603 research outputs found

    Nandao-Questions as a Special Kind of Rhetorical Questions

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    This paper addresses the syntax and semantics of a special kind of Rhetorical Questions (RQs) in Mandarin, i.e. questions with nandao (nandao-Q). Nandao-Qs necessarily have rhetorical question readings. To derive this, I propose that nandao is a WH-word which takes a question denoting a single proposition and turns it into a set with the complement proposition. This analysis differs significantly from earlier proposals for deriving RQ meanings as asserting the negation of the proposition denoted by its IP (cf. Sadock 1979, Han 2002, a.o.). The degenerate question nature of nandao-Q can explain why nandao-Q unlike Ordinary Questions (OQs) cannot be embedded under [+wh] selecting words like wen and zhidao

    The Relationship between Serum Osteocalcin Concentration and Glucose Metabolism in Patients with Type 2 Diabetes Mellitus

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    To study the correlations between serum osteocalcin and glucose metabolism in patients with type 2 diabetes, 66 cases were collected to determine total osteocalcin, undercarboxylated osteocalcin, fasting blood glucose, fasting insulin, and HbA1c. Osteocalcin concentrations were compared between groups of different levels of HbA1c, and parameters of glucose metabolism were compared between groups of different levels of total osteocalcin and undercarboxylated osteocalcin. The relationship between osteocalcin and parameters of glucose metabolism was also analyzed. We found that the total osteocalcin concentration of high-HbA1c group was significantly lower than that of low-HbA1c group. The fasting blood glucose of low-total-osteocalcin group was significantly higher than that of high-total-osteocalcin group in male participants, while the fasting blood glucose of low-undercarboxylated-osteocalcin group was significantly higher than that of high-undercarboxylated-osteocalcin group in all participants and in male participants. Total osteocalcin was inversely correlated with HbA1c, and undercarboxylated osteocalcin was inversely correlated with fasting blood glucose. However, no significant correlation was found between osteocalcin and HOMA-IR. Total osteocalcin was an independent related factor of HbA1c level. In summary, decreased serum total osteocalcin and undercarboxylated osteocalcin are closely related to the exacerbation of glucose metabolism disorder but have no relations with insulin resistance

    Dynamic evolution of a hydraulic-mechanical-electric system with randomly fluctuating speed based on Chebyshev polynomial approximation method

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    The research proposed in this paper focuses on the dynamic evolution of a hydraulic-mechanical-electric system under the effect of randomly fluctuating speed. The rapid growth of installed wind power capacity may potentially affect the stability of power grids, causing larger fluctuations of the generator speed to hydropower stations. In this work, a probabilistic component is associated to the generator speed of a deterministic hydraulic-mechanical-electric system providing a novel random model. This latter is analyzed to investigate the dynamic evolution of the system adopting the Chebyshev polynomial approximation method. A careful comparison of the numerical application results obtained by the deterministic and the probabilistic approaches is carried out. In addition, the influence of the fluctuation intensity (D) on the differential gain (kd) of the PID is investigated, proposing a law for kd as function of D. Finally, the operating ranges of the grid water hammer and of the elastic water hammer models are compared in order to validate the consistence of the law. The results of the study provide robust bases for the stable and safe operation of hydropower stations.National Natural Science Foundation of ChinaFundamental Research Funds for the Central UniversitiesNorthwest A&F Universit

    Real-Time Purchase Prediction Using Retail Video Analytics

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    The proliferation of video data in retail marketing brings opportunities for researchers to study customer behavior using rich video information. Our study demonstrates how to understand customer behavior of multiple dimensions using video analytics on a scalable basis. We obtained a unique video footage data collected from in-store cameras, resulting in approximately 20,000 customers involved and over 6,000 payments recorded. We extracted features on the demographics, appearance, emotion, and contextual dimensions of customer behavior from the video with state-of-the-art computer vision techniques and proposed a novel framework using machine learning and deep learning models to predict consumer purchase decision. Results showed that our framework makes accurate predictions which indicate the importance of incorporating emotional response into prediction. Our findings reveal multi-dimensional drivers of purchase decision and provide an implementable video analytics tool for marketers. It shows possibility of involving personalized recommendations that would potentially integrate our framework into omnichannel landscape

    Dynamic safety assessment of a nonlinear pumped-storage generating system in a transient process

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    This paper focuses on a pumped-storage generating system with a reversible Francis turbine and presents an innovative framework for safety assessment in an attempt to overcome their limitations. Thus the aim is to analyze the dynamic safety process and risk probability of the above nonlinear generating system. This study is carried out based on an existing pumped-storage power station. In this paper we show the dynamic safety evaluation process and risk probability of the nonlinear generating system using Fisher discriminant method. A comparison analysis for the safety assessment is performed between two different closing laws, namely the separate mode only to include a guide vane and the linkage mode that includes a guide vane and a ball valve. We find that the most unfavorable condition of the generating system occurs in the final stage of the load rejection transient process. It is also demonstrated that there is no risk to the generating system with the linkage mode but the risk probability of the separate mode is 6 percent. The results obtained are in good agreement with the actual operation of hydropower stations. The developed framework may not only be adopted for the applications of the pumped-storage generating system with a reversible Francis turbine but serves as the basis for the safety assessment of various engineering applications.National Natural Science Foundation of ChinaFundamental Research Funds for the Central UniversitiesScientific research funds of Northwest A&F UniversityScience Fund for Excellent Young Scholars from Northwest A&F University and Shaanxi Nova progra

    Enhancing clustering blog documents by utilizing author/reader comments

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    Blogs are a new form of internet phenomenon and a vast ever-increasing information resource. Mining blog files for information is a very new research direction in data mining. Blog files are different from standard web files and may need specialized mining strategies. We propose to include the title, body, and comments of the blog pages in clustering datasets from blog documents. In particular, we argue that the author/reader comments of the blog pages may have more discriminating effect in clustering blog documents. We constructed a word-page matrix by downloading blog pages from a well-known website and experimented a k-means clustering algorithm with different weights assigned to the title, body, and comment parts. Our experimental results show that assigning a larger weight value to the blog comments helps the k-means algorithm produce better clustering solutions. The experimental results confirm our hypothesis that the author/reader comments of the blog files are very useful in discriminating blog files

    Effect of temperature on microorganisms and nitrogen removal in a multi-stage surface flow constructed wetland

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    The effect of low temperature on microbial nitrogen metabolism in constructed wetlands has yet to be extensively investigated. In this study, we analyzed the effects of temperature changes on nitrogen-associated microorganisms and nitrogen metabolism functional genes in a multi-stage surface flow constructed wetland (MSSFCW) using metagenomic sequencing. The treatment of polluted river water in the MSSFCW, which had a mean water temperature (MWT) of ≤17 °C, resulted in a low removal efficiency (RE) for total nitrogen (TN; average RE: 23.05% at 1–17 °C) and nitrate nitrogen (NO3−-N; average RE: −2.41% at 1–17 °C). Furthermore, at a MWT of ≤11 °C, the REs were low for ammonium nitrogen (NH4+-N; average RE: 67.92% at 1–11 °C) and for chemical oxygen demand (COD; average RE: 27.45% at 1–11 °C). At 0.24 m3 m−2 d−1 influent load, the highest REs for TN (66.84%), NO3−-N (74.90%), NH4+-N (83.93%), and COD (52.97%) occurred in July and August, when water temperatures were between 26 and 28 °C

    Efficient Point based Global Illumination on Intel MIC Architecture

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    International audiencePoint-Based Global Illumination (PBGI) is a popular rendering method in special effects and motion picture productions. The tree-cut computation is in general the most time consuming part of this algorithm, but it can be formulated for efficient parallel execution, in particular regarding wide-SIMD hardware. In this context, we propose several vectorization schemes, namely single, packet and hybrid, to maximize the utilization of modern CPU architectures. While for the single scheme, 16 nodes from the hierarchy are processed for a single receiver in parallel, the packet scheme handles one node for 16 receivers. These two schemes work well for scenes having smooth geometry and diffuse material. When the scene contains high frequency bumps maps and glossy reflections, we use a hybrid vectorization method. We conduct experiments on an Intel Many Integrated Corearchitecture and report preliminary results on several scenes, showing that up to a 3x speedup can be achieved when compared with non-vectorized execution

    3D radiomics predicts EGFR mutation, exon-19 deletion and exon-21 L858R mutation in lung adenocarcinoma

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    Background: To establish a radiomic approach to identify epidermal growth factor receptor (EGFR) mutation status in lung adenocarcinoma patients based on CT images, and to distinguish exon-19 deletion and exon-21 L858R mutation. Methods: Two hundred sixty-three patients who underwent pre-surgical contrast-enhanced CT and molecular testing were included, and randomly divided into the training (80%) and test (20%) cohort. Tumor images were three-dimensionally segmented to extract 1,672 radiomic features. Clinical features (age, gender, and smoking history) were added to build classification models together with radiomic features. Subsequently, the top-10 most relevant features were used to establish classifiers. For the classifying tasks including EGFR mutation, exon-19 deletion, and exon-21 L858R mutation, four logistic regression models were established for each task. Results: The training and test cohort consisted of 210 and 53 patients, respectively. Among the established models, the highest accuracy and sensitivity among the four models were 75.5% (61.7-86.2%) and 92.9% (76.5-99.1%) to classify EGFR mutation, respectively. The highest specificity values were 86.7% (69.3-96.2%) and 70.4% (49.8-86.3%) to classify exon-19 deletion and exon-21 L858R mutation, respectively. Conclusions: CT radiomics can sensitively identify the presence of EGFR mutation, and increase the certainty of distinguishing exon-19 deletion and exon-21 L858R mutation in lung adenocarcinoma patients. CT radiomics may become a helpful non-invasive biomarker to select EGFR mutation patients for invasive sampling

    Exploring the Regulation Reliability of a Pumped Storage Power Plant in a Wind–Solar Hybrid Power Generation System

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    In the coming decades, the proportion of wind–solar energy in power system significantly increases, resulting to uncertainties of power fluctuation in abundant wind–solar energy regions. The flexibility operation of Pumped Storage Power Plants (PSPPs) has already been widely recognized to regulate wind–solar power fluctuations; however, less is known about the regulation reliability of the PSPP affected by them. It is a challenge, since various uncertainties exist during this regulation process. Here, a mathematical model with a solar–wind–hydro hybrid power generation system is adopted to investigate the regulation reliability of PSPP. The uncertainties and limitations of model parameters are considered during this process. Five regulation indexes, i.e., rise time, settling time, peak value, peak time and overshoot of the reactive power generator terminal voltage, guide vane opening and angular velocity, are extracted to evaluate the PSSP’s regulation quality. Finally, the PSPP reliability probability affected by parametric uncertainties is presented. The obtained results show that the inertia coefficient is the most sensitivity parameters for the settling time, peak value and peak time with sensitivity index 33.7%, 72.55% and 71.59%, respectively. The corresponding total contribution rate of the top 10 sensitive parameters are 74.45%, 93.45% and 87.15%, respectively. Despite some types of uncertainties not being considered, the results of this research are important for the regulation reliability evaluation of PSPPs in suppressing power fluctuations of wind and solar generation.Peer ReviewedPostprint (published version
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