It has been well documented that formulaic language (such as collocations; e.g., provide information) enjoys a processing advantage over novel language (e.g., compare information). In natural language use, however, many formulaic sequences are often inserted with words intervening in between the individual constituents (e.g., provided information → provide some of the information). Whether or not the processing advantage persists in nonadjacent forms remains largely unknown. The present study thus sought to address this gap by recording the eye movements of Chinese native speakers when they were reading sentences embedded with formulaic sequences (high frequency collocations) versus novel phrases (low frequency controls), in their adjacent (e.g., 'resolve difficulties' vs. 'experience difficulties'), short-insertion (e.g., 'resolve these difficulties' vs. 'experience these difficulties'), and long-insertion forms (e.g., 'resolved so many difficulties' vs. 'experienced so many difficulties'). Results suggested that the processing advantage for formulaic language over novel language existed not only in their adjacent form, but also in their short-insertion form, albeit the magnitude of the processing advantage diminished with the increase of insertion length. The persistence of FL processing advantage is in line with usage-based approach to language learning, processing, and use.
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http://dx.doi.org/10.1007/s10936-024-10040-5 | DOI Listing |
BMC Health Serv Res
January 2025
School of Pharmacy and Biomolecular Sciences (PBS), Royal College of Surgeons in Ireland (RCSI), 1st Floor Ardilaun House Block B, 111 St Stephen's Green, Dublin 2, Ireland.
Background: The advantages of electronic health records (EHRs) are well-documented regarding the process of care, enhanced data accessibility and cost savings. However, EHR design can also contribute to usability challenges, with poorly designed EHRs being implicated in user errors including patient overdoses. Our study seeks to evaluate how EHR design influences both usability and medication safety.
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January 2025
Scientific Affairs Department, Al-Mustaqbal University, Babylon, 51001, Iraq.
This study investigates the application of various neural network-based models for predicting temperature distribution in freeze drying process of biopharmaceuticals. For heat-sensitive biopharmaceutical products, freeze drying is preferred to prevent degradation of pharmaceutical compounds. The modeling framework is based on CFD (Computational Fluid Dynamics) and machine learning (ML).
View Article and Find Full Text PDFNat Commun
January 2025
i-lab, Vacuum Interconnected Nanotech Workstation (Nano-X), Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, China.
Transition-metal carbides have been advocated as the promising alternatives to noble-metal platinum-based catalysts in electrocatalytic hydrogen evolution reaction over half a century. However, the effectiveness of transition-metal carbides catalyzing hydrogen evolution in high-pH electrolyte is severely compromised due to the lowered proton activity and intractable alkaline-leaching issue of transition-metal centers. Herein, on the basis of validation of molybdenum-carbide model-catalyst system by taking advantage of surface science techniques, MoC micro-size spheres terminated by Al doped MoO layer exhibit a notable performance of alkaline hydrogen evolution with a near-zero onset-potential, a low overpotential (40 mV) at a typical current density of 10 mA/cm, and a small Tafel slope (45 mV/dec), as well as a long-term stability for continuous hydrogen production over 200 h.
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January 2025
Chongqing Vocational Institute of Tourism, Chongqing, China.
To enhance enterprises' interactive exploration capabilities for unstructured chart data, this paper proposes a multimodal chart question-answering method. Facing the challenge of recognizing curved and irregular text in charts, we introduce Gaussian heatmap encoding technology to achieve character-level precise text annotation. Additionally, we combine a key point detection algorithm to extract numerical information from the charts and convert it into structured table data.
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January 2025
Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541, Republic of Korea.
Model optimization is a problem of great concern and challenge for developing an image classification model. In image classification, selecting the appropriate hyperparameters can substantially boost the model's ability to learn intricate patterns and features from complex image data. Hyperparameter optimization helps to prevent overfitting by finding the right balance between complexity and generalization of a model.
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