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In this study, a carboxy esterification reaction was used to graft the hydrophilic polymers polyethylene glycol (PEG) and polyvinyl alcohol (PVA) onto the surface of carbon fibers (CFs). The properties of the grafted CFs were investigated by scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TG) and through the measurement of interlaminar shear strength (ILSS). SEM enabled the graft morphology on CF surfaces to be determined. In comparisons of grafted and non-grafted CFs, AFM indicated that the roughness was significantly improved; XPS showed that the concentration of oxygen-containing functional groups increased by 186.1%; TG showed that the grafting rate of CF-grafted PEG (CF-g-PEG) was 0.5%, and that of CF-grafted PVA (CF-g-PVA) was 2.0%; and the ILSS of CF-g-PEG and CF-g-PVA increased by 22.7% and 43.0%, respectively. We conclude that esterification grafting is an effective method for modifying the physicochemical properties of CFs and improving the interfacial adhesion of composites., INTRODUCTION It is generally believed that carbon fibers (CFs) are the most successful commercial carbon material to be developed in the past 40 years, and their discovery is regarded as [...]

Crack identification is essential for the preventive maintenance of asphalt pavement. Through periodic inspection, the characteristics of existing and emerging cracks can be obtained, and the pavement condition index can be calculated to assess pavement health. The most common method to estimate the area of cracks in an image is to count the number of grid cells or boxes that cover the cracks in an image. Accurate and efficient crack identification is the premise of crack assessment. However, the current patch‐based classification method is limited by the receptive field and cannot be used to directly classify cracks. Furthermore, the postprocessing algorithm in anchor‐based detection is not explicitly optimized for crack topology. In this paper, a new model, which is the fusion of grid‐based classification and box‐based detection based on You Only Look Once version 5 (YOLO v5) is developed and described for the first time. The accuracy and efficiency of the model are high partly due to the implementation of a shared backbone network, multi‐task learning, and joint training. The non‐maximum suppression (NMS)–area‐reduction suppression (ARS) algorithm is presented to filter redundant, overlapping prediction boxes in the postprocessing stage for the crack topology, and the mapping and matching algorithm is proposed to combine the advantages of both the grid‐based and box‐based models. A double‐labeled dataset containing tens of thousands of asphalt pavement images is assembled, and the proposed method is verified on the test set. The fusion model has superior performance over the individual classification and detection models, and the proposed NMS‐ARS algorithm further improves the detection accuracy. Experimental results demonstrate that the presented method effectively realizes automatic crack identification for asphalt pavement. [ABSTRACT FROM AUTHOR]

Dorsal stream is an important pathway for visual information transmission. As a part of the dorsal pathway, the middle temporal visual motion areas (V5/MT+) are mainly responsible for visual motion processing and the ability of visual motion processing is closely related to reading. Compared with alphabetic scripts, the visual structure of Chinese characters is more complex and there are no clear grapheme-phoneme correspondence rules. So the ability of visual analysis plays an important role in Chinese character processing. This study first investigated the brain activation of Chinese dyslexic children and children of the same chronological age when they observed coherent motion stimuli. ROI analysis indicated that only the activation of left V5/MT+ was significantly weaker in dyslexics than that in the control group. The activity of the magnocellular-dorsal stream was closely related to orthographic awareness in the combined data (two groups) and the typical children. In dyslexia group, the stronger the activation of V5/MT+ was, the worse the phonological awareness, rapid naming performance and orthographic awareness were. In short, Chinese dyslexic children were deficient in the activation of the left V5/MT+ and the activity of the magnocellular-dorsal pathway was closely related to orthographic awareness in Chinese pupils. [ABSTRACT FROM AUTHOR]

The high local electron density and efficient charge carrier separation are two important factors to affect photocatalytic activity, especially for the CO2 photoreduction reaction. However, the systematic studies on the structure‐functional relationship regarding the above two factors based on precisely structure model are rarely reported. Herein, as a proof‐of‐concept, we developed a new strategy on the evaluation of local electron density by controlling the relative electron‐deficient (ED) and electron‐rich (ER) intensity of monomer at a molecular level based on three rational‐designed vinylene‐linked sp2 carbon‐covalent organic frameworks (COFs). As expected, the as‐prepared vinylene‐linked sp2 carbon‐conjugated metal‐covalent organic framework (MCOFs) (VL‐MCOF‐1) with molecular junction exhibited excellent activities for CO2‐to‐HCOOH conversion (283.41 μmol g−1 h−1) and high selectivity of 97.1 %, much higher than the VL‐MCOF‐2 and g‐C34N6‐COF, which is due to the synergistic effect of the multi‐electronic metal clusters (Cu3(PyCA)3) (PyCA=pyrazolate‐4‐carboxaldehyde) as strong ER roles and cyanopyridine units as ED roles and active sites, as well as the boosted photo‐induced charge separation efficiency of vinyl connection and increased light utilization ability. These results not only provide a strategy for regulating the electron‐density distribution of photocatalysts at the molecular level but also offers profound insights for metal clusters‐based COFs to effective CO2 conversion. [ABSTRACT FROM AUTHOR]

Aims: Hikikomori is a common phenomenon reported in Japan and many other countries. However, the broad trends of the research publications on hikikomori are unclear. Therefore, this study examined the patterns of research on hikikomori using bibliometric analysis. Methods: Relevant publications were searched in Web of Science. Bibliometric analyses were performed with CiteSpace, R and VOSviewer. Results: In total, 297 publications on hikikomori met the eligibility criteria. The International Journal of Social Psychiatry (IF = 10.461) published the most papers (K = 17, or 5.7%) on hikikomori. Takahiro A. Kato from Kyushu University (41; 13.8%; H‐index = 18) was the most influential author, while Takahiro A. Kato (total link strength [TLS]: 235), Alan R. Teo (TLS: 157), and Masaru Tateno (TLS: 153) separately had the strongest research collaboration with other researchers. Of all countries that published on hikikomori, Japan had the highest number of publications (K = 91). The keywords "United States" and "psychiatric diagnosis" received the most attention between 2013 and 2015, whereas "health" and "autism spectrum disorder" received the most attention in 2021 and 2022. Conclusions: Peer‐reviewed research publications on hikikomori are growing rapidly and the research trends in this field are also changing. [ABSTRACT FROM AUTHOR]