Gnathodus pseudosemiglaber is an important conodont species for Lower Mississippian biostratigraphy, but differentiating it from morphologically similar species remains difficult due to uncertainties in the intraspecific, ontogenetic, and phylogenetic relationships between taxa. To clarify these uncertainties, a fauna from the Yudong Formation at the Yudong II section in Baoshan, southwestern China, that contains abundant G. pseudosemiglaber was analyzed using population thinking. Quantitative morphometric methods were employed to analyze G. pseudosemiglaber specimens. Six anatomical measurements were taken on specimens of different ontogenetic stages to conduct analyses on normal distribution, correlation, and regression. A geometric morphometric analysis based on 13 landmarks was also performed. The results demonstrated that all analyzed specimens belonged to a single population. The dorsal carina of G. pseudosemiglaber has a growth rate that far exceeds other features on the platform through ontogeny as well as exhibits a series of transverse ridges in adult individuals, which becomes the most prominent diagnostic characteristic of this species. Thus, an amended systematic description for G. pseudosemiglaber is presented. Gnathodus girtyi maxwelli, a previously named species, however, is regarded as a junior synonym of G. pseudosemiglaber. Based on the revised taxonomy of G. pseudosemiglaber, its possible phylogenetic lineages and biostratigraphic use were reviewed. The ancestor of G. pseudosemiglaber is probably G. semiglaber but its descendant is unknown. The range of G. pseudosemiglaber is from the Scaliognathus anchoralis–Doliognathus latus Zone of uppermost Tournaisian to the lower part of the G. bilineatus Zone of middle-upper Visean.

The ubiquity of social media platforms allows individuals to easily share and curate their personal lives with friends, family, and the world. The selective nature of sharing one’s personal life may reinforce the memories and details of the shared experiences while simultaneously inducing the forgetting of related, unshared memories/experiences. This is a well-established psychological phenomenon known as retrieval-induced forgetting (RIF, Anderson et al.). To examine this phenomenon in the context of social media, two experiments were conducted using an adapted version of the RIF paradigm in which participants either shared experimenter-contrived (Study 1) or personal photographs (Study 2) on social media platforms. Study 1 revealed that participants had more accurate recall of the details surrounding the shared photographs as well as enhanced recognition of the shared photographs. Study 2 revealed that participants had more consistent recall of event details captured in the shared photographs than details captured or uncaptured in the unshared photographs. These results suggest that selectively sharing photographs on social media may specifically enhance the recollection of event details associated with the shared photographs. The novel and ecologically embedded methods provide fodder for future research to better understand the important role of social media in shaping how individuals remember their personal experiences.

Manned lunar landers must ensure astronaut safety while enhancing payload capacity. Due to traditional landers being weak in high-impact energy absorb and heavy payload capacity, a Starship-type manned lunar lander is proposed in this paper. Firstly, a comprehensive analysis was conducted on the traditional cantilever beam cushioning mechanism for manned lander. Subsequently, a 26-ton manned lander and its landing mechanism were designed, and a rigid-flexible coupling dynamic analysis was performed on the compression process of the primary and auxiliary legs. Secondly, the landing performance of the proposed Starship-type manned lunar lander was compared with the traditional 14-ton manned lander in multiple landing conditions. The results indicate that under normal conditions, the largest acceleration of the proposed 26-ton Starship-type manned lander decreases more than 13.1%. It enables a significant increase in payload capacity while mitigating impact loads under various landing conditions.

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.

Rogue waves (RWs) can form on the ocean surface due to the well-known quasi-four-wave resonant interaction or superposition principle. The first is known as the nonlinear focusing mechanism and leads to an increased probability of RWs when unidirectionality and narrowband energy of the wave field are satisfied. This work delves into the dynamics of extreme wave focusing in crossing seas, revealing a distinct type of nonlinear RWs, characterised by a decisive longevity compared with those generated by the dispersive focusing (superposition) mechanism. In fact, through fully nonlinear hydrodynamic numerical simulations, we show that the interactions between two crossing unidirectional wave beams can trigger fully localised and robust development of RWs. These coherent structures, characterised by a typical spectral broadening then spreading in the form of dual bimodality and recurrent wave group focusing, not only defy the weakening expectation of quasi-four-wave resonant interaction in directionally spreading wave fields, but also differ from classical focusing mechanisms already mentioned. This has been determined following a rigorous lifespan-based statistical analysis of extreme wave events in our fully nonlinear simulations. Utilising the coupled nonlinear Schrödinger framework, we also show that such intrinsic focusing dynamics can be captured by weakly nonlinear wave evolution equations. This opens new research avenues for further explorations of these complex and intriguing wave phenomena in hydrodynamics as well as other nonlinear and dispersive multi-wave systems.

Yellow nutsedge (Cyperus esculentus L.) is one of the most problematic weeds in turfgrass due to its fast growth rate and high tuber production. Effective long-term control relies on translocation of systemic herbicides to underground tubers. Two identical trials were conducted simultaneously in separate greenhouses to evaluate the effect of several acetolactate synthase (ALS)- and protoporphyrinogen oxidase (PPO)-inhibiting postemergence herbicides on C. esculentus tuber production and viability. Seven tubers were planted into 1-L pots, and plants were allowed to mature for 6 wk before trial initiation. Treatments included pyrimisulfan at 73 g ai ha−1 once or 49 g ai ha−1 twice, imazosulfuron at 736 g ai ha−1 once or 420 g ai ha−1 twice, carfentrazone-ethyl + sulfentrazone at 22 + 198 g ai ha−1 once or 14 + 127 g ai ha−1 twice, halosulfuron at 70 g ai ha−1 once or 35 g ai ha−1 twice, and a nontreated control. Sequential applications were made 3 wk after initial treatment (WAIT) for both trials. Both single and sequential applications of carfentrazone-ethyl + sulfentrazone exhibited the quickest control (80% to 83% 4 WAIT). Two applications of imazosulfuron resulted in the greatest reduction in tuber number (81%) and tuber dry biomass (85%), while one application of carfentrazone-ethyl + sulfentrazone resulted in the greatest reduction in shoot biomass (71%). The viability of tubers that were recovered from each pot was reduced 48% to 70%, with the greatest reduction in response to carfentrazone-ethyl + sulfentrazone. Although two applications of pyrimisulfan only resulted in tuber number and shoot biomass reductions of 66% and 38%, respectively, tuber dry biomass reduction was 80%. Therefore, pyrimisulfan, imazosulfuron, halosulfuron, and carfentrazone-ethyl + sulfentrazone are all viable options for long-term C. esculentus control in turfgrass.

Liouville-type theorems for the steady incompressible Navier–Stokes system are investigated for solutions in a three-dimensional (3-D) slab with either no-slip boundary conditions or periodic boundary conditions. When the no-slip boundary conditions are prescribed, we prove that any bounded solution is trivial if it is axisymmetric or $ru^r$ is bounded, and that general 3-D solutions must be Poiseuille flows when the velocity is not big in $L^\infty$ space. When the periodic boundary conditions are imposed on the slab boundaries, we prove that the bounded solutions must be constant vectors if either the swirl or radial velocity is independent of the angular variable, or $ru^r$ decays to zero as $r$ tends to infinity. The proofs are based on the fundamental structure of the equations and energy estimates. The key technique is to establish a Saint-Venant type estimate that characterizes the growth of the Dirichlet integral of non-trivial solutions.

The recent expansion of cross-cultural research in the social sciences has led to increased discourse on methodological issues involved when studying culturally diverse populations. However, discussions have largely overlooked the challenges of construct validity- ensuring instruments are measuring what they are intended to- in diverse cultural contexts, particularly in developmental research. We contend that cross-cultural developmental research poses distinct problems for ensuring high construct validity, owing to the nuances of working with children and that the standard approach of transporting protocols designed and validated in one population to another risks low construct validity. Drawing upon our own and others’ work, we highlight several challenges to construct validity in the field of cross-cultural developmental research, including 1) lack of cultural and contextual knowledge, 2) dissociating developmental and cultural theory and methods, 3) lack of causal frameworks, 4) superficial and short- term partnerships and collaborations, and 5) culturally inappropriate tools and tests. We provide guidelines to address these challenges, including 1) using ethnographic and observational approaches, 2) developing evidence-based causal frameworks, 3) conducting community-engaged and collaborative research, and 4) culture-specific refinements and training. We discuss the need to balance methodological consistency with culture-specific refinements to improve construct validity in cross-cultural developmental research.

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.

The dynamic behaviour of helicopter during water impact, considering variations in initial downward velocity and pitching angle, have been investigated numerically and theoretically in the present study. The air-water two-phase flows are simulated by solving unsteady Reynolds-averaged Navier-Stokes equations enclosed by standard $k - \omega $ turbulence model. A treatment for computational domain in combination with a global dynamic mesh technique is applied to deal with the relative motion between the helicopter and water. Results indicate that the initial downward velocity of helicopter exhibits behaviour similar to that of a V-shaped body impacting on water, as does the initial pitching angle. To extend the theoretical approach for predicting the kinematic parameters during helicopter ditching, a shape factor capturing the combined effect of various attributes and an average deadrise angle for asymmetric wedges are also introduced.

Vaccines have revolutionised the field of medicine, eradicating and controlling many diseases. Recent pandemic vaccine successes have highlighted the accelerated pace of vaccine development and deployment. Leveraging this momentum, attention has shifted to cancer vaccines and personalised cancer vaccines, aimed at targeting individual tumour-specific abnormalities. The UK, now regarded for its vaccine capabilities, is an ideal nation for pioneering cancer vaccine trials. This article convened experts to share insights and approaches to navigate the challenges of cancer vaccine development with personalised or precision cancer vaccines, as well as fixed vaccines. Emphasising partnership and proactive strategies, this article outlines the ambition to harness national and local system capabilities in the UK; to work in collaboration with potential pharmaceutic partners; and to seize the opportunity to deliver the pace for rapid advances in cancer vaccine technology.

Aiming at the problems of poor coordination effect and low positioning accuracy of unmanned aerial vehicle (UAV) formation cooperative navigation in complex environments, an adaptive time-varying factor graph framework UAV formation cooperative navigation algorithm is proposed. The proposed algorithm uses the factor graph to describe the relationship between the navigation state of the UAV fleet and its own measurement information as well as the relative navigation information, and detects the relative navigation information at each moment by the double-threshold detection method to update the factor graph model at the current moment. And the robust estimation is combined with the factor graph, and the weight function measurements are used in the construction of the factor nodes for adaptive adjustment to make the system highly robust. The simulation results show that the proposed method realises the effective fusion of airborne multi-source sensing information and relative navigation information, which effectively improves the UAV formation cooperative navigation accuracy.

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.

The main purpose of this paper is to investigate the sensitivity analysis of structural equation model when minor perturbation is introduced. Some influence measure that based on the general case weight perturbation is derived for the generalized least squares estimation. An influence measure that related to the Cook's distance is also developed for the special case deletion perturbation scheme. Using the proposed methodology, the influential observation in a data set can be detected. Moreover, the general theory can be applied to detect the influential parameters in a model. Finally, some illustrative artificial and real examples are presented.

Several methods used to examine differential item functioning (DIF) in Patient-Reported Outcomes Measurement Information System (PROMIS®) measures are presented, including effect size estimation. A summary of factors that may affect DIF detection and challenges encountered in PROMIS DIF analyses, e.g., anchor item selection, is provided. An issue in PROMIS was the potential for inadequately modeled multidimensionality to result in false DIF detection. Section 1 is a presentation of the unidimensional models used by most PROMIS investigators for DIF detection, as well as their multidimensional expansions. Section 2 is an illustration that builds on previous unidimensional analyses of depression and anxiety short-forms to examine DIF detection using a multidimensional item response theory (MIRT) model. The Item Response Theory-Log-likelihood Ratio Test (IRT-LRT) method was used for a real data illustration with gender as the grouping variable. The IRT-LRT DIF detection method is a flexible approach to handle group differences in trait distributions, known as impact in the DIF literature, and was studied with both real data and in simulations to compare the performance of the IRT-LRT method within the unidimensional IRT (UIRT) and MIRT contexts. Additionally, different effect size measures were compared for the data presented in Section 2. A finding from the real data illustration was that using the IRT-LRT method within a MIRT context resulted in more flagged items as compared to using the IRT-LRT method within a UIRT context. The simulations provided some evidence that while unidimensional and multidimensional approaches were similar in terms of Type I error rates, power for DIF detection was greater for the multidimensional approach. Effect size measures presented in Section 1 and applied in Section 2 varied in terms of estimation methods, choice of density function, methods of equating, and anchor item selection. Despite these differences, there was considerable consistency in results, especially for the items showing the largest values. Future work is needed to examine DIF detection in the context of polytomous, multidimensional data. PROMIS standards included incorporation of effect size measures in determining salient DIF. Integrated methods for examining effect size measures in the context of IRT-based DIF detection procedures are still in early stages of development.

A 1k-dimensional multivariate normal distribution is made discrete by partitioning the k-dimensional Euclidean space with rectangular grids. The collection of probability integrals over the partitioned cubes is a k-dimensional contingency table with ordered categories. It is shown that loglinear model with main effects plus two-way interactions provides an accurate approximation for the k-dimensional table. The complete multivariate normal integral table is computed via the iterative proportional fitting algorithm from bivariate normal integral tables. This approach imposes no restriction on the correlation matrix. Comparisons with other numerical integration algorithms are reported. The approximation suggests association models for discretized multivariate normal distributions and contingency tables with ordered categories.