bluuebunny/crossref_metadata_2025_split huggingface dataset:
Probabilistic estimates of future changes in evaporation from the Caspian Sea based on multimodel ensembles of CMIP6 projections
Authors: Hoseini S. Mahya , Zolfaghari Mohammad R. , Soltanpour Mohsen 
Published: September 2023

AbstractThe Caspian Sea level (CSL) is strongly sensitive to climate‐induced changes in its water balance components, especially evaporation from its surface as the main expenditure component of the Caspian Sea's (CS) water budget. Projecting evaporation and determining associated uncertainties obtained from such studies are critical for reliably predicting future CSL fluctuations and developing mitigation and adaptation strategies. This paper studies the projected changes in evaporation from the CS using 18 global climate models (GCMs) from the latest Coupled Model Intercomparison Project phase 6 (CMIP6) and Meyer's semi‐empirical formula. Future evaporation projections are constructed employing a weighted combination of the top‐ranked GCMs, including all ensemble members of selected individual models in a probabilistic framework. This study estimates late 21st century median evaporation of 945, 1016, 1105 and 1173 mm under the low‐emission, medium‐emission, medium‐to‐high emission and high‐emission scenarios, respectively. The weighted multimodel ensemble suggests CS's annual mean evaporation is projected to substantially increase by 3.9%, 13.2%, 20% and 27.9% under SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5, respectively, for the late 21st century against the reference period. According to the spatial distribution of evaporation, arid eastern regions of CS experience higher evaporation than semi‐arid western and southwestern temperate regions. Additionally, the northwestern continental regions experience the least evaporation over the CS.
The efficacy of tropical and extratropical predictors for long‐lead El Niño‐Southern Oscillation prediction: A study using a machine learning algorithm
Authors: Song Wan‐Jiao , Yu Jin‐Yi , Lian Tao 
Published: September 2023

AbstractThis study illustrates the considerable improvement in accuracy achievable for long‐lead forecasts (18 months) of the Ocean Niño Index (ONI) through the utilization of a long short‐term memory (LSTM) machine learning algorithm. The research assesses the predictive potential of eight predictors from both tropical and extratropical regions constructed based on sea surface temperature, outgoing longwave radiation, sea surface height and zonal and meridional wind anomalies. In comparison to linear regression model forecasts, the LSTM model outperforms them for both the tropical and extratropical predictor sets. Among all the predictors, the western North Pacific (WNP) index demonstrates the highest prediction skill in ONI forecasts, followed by the North Tropical Atlantic (NTA) index and then the sea surface height index. While other predictors help the LSTM model to forecast either the phase variation of the amplitude variation of the observed ONI, the extratropical WNP predictor enables the LSTM model to forecast both variations. This superiority can be attributed to the involvement of SST anomalies in the WNP region in both tropical and extratropical El Niño–Southern Oscillation (ENSO) dynamics, allowing for the utilization of predictive potential from both components of ENSO dynamics. The study also concludes that the extratropical ENSO dynamics provide a robust source of predictability for long‐lead ENSO forecasts, which can be effectively harnessed using the LSTM model.
Behavioral multi‐lever decision‐making: A study of consumer return policy, price, and inventory decisions
Authors: Oh Han Kyul , Abdulla Huseyn , Oliva Rogelio 
Published: September 2023

AbstractConsumer return policies have been long recognized and studied by operations management scholars as an important managerial lever in a retail environment. Yet, the behavioral aspects of return policy decision‐making and interaction of return policy decisions with other common operational decisions have not been investigated to date. We present a behavioral analysis of return policy decision‐making in a retail environment with aggregate demand and individual product valuation uncertainties. Leveraging a generalized newsvendor context, we conduct a randomized behavioral experiment to understand how individuals make each of the three key retail decisions—refund amount, price, and order quantity—and the causal effect of salvage value on these decisions. We find that decision‐makers exhibit behavioral regularities in making decisions across the three levers and they react to changes in the operating conditions in a boundedly rational manner, suggesting the use of heuristics. Based on behavioral regularities that we observe in our data—that is, responses, time‐dependent effects, and decision dependencies—we develop a process theory based on behavioral decision‐making tenets that offers a new direction with testable hypotheses for future research. The process theory describes a conditional decision‐making heuristic that leads to a propagation of decision errors across different levers as well as lever‐specific decision biases.
A mapping exercise using automated techniques to develop a search strategy to identify systematic review tools
Authors: Sutton Anthea , O'Keefe Hannah , Johnson Eugenie Evelynne , Marshall Christopher 
Published: September 2023

AbstractThe Systematic Review Toolbox aims provide a web‐based catalogue of tools that support various tasks within the systematic review and wider evidence synthesis process. Identifying publications surrounding specific systematic review tools is currently challenging, leading to a high screening burden for few eligible records. We aimed to develop a search strategy that could be regularly and automatically run to identify eligible records for the SR Toolbox, thus reducing time on task and burden for those involved. We undertook a mapping exercise to identify the PubMed IDs of papers indexed within the SR Toolbox. We then used the Yale MeSH Analyser and Visualisation of Similarities (VOS) Viewer text‐mining software to identify the most commonly used MeSH terms and text words within the eligible records. These MeSH terms and text words were combined using Boolean Operators into a search strategy for Ovid MEDLINE. Prior to the mapping exercise and search strategy development, 81 software tools and 55 ‘Other’ tools were included within the SR Toolbox. Since implementation of the search strategy, 146 tools have been added. There has been an increase in tools added to the toolbox since the search was developed and its corresponding auto‐alert in MEDLINE was originally set up. Developing a search strategy based on a mapping exercise is an effective way of identifying new tools to support the systematic review process. Further research could be conducted to help prioritise records for screening to reduce reviewer burden further and to adapt the strategy for disciplines beyond healthcare.
The American Woodcock Singing Ground Survey largely conforms to the phenology of male woodcock migration
Authors: Blomberg Erik J. , Fish Alexander C. , Berigan Liam A. , Roth Amber M. , Rau Rebecca , Clements Sarah J. , Balkcom Greg , Carpenter Bobbi , Costanzo Gary , Duguay Jeffrey , Graham Clayton L. , Harvey William , Hook Michael , Howell Douglas L. , Maddox Seth , McWilliams Scott , Meyer Shawn W. , Nichols Theodore C. , Pollard J. Bruce , Roy Christian , Slezak Colby , Stiller Josh , Tetreault Mathieu , Williams Lisa 
Published: September 2023

AbstractAmerican woodcock (Scolopax minor; woodcock) are monitored, in part, by counts of displaying male woodcock collected via the American Woodcock Singing Ground Survey (SGS), which suggests long‐term, range‐wide declines in woodcock populations. Data from the SGS have been used extensively to develop conservation plans, direct management actions, and understand causes of decline. To avoid bias, the SGS should be timed to avoid spring migration, and the distribution of survey routes should coincide with woodcock breeding distribution. Our objectives for this research were to evaluate SGS timing with the phenology of male woodcock migration, relate the spatial coverage of the SGS to male woodcock breeding distributions, and explore other sources of variation in woodcock migration timing. We marked 133 male woodcock captured throughout eastern North America with global positioning system (GPS) transmitters during 2019–2022, and compared the timing of their spring migration with the spatiotemporal stratification of the SGS. Most woodcock (74%) completed migration prior to the onset of the SGS. In the northernmost SGS zone, a greater percentage of males (34%) continued migration during the survey window; however, the influence of this mismatch is offset because SGS routes were run more frequently during the second half of the window. Young woodcock completing their first spring migration took 8.6 days longer to do so, on average, compared to adults, and so were more likely to migrate during the SGS window. We found little evidence that timing of migration varied among years. Existing SGS routes cover the majority of male woodcock post‐migratory breeding distribution, with 90% of male woodcock establishing final breeding sites within the spatial coverage of the SGS. Our results confirm the SGS includes some migrating males, with the proportion relative to resident breeding males increasing in more northern survey strata. Our data suggests these errors are unlikely to bias trend estimates at large scales (e.g., within woodcock management regions), but there may be potential for bias at more local scales (e.g., state or provincial population indices).
Understanding the drivers of organizational business performance from the human capital perspective
Authors: Serenko Alexander , Abubakar A. Mohammed , Bontis Nick 
Published: September 2023

AbstractThe purpose of this study is to understand the drivers of organizational business performance from the perspective of human capital. Data were collected from 691 employees working in 15 North American credit unions. The model was developed and tested by means of the Partial Least Squares Structural Equation Modeling technique. This study illuminates an underexplored mechanism driving the association between transformational leadership and business performance based on several theoretical frameworks such as leader–member exchange theory, the conservation of resources theory, the heuristic model of employee turnover, equity theory, and capital‐based view. The findings indicate that transformational leaders provide their subordinates with constructive feedback and offer training and development (T&D) opportunities, which are the key factors driving employee job satisfaction. Employee job satisfaction curtails turnover intention, which, in turn, reduces human capital outflow and, consequently, increases business performance. Managers should always act as true transformational leaders and provide their subordinates with relevant performance feedback and ample T&D opportunities. Workers who undergo T&D at the expense of their organization become more loyal and are less likely to leave even though they become more marketable. Organizations are recommended to administer periodic employee satisfaction surveys and prevent the exodus of human capital, which may be difficult to replenish.
Reconstruction of Vocal Fold Medial Surface 3D Trajectories: Effects of Neuromuscular Stimulation and Airflow
Authors: Schlegel Patrick , Chung Hye Rhyn , Döllinger Michael , Chhetri Dinesh K. 
Published: September 2023

IntroductionAnalysis of medial surface dynamics of the vocal folds (VF) is critical to understanding voice production and treatment of voice disorders. We analyzed VF medial surface vibratory dynamics, evaluating the effects of airflow and nerve stimulation using 3D reconstruction and empirical eigenfunctions (EEF).Study DesignIn vivo canine hemilarynx phonation.MethodsAn in vivo canine hemilarynx was phonated while graded stimulation of the recurrent and superior laryngeal nerves (RLN and SLN) was performed. For each phonatory condition, vibratory cycles were 3D reconstructed from tattooed landmarks on the VF medial surface at low, medium, and high airflows. Parameters describing medial surface trajectory shape were calculated, and underlying patterns were emphasized using EEFs. Fundamental frequency and smoothed cepstral peak prominence (CPPS) were calculated from acoustic data.ResultsConvex‐hull area of landmark trajectories increased with increasing flow and decreasing nerve activation level. Trajectory shapes observed included circular, ellipsoid, bent, and figure‐eight. They were more circular on the superior and anterior VF, and more elliptical and line‐like on the inferior and posterior VF. The EEFs capturing synchronal opening and closing (EEF1) and alternating convergent/divergent (EEF2) glottis shapes were mostly unaffected by flow and nerve stimulation levels. CPPS increased with higher airflow except for low RLN activation and very dominant SLN stimulation.ConclusionWe analyzed VF vibration as a function of neuromuscular stimulation and airflow levels. Oscillation patterns such as figure‐eight and bent trajectories were linked to high nerve activation and flow. Further studies investigating longer sections of 3D reconstructed oscillations are needed.Level of EvidenceN/A, Basic Science Laryngoscope, 134:1249–1257, 2024
A Meta‐analysis of the effects of ground‐based extraction technologies on fine roots in forest soils
Authors: Latterini Francesco , Dyderski Marcin K. , Horodecki Paweł , Rawlik Mateusz , Stefanoni Walter , Högbom Lars , Venanzi Rachele , Picchio Rodolfo , Jagodziński Andrzej M. 
Published: September 2023

AbstractFine roots are an important component of forest soil as they play a key role in fundamental processes like plant nutrition and water supply. As with all the features of forest soil, the compaction related to the forest operations and, in particular, to the wood extraction via ground‐based technologies could lead to a significant impact on the presence of fine roots in the soil affected by the passage of the machines. Considering the lack of a review, we used a meta‐analytic approach to synthesise effect sizes of ground‐based extraction technologies affecting the presence of fine roots in the soil, using a multivariate mixed‐effects meta‐analytic model. The obtained results revealed that the presence of fine roots in the soil affected by the passage of the machines was significantly reduced by both skidding (g = −1.23, 95%CI ‐1.87, −0.60) and forwarding (g = −1.37, 95%CI ‐2.01, −0.74). Due to the higher soil compaction caused by forwarding, this method had a marginally but statistically significant greater impact than skidding. We further confirmed the hypothesis that soil compaction and the presence of fine roots were strongly correlated, with the latter being greatly reduced in compacted soils characterised by higher bulk density. What is more, even more than 20 years after a harvesting intervention, the presence of fine roots was significantly lower in both strip roads (forwarding) and skid trails (skidding) as compared to areas which were not impacted by the machine passage. This shows that fine roots are particularly vulnerable to forest operations. On the other hand, the majority of the trails in the database used for the meta‐analysis were created in countries that favour the creation of a small number of widely used trails. Therefore, it would be scientifically valuable to do a comparative evaluation in various forestry contexts, such as in the Mediterranean area, where the development of the forest trails network is oriented on creating a large number of trails with low traffic volumes. Because machinery‐induced soil compaction is the major driver of the decrease in fine roots in skid trails and strip roads, both the application of best management practices as well as of a smarter planning of the trail network to limit soil compaction are strongly recommended. Both applications are highly recommended to be used in the planning phase and in the practical implementation of logging activities.
The action and resistance mechanisms of Lenvatinib in liver cancer
Authors: Buttell Anna , Qiu Wei 
Published: September 2023

AbstractLenvatinib is a tyrosine kinase inhibitor that prevents the formation of new blood vessels namely by inhibiting tyrosine kinase enzymes as the name suggests. Specifically, Lenvatinib acts on vascular endothelial growth factor receptors 1−3 (VEGFR1−3), fibroblast growth factor receptors 1−4 (FGFR1−4), platelet‐derived growth factor receptor‐alpha (PDGFRα), tyrosine‐kinase receptor (KIT), and rearranged during transfection receptor (RET). Inhibition of these receptors works to inhibit tumor proliferation. It is through these inhibition mechanisms that Lenvatinib was tested to be noninferior to Sorafenib. However, resistance to Lenvatinib is common, making the positive effects of Lenvatinib on a patient's survival null after resistance is acquired. Therefore, it is crucial to understand mechanisms related to Lenvatinib resistance. This review aims to piece together various mechanisms involved in Lenvatinib resistance and summarizes the research done so far investigating it.
The Global Burden of Disease Attributable to Diet High in Red Meat in 204 Countries and Territories, 1999–2019: An updated Analysis of the Global Burden of Disease Study
Authors: Wu Zenghong , Wang Weijun , Zhang Kun , Fan Mengke , Lin Rong 
Published: September 2023

ScopeThe study aims to estimates of the deaths and disability‐adjusted life year rates (DALYs) of a diet high in red meat from 1999 to 2019.Methods and resultsThe deaths and disability‐adjusted life year rates (DALYs) attributable to diet high in red meat were analyzed by sex, age, and geographical location and by Socio‐demographic Index (SDI) from 1999 to 2019.ResultsGlobally, deaths and DALYs attributable to diets high in red meat have steadily increased between 1999 and 2019. The global deaths attributable to diet high in red meat have increased from 319,338 (95% UI 190,418 to 441,406) in 1999 to 411,066 (95% UI 250,993 to 573,864) in 2019 for females, and have increased from 335,711 (95% UI 183,491 to 472,091) in 1999 to 484,608 (95% UI 282,347 to 686,919) in 2019 for males. The global DALYs attributable to diet high in red meat have increased from 7,763,803 (95% UI 5,023,428 to 10,370,477) in 1999 to 10,164,451 (95% UI 6,816,205 to 13,348,860) in 2019 for females, and have increased from 9,564,377 (95% UI 5,528,491 to 13,231,311) in 1999 to 13,696,622 (95% UI 8,669,245 to 18,725,223) in 2019 for males.ConclusionGlobally, since 1999, deaths and DALYs caused by diets high in red meat have steadily increased.
Automatic view plane prescription for cardiac magnetic resonance imaging via supervision by spatial relationship between views
Authors: Wei Dong , Huang Yawen , Lu Donghuan , Li Yuexiang , Zheng Yefeng 
Published: September 2023

AbstractBackgroundView planning for the acquisition of cardiac magnetic resonance (CMR) imaging remains a demanding task in clinical practice.PurposeExisting approaches to its automation relied either on an additional volumetric image not typically acquired in clinic routine, or on laborious manual annotations of cardiac structural landmarks. This work presents a clinic‐compatible, annotation‐free system for automatic CMR view planning.MethodsThe system mines the spatial relationship—more specifically, locates the intersecting lines—between the target planes and source views, and trains U‐Net‐based deep networks to regress heatmaps defined by distances from the intersecting lines. On the one hand, the intersection lines are the prescription lines prescribed by the technologists at the time of image acquisition using cardiac landmarks, and retrospectively identified from the spatial relationship. On the other hand, as the spatial relationship is self‐contained in properly stored data, for example, in the DICOM format, the need for additional manual annotation is eliminated. In addition, the interplay of the multiple target planes predicted in a source view is utilized in a stacked hourglass architecture consisting of repeated U‐Net‐style building blocks to gradually improve the regression. Then, a multiview planning strategy is proposed to aggregate information from the predicted heatmaps for all the source views of a target plane, for a globally optimal prescription, mimicking the similar strategy practiced by skilled human prescribers. For performance evaluation, the retrospectively identified planes prescribed by the technologists are used as the ground truth, and the plane angle differences and localization distances between the planes prescribed by our system and the ground truth are compared.ResultsThe retrospective experiments include 181 clinical CMR exams, which are randomly split into training, validation, and test sets in the ratio of 64:16:20. Our system yields the mean angular difference and point‐to‐plane distance of 5.68 and 3.12 mm, respectively, on the held‐out test set. It not only achieves superior accuracy to existing approaches including conventional atlas‐based and newer deep‐learning‐based in prescribing the four standard CMR planes but also demonstrates prescription of the first cardiac‐anatomy‐oriented plane(s) from the body‐oriented scout.ConclusionsThe proposed system demonstrates accurate automatic CMR view plane prescription based on deep learning on properly archived data, without the need for further manual annotation. This work opens a new direction for automatic view planning of anatomy‐oriented medical imaging beyond CMR.