent issues described for bathing were the task not being performed (20%) and unclear documentation (18%); for dressing maintenance, the task was not performed (15%), not documented (15%), or poorly performed due to lack of competency (15%); and for assessing line indication, there was frequent communication breakdown (33%). CAUTI: The critical tasks most often reported were urinary catheter care (26%) and assessing the indication for urinary catheter (22%; Figure 4). Within these tasks, urinary catheter care was frequently not documented (38%) or not performed (16%); assessing urinary catheter necessity was often not documented (29%) or involved breakdown of communication (19%). Conclusion: We created a novel framework to evaluate common causes of HAIs in an academic healthcare network. This framework can be used to identify and track gaps over time and to develop quality improvement initiatives targeting key tasks and associated factors, such as communication difficulties when assessing device indications.

Disclosure: Colleen Kraft: Consultant - REbiotix/Ferring; Scientific Advisory Board - Seres, LLC

Archaeologists tend to produce slow data that is contextually rich but often difficult to generalize. An example is the analysis of lithic microdebitage, or knapping debris, that is smaller than 6.3 mm (0.25 in.). So far, scholars have relied on manual approaches that are prone to intra- and interobserver errors. In the following, we present a machine learning–based alternative together with experimental archaeology and dynamic image analysis. We use a dynamic image particle analyzer to measure each particle in experimentally produced lithic microdebitage (N = 5,299) as well as an archaeological soil sample (N = 73,313). We have developed four machine learning models based on Naïve Bayes, glmnet (generalized linear regression), random forest, and XGBoost (“Extreme Gradient Boost[ing]”) algorithms. Hyperparameter tuning optimized each model. A random forest model performed best with a sensitivity of 83.5%. It misclassified only 28 or 0.9% of lithic microdebitage. XGBoost models reached a sensitivity of 67.3%, whereas Naïve Bayes and glmnet models stayed below 50%. Except for glmnet models, transparency proved to be the most critical variable to distinguish microdebitage. Our approach objectifies and standardizes microdebitage analysis. Machine learning allows studying much larger sample sizes. Algorithms differ, though, and a random forest model offers the best performance so far.

Upernavik Isstrøm, a marine glacier undergoing rapid retreat, is simulated by forcing a numerical model with ocean-driven melt. A review of processes driving retreat led us to hypothesize that a glacier undergoing rapid retreat may be less sensitive to perturbations in the balance of forces than a glacier that is undergoing moderate changes or a glacier in steady state. Numerical experiments suggest this is not the case, and that a system in rapid retreat is as sensitive to basal traction perturbations as a system that is near to steady state. This result is important when considering other glacier systems experiencing marine-forced retreat. While the ice–ocean interface is of primary importance, additional perturbations from meltwater-forced decoupling of the glacier from its bed continue to feature in glacier dynamics.

The geometry and thermal structure of western Greenland ice sheet are known to have undergone relatively substantial change over the Holocene. Evolution of the frozen and melted fractions of the bed associated with the ice-sheet retreat over this time frame remains unclear. We address this question using a thermo-mechanically coupled flowline model to simulate a 11 ka period of ice-sheet retreat in west central Greenland. Results indicate an episode of ~100 km of terminus retreat corresponded to ~16 km of upstream frozen/melted basal boundary migration. The majority of migration of the frozen area is associated with the enhancement of the frictional and strain heating fields, which are accentuated toward the retreating ice margin. The thermally active bedrock layer acts as a heat sink, tending to slow contraction of frozen-bed conditions. Since the bedrock heat flux in our region is relatively low compared to other regions of the ice sheet, the frozen region is relatively greater and therefore more susceptible to marginward changes in the frictional and strain heating fields. Migration of melted regions thus depends on both geometric changes and the antecedent thermal state of the bedrock and ice, both of which vary considerably around the ice sheet.

Rapid vegetative growth and adverse application conditions are common factors leading to the failure of postemergence herbicides on Palmer amaranth. A sequential herbicide application, or respray, is often necessary to control weeds that have survived the initial herbicide application to protect crop yield and minimize weed seed production. The optimum timing after the initial application and the most effective herbicide for control of Palmer amaranth has not been characterized. The objectives of these experiments were to determine the optimum herbicide for treating Palmer amaranth regrowth, the optimum timing for each of those herbicides, and how the initial failed herbicide might affect efficacy of a second herbicide application. Bare ground field experiments were performed in 2017 and 2018 in which glufosinate or fomesafen herbicide failure was induced on Palmer amaranth plants that were 30 cm in height. Respray treatments of glufosinate, fomesafen, lactofen, 2,4-D, and dicamba were applied once at timings of 4 to 5 d, 7 d, or 11 d after the initial spray application. Nearly all herbicide treatment and timing combinations increased control by at least 13 percentage points compared to no respray herbicide treatment. Regardless of initial herbicide, glufosinate applied as a respray treatment was the most consistent and efficacious with up to 97% control. The specific herbicide used in the second application impacted final weed control more so than timing of the respray application. For instance, control by glufosinate respray treatments was 10 to 18 percentage points greater than control from lactofen respray treatments, whereas control decreased by 3 percentage points when respray applications of any herbicide were made 11 d after initial application of glufosinate compared to 4 to 5 and 7 d after initial application of glufosinate. In the event of failure to control Palmer amaranth with glufosinate or fomesafen, glufosinate should be applied in order to maximize control.

In the current era, many of the military threats that state leaders face come from domestic and transnational nonstate actors. Military alliances are recognized as an important policy strategy to counter military threats, but existing research has primarily been focused on threats from other states and has difficulty uncovering a consistent relationship between external threat and alliance formation. We argue that this discrepancy arises from the failure to recognize that many threats are not external to the state. We contend that alliance formation is motivated both by external threats from other states and by internal threats that make civil conflict more likely. Moreover, we argue that leaders design alliance obligations differently when faced with internal threats. An empirical analysis of alliance formation from 1946 to 2009 shows that while external threats motivate the formation of defense pacts, internal threats encourage the formation of consultation pacts. Internal threats with the greatest potential for internationalization also encourage the formation of neutrality/nonaggression pacts. This research deepens our understanding of how states design security policies to deal with the threats posed by nonstate actors, a salient concern of leaders in the twenty-first century, and helps us to understand the variety of alliance obligations that we observe.

Foliar herbicide applications to waterhemp can result in inadequate control, leading to subsequent regrowth that often necessitates a second herbicide application to prevent crop interference and seed production. The most effective herbicides and application timings are unknown in situations where waterhemp has regrown from previous injury, such as failed applications of glufosinate or fomesafen. The objective of this research was to determine the optimum combination of herbicide and time from the first failed herbicide application to a sequential herbicide application for control of waterhemp regrowth. Reduced rates of either glufosinate or fomesafen were applied to 30-cm waterhemp plants to mimic failure of the initial herbicide application in separate bare-ground experiments. Respray treatments of glufosinate, fomesafen, lactofen, 2,4-D, or dicamba were applied 3, 7, or 11 d after the initial application. Glufosinate and fomesafen as respray treatments resulted in 90% to 100% control of waterhemp regardless of application timing following a failed glufosinate application. After a failed application of fomesafen, applying glufosinate or 2,4-D resulted in 87% to 99% control of waterhemp. Waterhemp control with fomesafen and lactofen was 13% to 21% greater, respectively, when those treatments followed glufosinate compared with fomesafen as the initial herbicides. On the basis of these results, glufosinate and fomesafen should be used for respray situations after inadequate control from glufosinate; and 2,4-D or glufosinate should be used for respray situations following inadequate control from fomesafen where crop tolerance and herbicide product labels allow. Although glufosinate followed by glufosinate was very effective for controlling waterhemp regrowth, caution should be exercised to avoid sequential application of herbicide with the same site of action.

A full-stress, thermomechanically coupled, numerical model is used to explore the interaction between basal thermal conditions and motion of a terrestrially terminating section of the west Greenland ice sheet. The model domain is a two-dimensional flowline profile extending from the ice divide to the margin. We use data-assimilation techniques based on the adjoint model in order to optimize the basal traction field, minimizing the difference between modeled and observed surface velocities. We monitor the sensitivity of the frozen/melted boundary (FMB) to changes in prescribed geothermal heat flux and sliding speed by applying perturbations to each of these parameters. The FMB shows sensitivity to the prescribed geothermal heat flux below an upper threshold where a maximum portion of the bed is already melted. The position of the FMB is insensitive to perturbations applied to the basal traction field. This insensitivity is due to the short distances over which longitudinal stresses act in an ice sheet.

Accurate modeling of ice sheets requires proper information on boundary conditions, including the geothermal heat flow (or heat-flow density (HFD)). Traditionally, one uniform HFD value is adopted for the entire modeled domain. We have calculated a distributed, high-resolution HFD dataset for an approximate core area (Sweden and Finland) of the Scandinavian ice sheet, and imbedded this within lower-resolution data published for surrounding regions. Within the Last Glacial Maximum ice margin, HFD varies with a factor of as much as 2.8 (HFD values ranging between 30 and 83 mWm–2), with an average of 49 mWm–2. This average value is 17% higher than 42 mWm–2, a common uniform value used in ice-sheet modeling studies of Fennoscandia. Using this new distributed dataset on HFD, instead of a traditional uniform value of 42 mWm–2, yields a 1.4 times larger total basal meltwater production for the last glacial cycle. Furthermore, using the new dataset in high-resolution modeling results in increased spatial thermal gradients at the bed. This enhances and introduces new local and regional effects on basal ice temperatures and melt rates. We observed significant strengthening of local ‘ice streaming’, which in one case correlates to an ice-flow event previously interpreted from geomorphology. Regional to local variations in geothermal heat flow need to be considered for proper identification and treatment of thermal and hydraulic bed conditions, most likely also when studying Laurentide, Greenland and Antarctic ice sheets.

Results from the Heinrich Event Intercomparison (HEINO) topic of the Ice-Sheet Model Intercomparison Project (ISMIP) are presented. ISMIP HEINO was designed to explore internal large-scale ice-sheet instabilities in different contemporary ice-sheet models. These instabilities are of interest because they are a possible cause of Heinrich events. A simplified geometry experiment reproduces the main characteristics of the Laurentide ice sheet, including the sedimented region over Hudson Bay and Hudson Strait. The model experiments include a standard run plus seven variations. Nine dynamic/thermodynamic ice-sheet models were investigated; one of these models contains a combination of the shallow-shelf (SSA) and shallow-ice approximation (SIA), while the remaining eight models are of SIA type only. Seven models, including the SIA–SSA model, exhibit oscillatory surges with a period of ∼1000 years for a broad range of parameters, while two models remain in a permanent state of streaming for most parameter settings. In a number of models, the oscillations disappear for high surface temperatures, strong snowfall and small sediment sliding parameters. In turn, low surface temperatures and low snowfall are favourable for the ice-surge cycles. We conclude that further improvement of ice-sheet models is crucial for adequate, robust simulations of cyclic large-scale instabilities.

The floating terminal of Jakobshavn Isbræ, the fastest Greenland ice stream, has disintegrated since 2002, resulting in a doubling of ice velocity and rapidly lowering inland ice elevations. Conditions prior to disintegration were modeled using control theory in a plane-stress solution, and the Missoula model of ice-shelf flow. Both approaches pointed to a mechanism that inhibits ice flow and that is not captured by either approach. Jamming of flow, an inherent property of granular materials passing through a constriction (Jakobshavn Isfjord), is postulated as the mechanism. Rapid disintegration of heavily crevassed floating ice accompanies break-up of the ice jam.

Subglacial lakes beneath Antarctica’s fast-moving ice streams are known to undergo ∼1 km3 volume changes on annual timescales. Focusing on the MacAyeal Ice Stream (MacIS) lake system, we create a simple model for the response of subglacial water distribution to lake discharge events through assimilation of lake volume changes estimated from Ice, Cloud and land Elevation Satellite (ICESat) laser altimetry. We construct a steady-state water transport model in which known subglacial lakes are treated as either sinks or sources depending on the ICESat-derived filling or draining rates. The modeled volume change rates of five large subglacial lakes in the downstream portion of MacIS are shown to be consistent with observed filling rates if the dynamics of all upstream lakes are considered. However, the variable filling rate of the northernmost lake suggests the presence of an undetected lake of similar size upstream. Overall, we show that, for this fast-flowing ice stream, most subglacial lakes receive >90% of their water from distant distributed sources throughout the catchment, and we confirm that water is transported from regions of net basal melt to regions of net basal freezing. Our study provides a geophysically based means of validating subglacial water models in Antarctica and is a potential way to parameterize subglacial lake discharge events in large-scale ice-sheet models where adequate data are available.

Ten ice-sheet models are used to study sensitivity of the Greenland and Antarctic ice sheets to prescribed changes of surface mass balance, sub-ice-shelf melting and basal sliding. Results exhibit a large range in projected contributions to sea-level change. In most cases, the ice volume above flotation lost is linearly dependent on the strength of the forcing. Combinations of forcings can be closely approximated by linearly summing the contributions from single forcing experiments, suggesting that nonlinear feedbacks are modest. Our models indicate that Greenland is more sensitive than Antarctica to likely atmospheric changes in temperature and precipitation, while Antarctica is more sensitive to increased ice-shelf basal melting. An experiment approximating the Intergovernmental Panel on Climate Change’s RCP8.5 scenario produces additional first-century contributions to sea level of 22.3 and 8.1 cm from Greenland and Antarctica, respectively, with a range among models of 62 and 14 cm, respectively. By 200 years, projections increase to 53.2 and 26.7 cm, respectively, with ranges of 79 and 43 cm. Linear interpolation of the sensitivity results closely approximates these projections, revealing the relative contributions of the individual forcings on the combined volume change and suggesting that total ice-sheet response to complicated forcings over 200 years can be linearized.

The Numeniini is a tribe of 13 wader species (Scolopacidae, Charadriiformes) of which seven are Near Threatened or globally threatened, including two Critically Endangered. To help inform conservation management and policy responses, we present the results of an expert assessment of the threats that members of this taxonomic group face across migratory flyways. Most threats are increasing in intensity, particularly in non-breeding areas, where habitat loss resulting from residential and commercial development, aquaculture, mining, transport, disturbance, problematic invasive species, pollution and climate change were regarded as having the greatest detrimental impact. Fewer threats (mining, disturbance, problematic native species and climate change) were identified as widely affecting breeding areas. Numeniini populations face the greatest number of non-breeding threats in the East Asian-Australasian Flyway, especially those associated with coastal reclamation; related threats were also identified across the Central and Atlantic Americas, and East Atlantic flyways. Threats on the breeding grounds were greatest in Central and Atlantic Americas, East Atlantic and West Asian flyways. Three priority actions were associated with monitoring and research: to monitor breeding population trends (which for species breeding in remote areas may best be achieved through surveys at key non-breeding sites), to deploy tracking technologies to identify migratory connectivity, and to monitor land-cover change across breeding and non-breeding areas. Two priority actions were focused on conservation and policy responses: to identify and effectively protect key non-breeding sites across all flyways (particularly in the East Asian- Australasian Flyway), and to implement successful conservation interventions at a sufficient scale across human-dominated landscapes for species’ recovery to be achieved. If implemented urgently, these measures in combination have the potential to alter the current population declines of many Numeniini species and provide a template for the conservation of other groups of threatened species.

Creating institutions that effectively manage interstate conflict is a priority for policy-makers. In this article we demonstrate that military allies are well positioned to influence the crisis-bargaining behavior of both challengers and targets in ways that often lead to peace. Through a three-player game-theoretic model, we demonstrate that a target's alliances not only have an effect on the demand that the challenger makes, but also on the behavior of the target. When a target values an alliance highly, an ally's recommendation for settlement can encourage the target to concede to demands without further escalation. Our statistical analysis provides evidence in support of the theoretical finding. Allies can both deter challengers and restrain partners, and as a result, can encourage peaceful behavior not only from adversaries, but from member states as well. Our study thus sheds new light on the role of military alliances as potential conflict management devices.