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In the field of photocatalytic degradation, the separation and recycle technology of powdery g-C3N4 after usage has not been mature, which causes secondary pollution problems for large-scale industrial applications. In this paper, carbon-fiber/g-C3N4 nanosheet arrays were fabricated by chemical vapor deposition(CVD) under argon protection, and the optical, electrochemical and photocatalytic performance of carbon-fiber/g-C3N4 nanosheet arrays were studied. The results indicated that carbon-fiber/g-C3N4 nanosheet arrays generated photon-excited electrons and holes under visible light irradiation during photocatalytic process. The excellent electrical conductivity of carbon fiber could trap photon-excited electrons in conduction band of g-C3N4 nanosheet and creat holes in valence band of g-C3N4 nanosheet. 20.7%, 33.5% and 99.5% of 2, 4-dinitrophenol were degraded by photocatalysis, electrocatalysis and photoelectrocatalysis of carbon-fiber/g-C3N4 nanosheet arrays within 240 min. The external voltage further enhanced the separation of photo-generated electrons and holes, which made the photoelectrocatalysis of carbon-fiber/g-C3N4 nanosheet arrays exerted unexpected performance through synergistic interactions of photocatalysis and electrocatalysis. The assembly of powdery photocatalysts and carbon fibers textile might provide a general methodology in the design of separable and recyclable photocatalysts with broad applications in environment-related fields. The assembly strategy developed herein significantly reduced the separable and recyclable cost of powdery photocatalysts and offered valuables references for industrial application of photocatalysis and photoelectrocatalysis.

With the implementation of China’s innovation-driven development strategy, the competition among sci-tech talents has become increasingly fierce. Stimulating the innovative vigor of sci-tech talents has become a hot topic in theoretical research and policy practice. Based on the data from 246 questionnaires collected from sci-tech talents in Hebei province, this study explored the influence mechanism of an inclusive organizational climate on innovation input from technological talents and verified the mediating effects of innovation self-efficacy and intrinsic motivation. The results indicate that an inclusive organizational climate has a significant positive impact on innovation input, innovation self-efficacy, and intrinsic motivation of sci-tech talents. Both innovation self-efficacy and intrinsic motivation play a partial mediating role between an inclusive climate and innovation input. This study verified the important role of an inclusive climate in an organization’s human resource management practices and encouraged managers to emphasize enhancing the innovation self-efficacy and intrinsic motivation of sci-tech talents, thereby continuously improving the level of innovation.

Rule-based learning is an important aspect of language acquisition. Yang (2005,2016) proposed the Tolerance Principle (TP) to predict when a rule will be formed by the language learner. We present the derivation of the TP as originally proposed and test it on both hypothetical data and corpus data from 8 children. Results for the hypothetical data contradict the TP’s predictions, as do the data from 7 of the 8 children. We conclude that the original form of the TP does not explain rule-learning.

Do childrens early utterances reflect abstract syntactic knowledge or slot-filler formulae developed through word imita-tion? This study compares development of part-of-speech (POS) sequences with word sequences using language models(LMs) trained on mothers utterances (N=1,272,139) from CHILDES English corpora, in which POS tags are automaticallyassigned by MOR and POST programs (MacWhinney, 2000). Word-based and POS-based LM probabilities for childrensmulti-word utterances in the Providence corpus (Brschinger et al., 2013, 15-36 months, Nchildren=6, Nutterances=50,717)were calculated as a function of age. Word-based LM probability of childrens multi-word utterances first increases withage and then levels off after 23 months. By contrast, POS-based probability remains high and stable across all ages. Thissuggests children have adult-like syntactic knowledge even at a very early age when their word sequences are still notadult-like. The pattern of results supports the abstract syntax view. Additional studies will use more accurate POS-taggersand larger datasets.

Objective To evaluate the diagnostic value of Aβ protein PET brain imaging model in distinguishing patients with Alzheimer's disease （AD） from mild cognitive impairment （MCI）. Methods Thirty-two subjects with cognitive impairment were enrolled in this study. All participants were diagnosed with AD or MCI by clinical examination and underwent 18F-AV-45 （2.96~4.44 MBq/kg）PET/CT scan（heart and head）. The fitting curves of specific activity of left ventricle and region of interest （ROI） at different time points were delineated, and then the metabolic rate K was calculated by Logan model. The difference in metabolic rate K value was compared between AD and MCI groups by using Mann-Whitney U test. The diagnostic efficiency of Logan model was evaluated by the receiver operator characteristic （ROC） curve. Results The degree of Aβ protein deposition in the cerebral cortex of AD and MCI patients was different. AD and MCI patients could be distinguished with the K value of Logan model. The K value in the AD group was 3.96（2.66, 4.26）, significantly higher than 2.62（1.41, 2.96） in the MCI group （P < 0.05）. According to ROC curve analysis, the optimal diagnostic threshold of K value was 3.23, the diagnostic sensitivity was 100%, the specificity was 58.33%, and the area under ROC curve （AUC） was 0.781 （Z = -2.350, P < 0.05）, respectively. Conclusion Aβ protein PET imaging with Logan model has high diagnostic efficacy in distinguishing AD from MCI.

Background: Complete reporting of seroepidemiologic studies is critical to their utility in evidence synthesis and public health decision making. The Reporting of Seroepidemiologic studies—SARS‐CoV‐2 (ROSES‐S) guideline is a checklist that aims to improve reporting in SARS‐CoV‐2 seroepidemiologic studies. Adherence to the ROSES‐S guideline has not yet been evaluated. Objectives: This study aims to evaluate the completeness of SARS‐CoV‐2 seroepidemiologic study reporting by the ROSES‐S guideline during the COVID‐19 pandemic, determine whether guideline publication was associated with reporting completeness, and identify study characteristics associated with reporting completeness. Methods: A random sample from the SeroTracker living systematic review database was evaluated. For each reporting item in the guideline, the percentage of studies that were adherent was calculated, as well as median and interquartile range (IQR) adherence across all items and by item domain. Beta regression analyses were used to evaluate predictors of adherence to ROSES‐S. Results: One hundred and ninety‐nine studies were analyzed. Median adherence was 48.1% (IQR 40.0%–55.2%) per study, with overall adherence ranging from 8.8% to 72.7%. The laboratory methods domain had the lowest median adherence (33.3% [IQR 25.0%–41.7%]). The discussion domain had the highest median adherence (75.0% [IQR 50.0%–100.0%]). Reporting adherence to ROSES‐S before and after guideline publication did not significantly change. Publication source (p < 0.001), study risk of bias (p = 0.001), and sampling method (p = 0.004) were significantly associated with adherence. Conclusions: Completeness of reporting in SARS‐CoV‐2 seroepidemiologic studies was suboptimal. Publication of the ROSES‐S guideline was not associated with changes in reporting practices. Authors should improve adherence to the ROSES‐S guideline with support from stakeholders. [ABSTRACT FROM AUTHOR]