The phraseology of phrasal verbs in English: a corpus study of the language of Chinese learners and native English writers

The aim of this study is to supplement existing research on phraseology in learner language by exploring the behaviours of phrasal verbs, a notorious hurdle for learners of English. This thesis compares a Chinese learner corpus (CLEC) with an English native speakers’ corpus (LOCNESS), with a reference corpus, the Bank of English (BoE), being consulted where necessary. A series of quantitative and qualitative investigations are conducted on phrasal verbs: calculation of frequency distribution and type-token ratios; identification of phraseological information, including collocation, semantic preference, semantic sequence and prosody. The results are discussed in full. Additionally, a framework utilising degrees of idiomaticity and restriction strength to group phrasal verbs is proposed and the issue of distinguishing synonymous counterparts is tackled as well. The results generally indicate that Chinese learner language tends to have more phrasal verb tokens but fewer types than written native speaker English does. Detailed case studies of phrasal verbs show, however, that the phraseological behaviours of phrasal verbs as used by learners are so individualised that the findings are mixed. Learner uses are characterised by idiosyncrasies of different phraseological units, suggesting that the links (between lexis and lexis, or lexis and concepts) in the lexicon of L2 are different from those in L1

Optimal Material Search for Infrared Markers under Non-Heating and Heating Conditions

Research on optimal markers for infrared imaging and differences in their characteristics in the presence of heat sources has not yet been performed. This study investigates optimal material combinations for developing an accurate and detachable infrared marker for multiple conditions in the medium wave infrared (MWIR) region. Based on four requirements, 11 material combinations are systematically evaluated. Consequently, the optimal marker differs in relation to the presence of specular reflection components. Metal–insulator markers are suitable under non-heating and hot-air heating conditions without reflection components, although a printed marker made of copier paper is captured more clearly than metal–insulator markers during heating, using an optical radiation heating source with reflection components. Our findings can be applied in structural health monitoring and multi-modal projection involving heat sources

Iodine Redox-Mediated Electrolysis for Energy-Efficient Chlorine Regeneration from Gaseous HCl

This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives 4.0 License (CC BY-NC-ND, http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is not changed in any way and is properly cited. For permission for commercial reuse, please email: [email protected] chloride (HCl) by-product is often produced from chlorine-consuming processes. Traditional electrochemical processes for converting HCl to chlorine (Cl-2) are completed by anodic oxidation reaction coupled with cathodic reduction reactions (two major types: hydrogen evolution reaction and oxygen reduction reaction). Herein, a triiodide (I-3(-))/ iodide (I-) redox-mediated cathode is implemented for the first time for converting HCl to Cl-2. The iodide (I-) can be converted back to triiodide (I-3(-)) by air in a reactor external to the eletrolyzer. The desirable redox potential and facile kinetics of I-3(-)/I- offer a substantially lower operational cell voltage, reducing energy consumption by 20%-25% at a typical current density of 4 kA m(-2) and improving the efficiency of Cl-2 recovery.DEGi Chlorine

PRSOT: Precipitation Retrieval from Satellite Observations Based on Transformer

Precipitation with high spatial and temporal resolution can improve the defense capability of meteorological disasters and provide indispensable instruction and early warning for social public services, such as agriculture, forestry, and transportation. Therefore, a deep learning-based algorithm entitled precipitation retrieval from satellite observations based on Transformer (PRSOT) is proposed to fill the observation gap of ground rain gauges and weather radars in deserts, oceans, and other regions. In this algorithm, the multispectral infrared brightness temperatures from Himawari-8, the new-generation geostationary satellite, have been used as predictor variables and the Global Precipitation Measurement (GPM) precipitation product has been employed to train the retrieval model. We utilized two data normalization schemes, area-based and pixel-based normalization, and conducted comparative experiments. Comparing the estimated results with the GPM product on the test set, PRSOT_Pixel_based model achieved a Probability Of Detection (POD) of 0.74, a False Alarm Ratio (FAR) of 0.44 and a Critical Success Index (CSI) of 0.47 for two-class metrics, and an Accuracy (ACC) of 0.75 for multi-class metrics. Pixel-based normalization is more suitable for meteorological data, highlighting the precipitation characteristics and obtaining better comprehensive retrieval performance in visualization and evaluation metrics. In conclusion, the proposed PRSOT model has made a remarkable and essential contribution to precipitation retrieval and outperforms the benchmark machine learning model Random Forests

PRSOT: Precipitation Retrieval from Satellite Observations Based on Transformer

Precipitation with high spatial and temporal resolution can improve the defense capability of meteorological disasters and provide indispensable instruction and early warning for social public services, such as agriculture, forestry, and transportation. Therefore, a deep learning-based algorithm entitled precipitation retrieval from satellite observations based on Transformer (PRSOT) is proposed to fill the observation gap of ground rain gauges and weather radars in deserts, oceans, and other regions. In this algorithm, the multispectral infrared brightness temperatures from Himawari-8, the new-generation geostationary satellite, have been used as predictor variables and the Global Precipitation Measurement (GPM) precipitation product has been employed to train the retrieval model. We utilized two data normalization schemes, area-based and pixel-based normalization, and conducted comparative experiments. Comparing the estimated results with the GPM product on the test set, PRSOT_Pixel_based model achieved a Probability Of Detection (POD) of 0.74, a False Alarm Ratio (FAR) of 0.44 and a Critical Success Index (CSI) of 0.47 for two-class metrics, and an Accuracy (ACC) of 0.75 for multi-class metrics. Pixel-based normalization is more suitable for meteorological data, highlighting the precipitation characteristics and obtaining better comprehensive retrieval performance in visualization and evaluation metrics. In conclusion, the proposed PRSOT model has made a remarkable and essential contribution to precipitation retrieval and outperforms the benchmark machine learning model Random Forests

Glutathione S-transferase activity facilitates rice tolerance to the barnyard grass root exudate DIMBOA

Abstract Background In paddy fields, the noxious weed barnyard grass secretes 2,4-dihydroxy-7-methoxy-2H-1,4-benzoxazin-3(4H)-one (DIMBOA) to interfere with rice growth. Rice is unable to synthesize DIMBOA. Rice cultivars with high or low levels of allelopathy may respond differently to DIMBOA. Results In this study, we found that low concentrations of DIMBOA (≤ 0.06 mM) promoted seedling growth in allelopathic rice PI312777, while DIMBOA (≤ 0.08 mM) had no significant influence on the nonallelopathic rice Lemont. DIMBOA treatment caused changes in the expression of a large number of glutathione S-transferase (GST) proteins, which resulting in enrichment of the glutathione metabolic pathway. This pathway facilitates plant detoxification of heterologous substances. The basal levels of GST activity in Lemont were significantly higher than those in PI312777, while GST activity in PI312777 was slightly induced by increasing DIMBOA concentrations. Overexpression of GST genes (Os09g0367700 and Os01g0949800) in these two cultivars enhanced rice resistance to DIMBOA. Conclusions Taken together, our results indicated that different rice accessions with different levels of allelopathy have variable tolerance to DIMBOA. Lemont had higher GST activity, which helped it tolerate DIMBOA, while PI312777 had lower GST activity that was more inducible. The enhancement of GST expression facilitates rice tolerance to DIMBOA toxins from barnyard grass root exudates

A zinc–iron redox-flow battery under $100 per kW h of system capital cost

Redox flow batteries (RFBs) are one of the most promising scalable electricity-storage systems to address the intermittency issues of renewable energy sources such as wind and solar. The prerequisite for RFBs to be economically viable and widely employed is their low cost. Here we present a new zinc–iron (Zn–Fe) RFB based on double-membrane triple-electrolyte design that is estimated to have under $100 per kW h system capital cost. Such a low cost is achieved by a combination of inexpensive redox materials (i.e., zinc and iron) and high cell performance (e.g., 676 mW cm[superscript −2] power density). Engineering of the cell structure is found to be critical to enable the high power density. Our cost model shows that a Zn–Fe RFB demonstrates the lowest cost among some notable RFBs and could reach the 2023 cost target set by the U.S. Department of Energy ($150 per kW h).United States. Dept. of Energy (ARPA-E Award DE-AR0000346

The complete chloroplast genome sequence of Bambusa albolineata (bambusodae)

Bambusa albolineata (local name: Hua Zhu) is found in Zhejiang, Jiangxi, Fujian, Taiwan, and Guangdong provinces of China, and is often cultivated on low hills, flatlands, and along streams and rivers. Due to its long internodes and flexible material, it is used as timber wood in China. In the current research, the complete chloroplast (CP) genome of B. albolineata was sequenced and reported for the first time. The complete CP genome sequence was 139,326 bp, including a large single-copy (LSC) region of 82,862 bp, a small single-copy (SSC) region of 12,870 bp, and a pair of invert repeats (IR) regions of 21,798 bp. Besides, the plastid genome consisted of 129 genes; having 82 protein-coding genes, 39 tRNA genes, and eight rRNA genes. The overall GC content of the genome was 44.2%. The phylogenetic analysis based on the complete chloroplast genome indicates that B. albolineata is strongly related to B. flexuosa and B. boniopsis