bluuebunny/crossref_metadata_2025_split huggingface dataset:
Persistent fever after coronavirus disease 2019 in liver/kidney transplant recipient
Authors: Mullis Caroline E. , Heldman Madeleine , Bahr Nathan C. , Minamoto Grace Y. , Puius Yoram A. , Malinis Maricar 
Published: April 2024

AbstractIn this case, a 64‐year‐old male with a history of simultaneous orthotopic liver transplant and cadaveric renal transplant presented five years prior presented with persistent fevers two days after a positive SARS‐CoV‐2 nasal PCR. A CT scan of the chest on hospital day nine revealed innumerable 1–2 mm nodules in a miliary pattern throughout the lung. (1,3)‐β‐D‐glucan on hospital day 11 was 133 pg/mL. In this article, the approach, diagnostic and management strategies for patients with persistent fevers after diagnosis of COVID‐19 in a transplant recipient are discussed.
A complex receptor locus confers responsiveness to necrosis and ethylene‐inducing like peptides in Brassica napus
Authors: Yalcin Hicret Asli , Jacott Catherine N. , Ramirez‐Gonzalez Ricardo Humberto , Steuernagel Burkhard , Sidhu Gurpinder Singh , Kirby Rachel , Verbeek Emma , Schoonbeek Henk‐jan , Ridout Christopher J. , Wells Rachel 
Published: April 2024

SUMMARYBrassica crops are susceptible to diseases which can be mitigated by breeding for resistance. MAMPs (microbe‐associated molecular patterns) are conserved molecules of pathogens that elicit host defences known as pattern‐triggered immunity (PTI). Necrosis and Ethylene‐inducing peptide 1‐like proteins (NLPs) are MAMPs found in a wide range of phytopathogens. We studied the response to BcNEP2, a representative NLP from Botrytis cinerea, and showed that it contributes to disease resistance in Brassica napus. To map regions conferring NLP response, we used the production of reactive oxygen species (ROS) induced during PTI across a population of diverse B. napus accessions for associative transcriptomics (AT), and bulk segregant analysis (BSA) on DNA pools created from a cross of NLP‐responsive and non‐responsive lines. In silico mapping with AT identified two peaks for NLP responsiveness on chromosomes A04 and C05 whereas the BSA identified one peak on A04. BSA delimited the region for NLP‐responsiveness to 3 Mbp, containing ~245 genes on the Darmor‐bzh reference genome and four co‐segregating KASP markers were identified. The same pipeline with the ZS11 genome confirmed the highest‐associated region on chromosome A04. Comparative BLAST analysis revealed unannotated clusters of receptor‐like protein (RLP) homologues on ZS11 chromosome A04. However, no specific RLP homologue conferring NLP response could be identified. Our results also suggest that BR‐SIGNALLING KINASE1 may be involved with modulating the NLP response. Overall, we demonstrate that responsiveness to NLP contributes to disease resistance in B. napus and define the associated genomic location. These results can have practical application in crop improvement.
Commonality and heterogeneity of pacemaker mechanisms in the male reproductive organs
Authors: Hashitani Hikaru , Takeya Mitsue , van Helden Dirk F. 
Published: April 2024

AbstractDuring emission, the first phase of ejaculation, smooth muscle in organs of the male reproductive tract (MRT) vigorously contract upon sympathetic nerve excitation to expel semen consisting of sperm and seminal plasma. During inter‐ejaculation phases, the epididymis, seminal vesicles and prostate undergo spontaneous phasic contractions (SPCs), this transporting and maintaining the quality of sperm and seminal plasma. Recent studies have revealed platelet‐derived growth factor receptor α‐expressing (PDGFRα+) subepithelial interstitial cells in seminal vesicles subserve the role of pacemaker cells that electrically drive SPCs in this organ. PDGFRα+ smooth muscle cells in the epididymis also appear to function as pacemaker cells implicating PDGFRα as a potential signature molecule in MRT pacemaking. The dominant mechanism driving pacemaking in these organs is the cytosolic Ca2+ oscillator. This operates through entrainment of the release‐refill cycle of Ca2+ stores, the released Ca2+ ions opening Ca2+‐activated chloride channels, including in some cases ANO1 (TMEM16A), with the resultant pacemaker potential activating L‐type voltage‐dependent Ca2+ channels in the smooth muscle causing contraction (viz. SPCs). A second pacemaker mechanism, namely the membrane oscillator also has a role in specific cases. Further investigations into the commonality and heterogeneity of MRT pacemakers will open an avenue for understanding the pathogenesis of male infertility associated with deterioration of seminal plasma.
image
Design and Application of Deep Learning-Based Crash Damage Prediction Model for Self-Driving Cars
Authors: Zhang Wenxia , Wang Zhixue 
Published: April 2024

Abstract
The collision damage of automated cars has grown in importance as self-driving car technology has advanced to the pilot operation stage. To enhance the safety of autonomous vehicles by predicting and preventing potential hazards during autonomous driving, this study presents a model for collision damage prediction in automated driving cars. The model optimizes deep convolutional neural networks using the self-attention mechanism and incorporates a degree convolutional neural network algorithm with the attention mechanism. Its application is key to reduce risks in autonomous driving. The results demonstrated that the accuracy, reliability, specificity, and Mathews correlation coefficient of the improved algorithm were 94.0%, 94.8%, 93.6%, and 0.88, respectively, resulting in a high overall performance. The prediction model's accuracy during training on the training data set and validation data set was 100% and 98%, respectively, demonstrating its efficacy. The prediction model's prediction accuracy in calculating the degree of auto collision damage for 10 working conditions in the validation data set was 83.3%. The prediction results were essentially consistent with the trend of the actual collision damage degree curve, demonstrating both the viability and high prediction accuracy of the prediction model. The aforementioned findings demonstrated the model's strong performance and great application value in the field of self-driving car collision avoidance and warning.
Analysis of Unburned Methane Emission Mechanisms in Large-Bore Natural Gas Engines With Prechamber Ignition
Authors: Patterson Mark. A. , Xie Nelson , Beurlot Kyle , Jacobs Timothy , Olsen Daniel 
Published: April 2024

Abstract
Although precombustion chambers, or prechambers, have long been employed for improving large-bore two-stroke natural gas engine ignition and combustion stability, their design predates modern analysis techniques. Employing the latest computational fluid dynamics (CFD) modeling techniques, this study investigates the importance of temperature and chemistry for ignition of the main chamber, with an emphasis on eliminating unburned methane. The sensitivity of the ignition and complete combustion to main chamber air/fuel mixture homogeneity was also explored. This study compares the effect of purely thermal ignition, purely chemical ignition, and how their interplay can influence the complete combustion of methane in typical mixtures and in homogeneous distributions of fuel in the combustion chamber. The CFD results demonstrated that temperature and chemistry are equally important in the ignition mechanism, and combining the two phenomena is effective at igniting the main chamber. Reduction of residual methane in the main combustion chamber (MCC) is most effective when chemical intermediates and thermal ignition are combined. A rudimentary analysis of the effect of fuel/air stratification was also conducted, and it demonstrated that a dramatic reduction in methane emissions is observed for homogeneous mixtures. The flow field in the main combustion chamber was shown to create detrimental stratification of the fuel/air mixture, which inhibited complete combustion of the methane in the main chamber. By contrast, in the extreme case of a perfectly homogeneous distribution of both chemical intermediates and fuel in the combustion chamber, it is possible to completely eliminate unburned methane in the main combustion chamber.
Fourier Analysis of the Vertical Ground Reaction Force During Walking: Applications for Quantifying Differences in Gait Strategies
Authors: Trentadue Taylor P. , Schmitt Daniel 
Published: April 2024

Time series biomechanical data inform our understanding of normal gait mechanics and pathomechanics. This study examines the utility of different quantitative methods to distinguish vertical ground reaction forces (VGRFs) from experimentally distinct gait strategies. The goals of this study are to compare measures of VGRF data—using the shape factor method and a Fourier series-based analysis—to (1) describe how these methods reflect and distinguish gait patterns and (2) determine which Fourier series coefficients discriminate normal walking, with a relatively stiff-legged gait, from compliant walking, using deep knee flexion and limited vertical oscillation. This study includes a reanalysis of previously presented VGRF data. We applied the shape factor method and fit 3- to 8-term Fourier series to zero-padded VGRF data. We compared VGRF renderings using Euclidean L2 distances and correlations stratified by gait strategy. Euclidean L2 distances improved with additional harmonics, with limited improvement after the seventh term. Euclidean L2 distances were greater in shape factor versus Fourier series renderings. In the 8 harmonic model, amplitudes of 9 Fourier coefficients—which contribute to VGRF features including peak and local minimum amplitudes and limb loading rates—were different between normal and compliant walking. The results suggest that Fourier series-based methods distinguish between gait strategies.
Manhattan Vision Screening and Follow-up Study (NYC-SIGHT): a nested cross-sectional assessment of falls risk within a cluster randomised trial
Authors: Hark Lisa A , Wang Yujia , Gorroochurn Prakash , Simon Phyllis R , Maruri Stefania C , Henriquez Desiree R , Diamond Daniel F , Horowitz Jason D , Park Lisa , Wang Qing , Auran James D , Carrion Jailine , Friedman David S , Liebmann Jeffrey L , Cioffi George A , Harizman Noga 
Published: April 2024

BackgroundTo investigate the feasibility of using the Stopping Elderly Accidents, Deaths and Injuries (STEADI) Falls Risk Tool Kit during community-based eye health screenings to assess falls risk of participants enrolled in the Manhattan Vision Screening and Follow-Up Study (NYC-SIGHT).MethodsCross-sectional analysis of data from a 5-year prospective, cluster-randomised clinical trial conducted in affordable housing developments in New York City in adults age 40 years and older. Prescreening questions determined whether participants were at risk of falling. STEADI tests classified participants at low, moderate or high risk of falling. Multivariate logistic regression determined odds of falls risk of all enrolled participants.Results708 participants completed the eye health screening; 351 (49.6%) performed STEADI tests; mean age: 71.0 years (SD±11.3); 72.1% female; 53.6% Black, non-Hispanic, 37.6% Hispanic/Latino. Level of falls risk: 32 (9.1%) low, 188 (53.6%) moderate and 131 (37.3%) high. Individuals age >80 (OR 5.921, 95% CI (2.383 to 14.708), p=0.000), had blurry vision (OR 1.978, 95% CI (1.186 to 3.300), p=0.009), high blood pressure (OR 2.131, 95% CI (1.252 to 3.628), p=0.005), arthritis (OR 2.29876, 95% CI (1.362 to 3.875), p=0.002) or foot problems (OR 5.239, 95% CI (2.947 to 9.314), p=0.000) had significantly higher odds of falling, emergency department visits or hospitalisation due to falling.ConclusionThis study detected a significant amount of falls risk in an underserved population. The STEADI Falls Risk screening questions were easy for eye care providers to ask, were highly predictive of falls risk and may be adequate for referral to occupational health and/or physical therapy.
Inequalities in sexual and reproductive outcomes among women aged 16–24 in England (2012–2019)
Authors: Solomon Danielle , Gibbs Jo , Burns Fiona , Mohammed Hamish , Migchelsen Stephanie J , Sabin Caroline A 
Published: April 2024

BackgroundWomen aged 16–24 in England have a high burden of sexual and reproductive morbidity, with particularly poor outcomes among people living in more deprived areas (including racially minoritised populations). This analysis used national data to examine the disparities within sexual and reproductive outcomes among this population and to assess whether the patterns of inequality were consistent across all outcomes.MethodsWithin this ecological study, univariable and multivariable Poisson regression analyses of neighbourhood-level data from national data sets were carried out to investigate the relationships of deprivation and ethnicity with each of six dependent variables: gonorrhoea and chlamydia testing rates, gonorrhoea and chlamydia test positivity rates, and abortion and repeat abortion rates.ResultsWhen comparing Index of Multiple Deprivation (IMD) decile 1 (most deprived) and IMD decile 10 (least deprived), chlamydia (RR 0.65) and gonorrhoea (0.79) testing rates, chlamydia (0.70) and gonorrhoea (0.34) positivity rates, abortion rates (0.45) and repeat abortion rates (0.72) were consistently lower in IMD decile 10 (least deprived). Similarly, chlamydia (RR 1.24) and gonorrhoea positivity rates (1.92) and repeat abortion rates (1.31) were higher among black women than white women. Results were similar when both ethnicity and deprivation were incorporated into multivariable analyses.ConclusionWe found similar patterns of outcome inequality across a range of sexual and reproductive outcomes, despite multiple differences in the drivers of each outcome. Our analysis suggests that there are broad structural causes of inequality across sexual and reproductive health that particularly impact the health of deprived and black populations.
Transcatheter Pulmonary Valve Replacement With the Harmony Valve in Patients Who Do Not Meet Recommended Oversizing Criteria on the Screening Perimeter Plot
Authors: McElhinney Doff B. , Gillespie Matthew J. , Aboulhosn Jamil A. , Cabalka Allison K. , Morray Brian H. , Balzer David T. , Qureshi Athar M. , Hoskoppal Arvind K. , Goldstein Bryan H. 
Published: April 2024

BACKGROUND:
Anatomic selection for Harmony valve implant is determined with the aid of a screening report and perimeter plot (PP) that depicts the perimeter-derived radius along the right ventricular outflow tract (RVOT) and projects device oversizing. The PP provides an estimation of suitability for implant, but its sensitivity as a screening method is unknown. This study was performed to describe anatomic features and outcomes in patients who underwent Harmony TPV25 implant despite a PP that predicted inadequate oversizing.

METHODS:
We reviewed RVOT anatomic features and measurements in patients who underwent transcatheter pulmonary valve replacement with the Harmony TPV25 device despite a PP that predicted inadequate oversizing.

RESULTS:
This study included 22 patients. There were no unsuccessful implants or adverse valve-related events. Anatomic features varied, but all patients fit into 1 of 3 anatomic types characterized by differences in RVOT dimensions. Type 1 patients (n=9) had a long RVOT with a choke point and a wide main pulmonary artery. Type 2 patients (n=6) had a short RVOT that was pyramidal in shape, with no choke point, and extensive main pulmonary artery lengthening/expansion during systole. Type 3 patients (n=7) had a short, bulbous main pulmonary artery with a choke point and an open pulmonary artery bifurcation.

CONCLUSIONS:
Transcatheter pulmonary valve replacement with the Harmony valve is feasible in some patients whose PP fit analysis predicts inadequate oversizing. All cases in this series fit into 1 of 3 anatomic patterns, which are not identified in the screening report. Implanters must review cases individually to assess the feasibility of the implant.
Resting-state global brain activity induces bias in fMRI motion estimates
Authors: Mao Yixiang , Chen Conan , Nguyen Truong , Liu Thomas T. 
Published: April 2024

Abstract
Head motion is a significant source of artifacts in resting-state fMRI (rsfMRI) studies and has been shown to affect resting-state functional connectivity (rsFC) measurements. In many rsfMRI studies, motion parameters estimated from volume registration are used to characterize head motion and to mitigate motion artifacts in rsfMRI data. While prior task-based fMRI studies have shown that task-evoked brain activations may induce temporally correlated bias in the motion estimates, resulting in artificial activations after registration, relatively little is known about neural-related bias in rsfMRI motion parameter. In this study, we demonstrate that neural-related bias exists in rsfMRI motion estimates and characterize the potential effects of the bias on rsFC estimates. Using a public multi-echo rsfMRI dataset, we use the differences between motion estimates from the first echo and second echo data as a measure of neural-induced bias. We show that the resting-state global activity of the brain, as characterized with the global signal (GS), induces bias in the motion estimates in the y- and z-translational axes. Furthermore, we demonstrate that the GS-related bias reflects superior-inferior and anterior-posterior asymmetries in the GS beta coefficient map. Finally, we demonstrate that regression with biased motion estimates can negatively bias rsFC estimates and also reduce rsFC differences between young and old subjects.
Evaluating the Ripple Effects of Knowledge Editing in Language Models
Authors: Cohen Roi , Biran Eden , Yoran Ori , Globerson Amir , Geva Mor 
Published: April 2024

Abstract
Modern language models capture a large body of factual knowledge. However, some facts can be incorrectly induced or become obsolete over time, resulting in factually incorrect generations. This has led to the development of various editing methods that allow updating facts encoded by the model. Evaluation of these methods has primarily focused on testing whether an individual fact has been successfully injected, and if similar predictions for other subjects have not changed. Here we argue that such evaluation is limited, since injecting one fact (e.g., “Jack Depp is the son of Johnny Depp”) introduces a “ripple effect” in the form of additional facts that the model needs to update (e.g., “Jack Depp is the sibling of Lily-Rose Depp”). To address this, we propose novel evaluation criteria that consider the implications of an edit on related facts. Using these criteria, we then construct RippleEdits, a diagnostic benchmark of 5K factual edits, capturing various types of ripple effects. We evaluate prominent editing methods on RippleEdits, showing that they fail to introduce consistent changes in the model’s knowledge. In addition, we find that a simple in-context editing baseline obtains the best scores on our benchmark, suggesting a promising research direction for model editing.1
Retrieve What You Need: A Mutual Learning Framework for Open-domain Question Answering
Authors: Wang Dingmin , Huang Qiuyuan , Jackson Matthew , Gao Jianfeng 
Published: April 2024

Abstract
An open-domain question answering (QA) system usually follows a retrieve-then-read paradigm, in which a retriever is used to retrieve relevant passages from a large corpus, and then a reader generates answers based on the retrieved passages and the original question. In this paper, we propose a simple and novel mutual learning framework to improve the performance of retrieve-then-read-style models via an intermediate module named the knowledge selector, which we train with reinforcement learning. The key benefits of our proposed intermediate module are: 1) no requirement for additional annotated question-passage pairs; 2) improvements in both retrieval and QA performance, as well as computational efficiency, compared to prior competitive retrieve-then-read models; 3) with no finetuning, improvement in the zero-shot performance of large-scale pre-trained language models, e.g., ChatGPT, by encapsulating the input with relevant knowledge without violating the input length constraint.
Host tree-based scenario modelling for predicting a key edible insect, mopane worm Gonimbrasia belina (Westwood, 1894) distribution in Southern Africa
Authors: Meltus Q.J. , Mudereri B.T. , Mutamiswa R. , Abdel-Rahman E.M. , Matunhu J. , Musundire R. , Niassy S. , Tonnang H.E.Z. 
Published: April 2024

Abstract
Gonimbrasia belina, known as the mopane worm, is a large edible caterpillar in tropical and subtropical regions. However, little is known about the bioecology of this species as influenced by its host trees. This study evaluated the importance of different potential host trees in understanding mopane worms’ behaviour and spatial distribution. To assess their relative importance, the study compared models incorporating various mopane worm host trees and predictor variables. Using the species distribution modelling (SDM) package in R, an ensemble of random forest (RF), support vector machine (SVM), and boosted regression tree (BRT) algorithms were used to assess the spatial extent of mopane worm distribution in Southern Africa. Four host tree-based scenarios were developed to assess their contribution to the relative distribution of the mopane worm i.e. (1) by excluding all the potential host trees as explanatory variables and considering only the environmental variables, (2) focusing on the primary host tree, Colophospermum mopane as an explanatory variable together with the other environmental variables, (3) incorporating all the host trees, including C. mopane and (4) examining all other host trees excluding C. mopane. Results demonstrated that incorporating all host trees enhanced the models’ predictive abilities (mean AUC = 0.87) underscoring the significant impact of the alternative host trees on the mopane worm distribution patterns beyond just the C. mopane. This study highlights the significance of host trees in predicting the behaviour and distribution of mopane worm populations, providing valuable insights and decision-making for mopane worm use as an alternative protein source, conservation efforts, and land management practices.
Global Observations of Deep Ocean Kinetic Energy Transfers
Authors: Sévellec F. , Colin de Verdière A. , Kolodziejczyk N. 
Published: April 2024

Abstract
Observations of deep Argo displacements (located between 950 and 1150 dbar) and their associated integrated Lagrangian velocities allow for the first time to compute worldwide deep horizontal transfers of kinetic energy (KE) between the 3° × 3° mean and eddy reservoirs [mean kinetic energy (MKE) and eddy kinetic energy (EKE), respectively]. This diagnostic reveals that the transfers are mainly localized along western boundaries and in the Southern Ocean. Overall, the MKE-to-EKE transfers appear dominant globally and in all specifically tested regions (i.e., Gulf Stream, Kuroshio, Agulhas Current, and Antarctic Circumpolar Current). However, an important exception is the Zapiola Gyre where EKE-to-MKE transfers dominate. Beyond that, we find that horizontal KE transfers are better described by the horizontal properties of the mean flow deformation (divergence and strain) than by the horizontal properties of the turbulent velocities. Our theoretical analysis also demonstrates that the mean flow vorticity does not contribute to KE transfers. We show the existence of two consistent transfer modes: one from MKE to EKE and one from EKE to MKE, which are based on the eigendirections of the mean flow deformation tensor. The alignment of the turbulence along these directions selects the transfer modes, and it is the competition between these two transfer modes that leads to the actual transfers. We compute these transfer modes globally, regionally, and locally. We explain the distinctive situation of the Zapiola Gyre by the favored alignment of the turbulence with the EKE-to-MKE transfer mode. Overall, the dominance of the large-scale flow properties on the structure of the MKE-to-EKE transfers suggests the potential for large-scale parameterization.