1,748 research outputs found
Flexibility in the Parts-of-Speech System of Classical Chinese/ Linlin Sun.
No full textIn English.Based on empirical data from five classical texts, this study investigates flexibility of parts of speech in Classical Chinese. The findings suggest that flexibility in a parts-of-speech system can only be fully understood by integrating a wide range of aspects. The components needed to account for it include constructions, semantics, metonymies, metaphors, pragmatic implicatures - and world knowledge as reflected within a given culture.Frontmatter -- Acknowledgements -- Contents -- List of figures -- List of tables -- List of abbreviations -- 1. Introduction -- 2. Background for studying flexibility in parts-of-speech systems -- 3. Syntactic observations on flexibility in Classical Chinese -- 4. Cognitive-semantic foundations of flexibility in Classical Chinese -- 5. Pragmatics of flexibility in Classical Chinese: The level of argument structure constructions -- 6. Conclusion -- References -- Appendix I -- Appendix II -- Index1 online resource (XVI, 283 p.)
Growth inhibition induced by transforming growth factor-beta1 in human oral squamous cell carcinoma
No full textXiumei Wang, Wenjing Sun, Jing Bai, Linlin Ma, Yang Yu, Jingshu Geng, Jiping Qi, Zhongcheng Shi and Songbin F
Fault detection and fault-tolerant control for nonlinear systems
No full textLinlin Li addresses the analysis and design issues of observer-based FD and FTC for nonlinear systems. The author analyses the existence conditions for the nonlinear observer-based FD systems to gain a deeper insight into the construction of FD systems. Aided by the T-S fuzzy technique, she recommends different design schemes, among them the L_inf/L_2 type of FD systems. The derived FD and FTC approaches are verified by two benchmark processes. Contents Overview of FD and FTC Technology Configuration of Nonlinear Observer-Based FD Systems Design of L2 nonlinear Observer-Based FD Systems Design of Weighted Fuzzy Observer-Based FD Systems FTC Configurations for Nonlinear Systems< Application to Benchmark Processes Target Groups Researchers and students in the field of engineering with a focus on fault diagnosis and fault-tolerant control fields The Author Dr. Linlin Li completed her dissertation under the supervision of Prof. Steven X. Ding at the Faculty of Engineering, University of Duisburg-Essen, Germany
Aggregate Productivity Growth in Indian Manufacturing : An Application of Domar Aggregation
No full textProductivity growth in Indian manufacturing is an important driver of overall growth, yet the issues related to its measurement have still not been resolved. The issue of how to compute an aggregate productivity measure holds significance for two reasons : one, the productivity of a firm should reflect the productivity of the lower levels, which comprise the aggregate; and two, aggregate productivity should also emphasize the importance of inter-industry transactions in an analysis of productivity growth. Contributions from Domar (1961), Hulten (1978) and Jorgenson et al. (1987) have addressed the issue of measuring aggregate productivity. We have made an attempt to compute the aggregate productivity growth using the Domar aggregation technique. Building up from the Total Factor Productivity Growth (TFPG) estimates for 3-digit industries, we have used Domar weights to computed total factor productivity (TFP) growth for selected 10, 2-digit industries for the period 1980-2000. Comparing the estimates based on the Domar aggregation technique with those based on the traditional aggregate value added approach, we observe that the preferred estimates are about half of that obtained by the traditional aggregate value added method. This holds immense significance for any underlying productivity numbers.Productivity growth, Domar aggregation, aggregate value added, Indian manufacturing
Supplemental Material - Development and Validation of Knowledge Assessment Scales for Dementia and Urinary Incontinence in Community Older People
No full textSupplemental Material for Development and Validation of Knowledge Assessment Scales for Dementia and Urinary Incontinence in Community Older People by Hui Sun, Wenqi Liu, Xuemei Sun, Yinyan Gao, Yancong Chen, Yali Lin, Jinlu Song, Zixuan Zhang, Betty H Wang, Lingqi Li, Hui Feng, Hongzhuan Tan, Qiong Chen, Linlin Peng, Wenjie Dai, and Irene XY Wu in Journal of Applied Gerontology</p
Litter quality modulates changes in bacterial and fungal communities during the gut transit of earthworm species of different ecological groups
No full textAbstract Earthworms are keystone animals stimulating litter decomposition and nutrient cycling. However, earthworms comprise diverse species which live in different soil layers and consume different types of food. Microorganisms in the gut of earthworms are likely to contribute significantly to their ability to digest organic matter, but this may vary among earthworm species. Here, we analyse the effect of food (litter) quality on gut microbiota and their changes during the gut passage (from foregut to hindgut) of earthworms of different ecological groups. The endogeic (soil living) species Aporrectodea caliginosa and the anecic (litter feeding) species Lumbricus terrestris were fed with high- (rape leaves) and low-quality litter (wheat straw) in a microcosm experiment for 18 weeks. Irrespective of earthworm species, alpha diversity of bacterial and fungal communities changed little during the gut passage, with the composition and diversity of microbial communities in the gut generally resembling those in soil more than in litter. In addition, the low-quality litter supported higher alpha diversity and more complex communities than high-quality litter. Further, gut microbial communities of the anecic L. terrestris changed less during gut passage than those of the endogeic A. caliginosa, especially when fed low-quality litter. Our findings indicate that earthworm gut microbial communities are predominantly shaped by the soil they ingest, but are modulated by the quality of litter they feed on and earthworm ecological group. Overall, the results suggest that earthworms primarily influence soil microbiota by mixing and spreading microorganisms from different microhabitats through bioturbation rather than by digesting microorganisms.Open-Access-Publikationsfonds 202
Development of a novel continuum damage mechanics-based machine learning approach for vibration fatigue assessment of fastener clip subjected to high-frequency vibration
No full textThis paper proposes a novel method based on continuum damage mechanics (CDM) and machine learning (ML) models to evaluate the vibration fatigue behavior of W1-type railway fastener clips subjected to high-frequency vibration. Firstly, static and fatigue tests are conducted on 60Si2Mn spring steel to acquire elastic modulus, tensile strength, and P-S-N curves. Subsequently, a CDM model is established, and numerical simulations are performed under various working conditions to obtain the fatigue characteristics of the clips. Finally, the ML model is trained using numerical simulation results, thereby establishing a mapping model between the working conditions and fatigue characteristics. The developed ML model demonstrates high accuracy in predicting the vibration fatigue life of the clips. Moreover, the Shapley Additive Explanations (SHAP) algorithm is employed to elucidate the ML model, revealing that the vibration frequency has a greater impact on the fatigue life of the clips compared to the vibration displacement.The authors sincerely acknowledge the support from the National Natural Science Foundation of China (No. 12002011). Linlin Sun is supported by the scientific research project of China Academy of Railway Sciences Co., Ltd. (2021YJ069)
Using in situ and Satellite Hyperspectral Data to Estimate the Surface Suspended Sediments Concentrations in the Pearl River Estuary.pdf
No full textThe objectives of this study were to examine the effect of direct inoculation of seeds with the rhizobacteria Pseudomonas sp. SB on the growth of tall fescue and phytodegradation efficiency in an oily-sludge-contaminated soil. SB isolated from rhizosphere soil of tall fescue was evaluated for their plant-growth-promoting characters and ability to produce biosurfactant. A pot experiment was conducted to study the effect of inoculation of SB on phytoremediation. SB reduced the surface tension of culture media and produced indole acetic acid, siderophores, and 1-aminocyclopropane-1-carboxylate deaminase. Inoculation of SB increased shoot and root dry weights of tall fescue in oily-sludge-contaminated soil by 28 % and 19 %, respectively. Over 120 days, the content of total petroleum hydrocarbon in soil decreased by 33.9 %, 68.0 %, and 84.5 %, and of polycyclic aromatic hydrocarbons (PAHs) by 32.9 %, 40.9 %, and 46.2 %, respectively, in the no-plant control, tall fescue, and tall fescue + SB treatments. Inoculation of SB also increased the activity and biodiversity of soil microbial communities in the planted treatments. SB could produce biosurfactant and exhibited a number of characters of plant-growth-promoting rhizobacteria. Inoculation of SB to tall fescue led to more effective remediation of oily-sludge-contaminated soils.The objectives of this study were to examine the effect of direct inoculation of seeds with the rhizobacteria Pseudomonas sp. SB on the growth of tall fescue and phytodegradation efficiency in an oily-sludge-contaminated soil
Bagdadia khaoensis Park & Ponomarenko 1999, comb. nov.
No full textBagdadia khaoensis (Park & Ponomarenko, 1999) comb. nov. Capidentalia khaoensis Park & Ponomarenko, 1999: 334, figs. 9, 22, 22 a–c, 23. TL: Thailand (Khao Soi Dao, Chantha-Buri Prov.). Material examined. CHINA, Hainan Province: 2 ♂, 2 ♀, Mt. Jianfeng, 940 m, 4.vi. 2007, leg. Zhiwei Zhang and Weichun Li; 1 ♂, Nancha River, Mt. Bawang, 600 m, 10.vi. 2007, leg. Zhiwei Zhang and Weichun Li; 1 ♂, Mt. Jianfeng, 900 m, 5.xii. 2009, leg. Zhaohui Du and Linlin Yang; 1 ♂, Mt. Yingge, 620 m, 9.xii. 2009, leg. Zhaohui Du and Linlin Yang; 1 ♂, 1 ♀, Mt. Yingge, 620 m, 23.v. 2010, leg. Bingbing Hu and Jing Zhang; 2 ♀, Tianchi, Mt. Jianfeng, 12.vi. 2010, leg. Bingbing Hu and Jing Zhang; 1 ♀, Tianchi, Mt. Jianfeng, Ledong, 1050 m, 30.iv. 2013, leg. Yinghui Sun, Wei Guan and Tengteng Liu; 1 ♀, Qicha Town, Changjiang County, 125 m, 6.v. 2013, leg. Yinghui Sun, Wei Guan and Tengteng Liu; 1 ♀, Yajia, Mt. Bawang, Changjiang County, 245 m, 7.v. 2013, leg. Yinghui Sun, Wei Guan and Tengteng Liu; 1 ♂, Yajia, Mt. Bawang, Changjiang County, 245 m, 8.v. 2013, leg. Yinghui Sun, Wei Guan and Tengteng Liu; 1 ♂, 2 ♀, Mt. Bawang, Changjiang County, 161 m, 21.vii. 2014, leg. Peixin Cong, Linjie Liu and Sha Hu. Host plant. Sapindaceae: Dimocarpus longan Lour. (Park & Ponomarenko, 1999). Distribution. China (Hainan), Thailand. Remarks. This species is reported for the first time from China.Published as part of Yang, Meiqing & Li, Houhun, 2015, A taxonomic study of the genus Bagdadia Amsel, 1949 from Hainan Island of China (Lepidoptera: Gelechiidae), pp. 589-594 in Zootaxa 3972 (4) on page 591, DOI: 10.11646/zootaxa.3972.4.10, http://zenodo.org/record/23525
A novel hybrid technique for short-term electricity price forecasting in deregulated electricity markets
No full textThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Short-term electricity price forecasting is now crucial practice in deregulated electricity markets, as it forms the basis for maximizing the profits of the market participants. In this thesis, short-term electricity prices are forecast using three different predictor schemes, Artificial Neural Networks (ANNs), Support Vector Machine (SVM) and a hybrid scheme, respectively.
ANNs are the very popular and successful tools for practical forecasting. In this thesis, a hidden-layered feed-forward neural network with back-propagation has been adopted for detailed comparison with other forecasting models. SVM is a newly developed technique that has many attractive features and good performance in terms of prediction. In order to overcome the limitations of individual forecasting models, a hybrid technique that combines Fuzzy-C-Means (FCM) clustering and SVM regression algorithms is proposed to forecast the half-hour electricity prices in the UK electricity markets. According to the value of their power prices, thousands of the training data are classified by the unsupervised learning method of FCM clustering. SVM regression model is then applied to each cluster by taking advantage of the aggregated data information, which reduces the noise for each training program.
In order to demonstrate the predictive capability of the proposed model, ANNs and SVM models are presented and compared with the hybrid technique based on the same training and testing data sets in the case studies by using real electricity market data. The data was obtained upon request from APX Power UK for the year 2007.
Mean Absolute Percentage Error (MAPE) is used to analyze the forecasting errors of
different models and the results presented clearly show that the proposed hybrid
technique considerably improves the electricity price forecasting
- …
