Objective: This study examined whether the negative association between children's attention difficulties and their academic functioning is largely confined to children whose attention problems persist across early grades and whether it depends on when attention problems emerge in children's schooling.
Method: Children from the normative sample of the Fast Track study were classified into four attention problem groups based on the presence versus absence of attention problems in first and second grade.
Results: Those with attention problems in both grades showed a decline in reading and math achievement during the K-5 interval relative to children with attention problems in first grade only. Both groups of inattentive first graders also performed worse than comparison children. In contrast, children whose attention problems emerged in second grade did not differ from comparison children on any achievement outcome performed significantly better than inattentive first graders.
Conclusion: The implications of these findings are discussed.
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http://dx.doi.org/10.1177/1087054713507974 | DOI Listing |
Int J Lang Commun Disord
January 2025
Department of Language and Cognition, University College London, London, UK.
Background: Global aphasia is a severe communication disorder affecting all language modalities, commonly caused by stroke. Evidence as to whether the functional communication of people with global aphasia (PwGA) can improve after speech and language therapy (SLT) is limited and conflicting. This is partly because cognition, which is relevant to participation in therapy and implicated in successful functional communication, can be severely impaired in global aphasia.
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January 2025
School of Mechanical Engineering, Sichuan University, Chengdu 610065, China.
With the digital transformation of the manufacturing industry, data monitoring and collecting in the manufacturing process become essential. Pointer meter reading recognition (PMRR) is a key element in data monitoring throughout the manufacturing process. However, existing PMRR methods have low accuracy and insufficient robustness due to issues such as blur, uneven illumination, tilt, and complex backgrounds in meter images.
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January 2025
Beijing Institute of Spacecraft System Engineering, China Academy of Space Technology, Beijing 100094, China.
The Chang'e-6 (CE-6) landing area on the far side of the Moon is located in the southern part of the Apollo basin within the South Pole-Aitken (SPA) basin. The statistical analysis of impact craters in this region is crucial for ensuring a safe landing and supporting geological research. Aiming at existing impact crater identification problems such as complex background, low identification accuracy, and high computational costs, an efficient impact crater automatic detection model named YOLOv8-LCNET (YOLOv8-Lunar Crater Net) based on the YOLOv8 network is proposed.
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January 2025
School of Mechanical Engineering, Guizhou University, Guiyang 550028, China.
Deep learning has performed well in feature extraction and pattern recognition and has been widely studied in the field of fault diagnosis. However, in practical engineering applications, the lack of sample size limits the potential of deep learning in fault diagnosis. Moreover, in engineering practice, it is usually necessary to obtain multidimensional fault information (such as fault localization and quantification), while current methods mostly only provide single-dimensional information.
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January 2025
College of Transportation, Shandong University of Science and Technology, Qingdao 266590, China.
To address the problems that exist in the target detection of vehicle-mounted visual sensors in foggy environments, a vehicle target detection method based on an improved YOLOX network is proposed. Firstly, to address the issue of vehicle target feature loss in foggy traffic scene images, specific characteristics of fog-affected imagery are integrated into the network training process. This not only augments the training data but also improves the robustness of the network in foggy environments.
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