Objectives/Goals: Electronic health record (EHR)-based recruitment can facilitate participation in clinical trials, but is not a panacea to trial accrual challenges. We conducted a root cause analysis to identify EHR-based accrual barriers and facilitators in a pragmatic randomized trial of metformin for those with prostate cancer and glucose intolerance. Methods/Study Population: We quantitatively analyzed enrollment drop-offs among eligible patients who either did not complete a consent (with analysis of EHR-embedded consent process) or who completed a consent but were not enrolled (with analysis of EHR implementation of a Best Practice Alert). We summarized data from the EHR by eligibility, provider encounters, and alerts, and generated CONSORT diagrams and tables to trace the enrollment pathway. We supplemented quantitative findings with a thematic analysis of semi-structured individual interviews with eligible patients (n = 10) and study providers (n = 4) to identify systematic barriers to recruitment and enrollment of eligible patients. Results/Anticipated Results: CONSORT diagram analysis found that 24% of potentially eligible patients (268 of 1130) had an eligible study encounter but were not enrolled. Additionally, BPAs were not triggering for some eligible patients. Interviews revealed that study providers wanted more detailed information about which study arm their patient would be assigned to, and about next steps after enrollment, especially relating to additional lab tests and follow-up care needed. Patient interviews suggested that patients often did not remember completing the consent process and felt overwhelmed with appointments and information; patients expected providers to actively bring up research opportunities during appointments. Discussion/Significance of Impact: While pragmatic EHR-embedded trials are often characterized as lower-burden, these trials still require active engagement by providers, as well as ongoing attention from both research and informatics teams to ensure that EHR-embedded processes are functioning as designed, and that they are effective in recruiting study participants.

Objectives/Goals: This study aims to evaluate the performance of a third-party artificial intelligence (AI) product in predicting diagnosis-related groups (DRGs) in a community healthcare system. We highlight a use case illustrating how clinical practice leverages AI-predicted information in unexpected yet advantageous ways and assess the AI predictions accuracy and practical application. Methods/Study Population: DRGs are crucial for hospital reimbursement under the prospective payment model. The Mayo Clinic Health System (MCHS), a network of clinics and hospitals serving a substantial rural population in Minnesota and Wisconsin, has recently adopted an AI algorithm developed by Xsolis (an AI-focused healthcare solution provider). This algorithm, a 1D convolutional neural network, predicts DRGs based on clinical documentation. To assess the accuracy of AI-generated DRG predictions for inpatient discharges, we analyzed data from 930 patients hospitalized at MCHS Mankato between March 2 and May 13, 2024. The Xsolis platform provided the top three DRG predictions for the first 48 hours of each inpatient stay. The accuracy of these predictions was then compared against the final billed DRG codes from the hospital’s records. Results/Anticipated Results: In our validation set, Xsolis achieved a top-3 DRG prediction accuracy of 71% at 24 hours and 81% at 48 hours, which is lower than the originally reported accuracy of 81.1% and 83.3%, respectively. Interestingly, discussions with clinical practice leaders revealed that the most valuable information derived from the AI predictions was the expected geometric mean length of stay (GMLOS), which Xsolis was perceived to predict accurately. In the Medicare system, each DRG is associated with an expected GMLOS, a critical factor for efficient hospital flow planning. A subsequent analysis comparing predicted GMLOS with the actual length of stay showed variances of -0.10 days on day 1 and 0.14 days on day 2, indicating a high degree of accuracy and aligning with clinical practice perceptions. Discussion/Significance of Impact: Our research underscores that clinical practice can leverage AI predictions in unexpected yet beneficial ways. While initially focused on DRG prediction, the associated GMLOS emerged as more significant. This suggests that AI algorithm validation should be tailored to specific clinical needs rather than relying solely on generalized benchmarks.

We introduce, test, and compare two auction-based methods for eliciting discount rates. In these “patience auctions”, participants bid the smallest future sum they would prefer -or- the longest time they would wait for a reward, rather than receive a smaller, immediate payoff. The most patient bidder receives the delayed reward; all others receive the immediate payoff. These auctions allow us to compare discounting when participants’ attention is focused on the temporal versus monetary dimension of delayed rewards. We find that the estimated parameters in the three most commonly used discount functions (exponential, hyperbolic, and quasi-hyperbolic) differ across these two bidding methods (time-bids vs. money-bids). Specifically, our participants tend to show more impatience under time-bids. Furthermore, we find that people are more likely to exhibit exponential (as opposed to hyperbolic) discounting and exhibit less present bias under time-bids, compared to money-bids. To our knowledge, this paper is the first to directly compare time versus money preference elicitations, within the same subjects, using an incentive-compatible mechanism.

For almost eight decades, productivity in the United States agricultural sector has substantially increased, in large extent due to the adoption of technological innovations. Despite the increased utilization of technology, questions remain regarding which producers are more likely to adopt a greater number of technological innovations. This research seeks to understand how commodity diversification strategies, farm characteristics, producer perceptions of risk, conservation, information sources, climate adaptation, and producer demographic characteristics are associated with technology adoption among beef cattle producers in the Southeast United States. Utilizing data from an online survey and an Ordered Probit model, we show that beef cattle producers who also produce fruit have an increased probability of adopting a greater number of technologies. The opposite effect is found for other commodities such as vegetables, row crops, and other livestock. Policy recommendations are also discussed.

We present the first results from a new backend on the Australian Square Kilometre Array Pathfinder, the Commensal Realtime ASKAP Fast Transient COherent (CRACO) upgrade. CRACO records millisecond time resolution visibility data, and searches for dispersed fast transient signals including fast radio bursts (FRB), pulsars, and ultra-long period objects (ULPO). With the visibility data, CRACO can localise the transient events to arcsecond-level precision after the detection. Here, we describe the CRACO system and report the result from a sky survey carried out by CRACO at 110-ms resolution during its commissioning phase. During the survey, CRACO detected two FRBs (including one discovered solely with CRACO, FRB 20231027A), reported more precise localisations for four pulsars, discovered two new RRATs, and detected one known ULPO, GPM J1839 $-$10, through its sub-pulse structure. We present a sensitivity calibration of CRACO, finding that it achieves the expected sensitivity of 11.6 Jy ms to bursts of 110 ms duration or less. CRACO is currently running at a 13.8 ms time resolution and aims at a 1.7 ms time resolution before the end of 2024. The planned CRACO has an expected sensitivity of 1.5 Jy ms to bursts of 1.7 ms duration or less and can detect $10\times$ more FRBs than the current CRAFT incoherent sum system (i.e. 0.5 $-$2 localised FRBs per day), enabling us to better constrain the models for FRBs and use them as cosmological probes.

With wide-field phased array feed technology, the Australian Square Kilometre Array Pathfinder (ASKAP) is ideally suited to search for seemingly rare radio transient sources that are difficult to discover previous-generation narrow-field telescopes. The Commensal Real-time ASKAP Fast Transient (CRAFT) Survey Science Project has developed instrumentation to continuously search for fast radio transients (duration $\lesssim$ 1 s) with ASKAP, with a particular focus on finding and localising fast radio bursts (FRBs). Since 2018, the CRAFT survey has been searching for FRBs and other fast transients by incoherently adding the intensities received by individual ASKAP antennas, and then correcting for the impact of frequency dispersion on these short-duration signals in the resultant incoherent sum (ICS) in real time. This low-latency detection enables the triggering of voltage buffers, which facilitates the localisation of the transient source and the study of spectro-polarimetric properties at high time resolution. Here we report the sample of 43 FRBs discovered in this CRAFT/ICS survey to date. This includes 22 FRBs that had not previously been reported: 16 FRBs localised by ASKAP to $\lesssim 1$ arcsec and 6 FRBs localised to $\sim 10$ arcmin. Of the new arcsecond-localised FRBs, we have identified and characterised host galaxies (and measured redshifts) for 11. The median of all 30 measured host redshifts from the survey to date is $z=0.23$. We summarise results from the searches, in particular those contributing to our understanding of the burst progenitors and emission mechanisms, and on the use of bursts as probes of intervening media. We conclude by foreshadowing future FRB surveys with ASKAP using a coherent detection system that is currently being commissioned. This will increase the burst detection rate by a factor of approximately ten and also the distance to which ASKAP can localise FRBs.

Real-effort experiments are frequently used when examining a response to incentives. For a real-effort task to be well suited for such an exercise its measurable output must be sufficiently elastic over the incentives considered. The popular slider task in Gill and Prowse (Am Econ Rev 102(1):469–503, 2012) has been characterized as satisfying this requirement, and the task is increasingly used to investigate the response to incentives. However, a between-subject examination of the slider task’s response to incentives has not been conducted. We provide such an examination with three different piece-rate incentives: half a cent, two cents, and eight cents per slider completed. We find only a small increase in performance: despite a 1500 % increase in the incentives, output only increases by 5 %. With such an inelastic response we caution that for typical experimental sample sizes and incentives the slider task is unlikely to demonstrate a meaningful and statistically significant performance response.

When one fluid is injected into a confined geometry such as a porous medium filled with another immiscible fluid, even at an extremely low injection speed, rapid filling of several pore spaces accompanied by retraction of multiple fluid–fluid interfaces can be observed. Such processes with fast liquid redistribution within the solid structure, called Haines jumps, are ubiquitous in many multiphase flow systems, which can impact fluid trapping, energy dissipation and hysteretic saturation in various engineering applications. Inspired by this mechanism, here, we propose a dual-channel structure to realise controlled Haines jumps during fluid displacement processes. Via theoretical analysis and numerical simulations, we show that the dynamics of fluid interfaces during Haines jumps can be quantitatively correlated with the driving capillary pressure and dissipating viscous stress, which enables simultaneous determination of the fluid viscosity and interfacial tension in the dual-channel multiphase system.

During the automatic docking assembly of aircraft wing-fuselage, using monocular camera or dual-camera to monitor the docking stage of the fork-ear will result in an incomplete identification of the fork-ear pose-position and an inaccurate description of the deviation in the intersection holes’ position coordinates. To address this, a quality inspection and error correction method is proposed for the fork-ear docking assembly based on multi-camera stereo vision. Initially, a multi-camera stereo vision detection system is established to inspect the quality of fork-ear docking assembly. Subsequently, a spatial position solution mathematical model of the fork-ear feature points is developed, and a spatial pose determination mathematical model of fork-ear is established by utilised the elliptical cone. Finally, an enhanced artificial fish swarm particle filter algorithm is proposed to track and estimate the coordinate of the fork-ear feature points. An adaptive weighted fusion algorithm is employed to fuse the detection data from the multi-camera and the laser tracker, and a wing pose-position fine-tuning error correction model is constructed. Experimental results demonstrate that the method enhances the effect of the assembly quality inspection and effectively improves the wing-fuselage docking assembly accuracy of the fork-ear type aircraft.

This study aimed to estimate the nationwide prevalence of cardiometabolic diseases (CMD) among adults with underweight in the US general population. Using data from the National Health and Nutrition Examination Survey (1999–2020), we estimated the age-standardised prevalence of dyslipidemia, hypertension, diabetes, chronic kidney disease, CVD and the presence of zero or at least two CMD. Multivariable Poisson regressions were used to compare CMD prevalence between subgroups, adjusting for age, sex and race/ethnicity. Among the 855 adults with underweight included, the weighted mean age was 40·8 years, with 68·1 % being women and 70·4 % non-Hispanic White. The estimated prevalence rates were 23·4 % for dyslipidemia (95 % CI 19·4 %, 27·5 %), 15·6 % for hypertension (95 % CI 13·3 %, 17·8 %), 2·5 % for diabetes (95 % CI 1·5 %, 3·5 %), 7·9 % for chronic kidney disease (95 % CI 6·9 %, 8·8 %) and 6·1 % for CVD (95 % CI 4·3 %, 7·9 %). The prevalence of having zero and at least two CMD was 50·6 % (95 % CI 44·1 %, 57·0 %) and 12·3 % (95 % CI 8·1 %, 16·4 %), respectively. Non-Hispanic Black adults had significantly higher prevalence of diabetes (adjusted prevalence ratio, 3·35; 95 % CI 1·35, 8·30) compared with non-Hispanic White adults. In conclusion, approximately half of the underweight adults had at least one CMD, and 12·3 % had at least two CMD. Prevention and management of CMD in underweight adults are critical yet neglected public health challenges.

The pth ($p\geq 1$) moment exponential stability, almost surely exponential stability and stability in distribution for stochastic McKean–Vlasov equation are derived based on some distribution-dependent Lyapunov function techniques.

Consider the flow through a channel with grooved edges on one (or both) side(s). If heating is applied to the boundaries, thermal drift is the flow generated by the interaction of the groove and heating patterns. It is known that, if one side of a channel is smooth while the other is grooved, the application of heating forms a so-called ‘thermal drift engine’. Two thermal drift engines are activated if both surfaces are grooved, and these may reinforce or oppose each other. Carefully choosing these engines can lead to an intensification of the thermal drift. The interplay of two drift engines is explored using a horizontal slot with grooves that have a sinusoidal profile with a prescribed wavenumber $\alpha $. It is shown that the strength of the flow decreases proportional to $\alpha $ as $\alpha \to 0$ and proportional to ${\alpha ^{ - 1}}$ as $\alpha \to \infty $. We determine the value of $\alpha $ corresponding to the strongest flow and characterize how the conclusions should be modified if a uniform heating component is added to the heating pattern.

This case study presents an analysis of community-driven partnerships, focusing on the nonprofit Baltimore CONNECT (BC) network and its collaborative efforts with a Community-Engaged Research (CEnR) team of the Johns Hopkins Institute for Clinical and Translational Research (ICTR). BC has built a network of over 30 community-based organizations to provide health and social services in Baltimore City. The study emphasizes the role of CEnR in supporting community-led decision-making, specifically in the planning and implementation of community health resource fairs. These fairs address social determinants of health by offering a variety of services, including health education, screenings, vaccinations, and resource distribution. The paper details the methods, resource mobilization, and collaborative framing processes in the execution of these fairs in a community-academic collaboration with the ICTR. Results from a 2.5-year period show the positive impact of the fairs on individuals, families, and the community at large in East Baltimore. The findings underscore the importance of community-led collaborations in addressing health disparities and improving overall community well-being. It concludes by reflecting on the sustained engagement, trust-building, and shared learning that emerges from such partnerships, suggesting a model for future community-academic health initiatives.

Basal crevasses threaten the stability of ice shelves through the potential to form rifts and calve icebergs. Furthermore, it is important to determine the dependence of crevasse stability on temperature due to large vertical temperature variations on ice shelves. In this work, considering the vertical temperature profile through ice viscosity, we compare (1) the theoretical crack depths and (2) the threshold stress causing the transition from basal crevasses to full thickness fractures in several fracture theories. In the Zero Stress approximation, the depth-integrated force at the crevassed and non-crevassed location are unbalanced, violating the volume-integrated Stokes equation. By incorporating a Horizontal Force Balance (HFB) argument, recent work showed analytically that the threshold stress for rift initiation is only half of that predicted by the Zero Stress approximation. We generalize the HFB theory to show that while the temperature profile influences crack depths, the threshold rifting stress is insensitive to temperature. We compare with observations and find that HFB best matches observed rifts. Using HFB instead of Zero Stress for cracks in an ice-sheet model would substantially enlarge the predicted fracture depth, reduce the threshold rifting stress and potentially increase the projected rate of ice shelf mass loss.

Hunting, habitat loss and fragmentation have caused a rapid decline in the distribution and abundance of the clouded leopard Neofelis nebulosa across its range, and in several areas, including Taiwan, the species is now extirpated. Taiwan, a former stronghold for the species, is a candidate for its reintroduction, based on increasing prey abundance and high forest coverage. Such future reintroduction efforts, however, are hampered by a lack of analysis of potential clouded leopard habitat on the island. To address this, we explore habitat suitability for the species in Taiwan. We used a multi-scale, multivariate habitat selection model based on clouded leopard presence–absence data from extensive camera-trap surveys across its current range to predict suitable habitat in Taiwan. Our findings indicate that 38% of Taiwanese territory is potentially suitable habitat for the clouded leopard, of which 46% is under protection. This demonstrates the high potential of Taiwan's habitat for clouded leopard reintroduction.

The effectiveness of utilizing heating patterns as a drag-reduction tool in sloping channels is analysed. The usefulness of heating is judged by determining the pressure gradient required to maintain the same flow rate as in the isothermal case. The key to reducing pressure loss is the formation of separation bubbles, although these bubbles are washed away at relatively large Reynolds numbers. The bubbles reduce the direct contact between the stream and the side walls, thereby reducing the friction experienced by the flow. Moreover, the fluid inside the bubbles tends to rotate, a motion provoked by longitudinal temperature gradients. This rotation also seems to reduce the resistance. On the other hand, the existence of the bubbles tends to obstruct the stream, increasing the flow resistance. In general, channels oriented close to horizontal experience a relatively small pressure loss, but this loss grows markedly as the channel inclines towards the vertical. When modest heating is applied, the pressure loss is approximately proportional to the square of the associated Rayleigh number. It is also shown that if the heating wavelength is too short or too long, the heating loses its effectiveness. In certain circumstances, it turns out that the theoretical pressure-gradient reduction achieved by judicious heating is so large that it exceeds the pressure gradient required to drive the flow in the isothermal problem. The conclusion is that in these instances, a pressure gradient of the opposite sign must be applied to prevent flow acceleration.