48 research outputs found

    Needle ÎŽ13C and mobile carbohydrates in Pinus koraiensis in relation to decreased temperature and increased moisture along an elevational gradient in NE China

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    A tree's crown interacts with atmospheric variables such as CO2, temperature, and humidity. Physioecology of leaves/needles (e.g. ÎŽ13C, mobile carbohydrates, and nitrogen) is, therefore, strongly affected by microclimate in and surrounding a tree crown. To understand the physiological responses of leaves to changes in air temperature and moisture, we measured ÎŽ13C, soluble sugars, starch, and total nitrogen (N) concentrations in current year and 1-yr-old needles of Pinus koraiensis trees, and compared the growing season air temperature and relative humidity within and outside P. koraiensis crowns along an elevational gradient from 760 to 1,420ma.s.l. on Changbai Mountain, NE China. Our results indicated that needle N and mobile carbohydrates concentrations, as well as needle ÎŽ13C values changed continuously with increasing elevation, corresponding to a continuous decrease in air temperature and an increase in relative humidity. Needle carbon and nitrogen status is highly significantly negatively correlated with temperature, but positively correlated with relative humidity. These results indicate that increases in air temperature in combination with decreases in relative humidity may result in lower levels of N and mobile carbohydrates in P. koraiensis trees, suggesting that future climate changes such as global warming and changes in precipitation patterns will directly influence the N and carbon physiology at P. koraiensis individual level, and indirectly affect the competitive ability, species composition, productivity and functioning at the stand and ecosystem level in NE China. Due to the relatively limited range of the transect (760-1,420m) studied, further research is needed to explain whether the present results are applicable to scales across large elevational gradient

    Maternal face processing in Mosuo preschool children

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    Instinctively responding to maternal face is an evolutionary function of enhancing survival and development. However, because of the confounding nature of familiarity, little is known concerning the neural mechanism involved in maternal face recognition. We had a rare opportunity to examine Mosuo preschool children who were raised in a matrilineal society in which mothers and aunts represent equally familiar faces to the children. The participants were exposed to photographs of their mother's face, aunt's face, and an unfamiliar female's faces during electroencephalography (EEG) recording. The EEG results showed that the mother's face elicited a more negative N1 component, a larger left N170 component, and a larger P300 component; both the mother's and aunt's faces elicited a larger right N170 component. These results suggest that the emotional attachment between mother and child has neural ramifications across three successive face processing stages that are distinguished from the neural effects of facial familiarity. (C) 2014 Elsevier B.V. All rights reserved

    Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

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    Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

    The 16th Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

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    This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17)

    The 16th Data Release of the Sloan Digital Sky Surveys : First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

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    This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17).Peer reviewe

    The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data

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    This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys

    Design and analysis of 12 MW offshore wind turbine

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    Permanent magnet synchronous motors are widely used in various fields for the advantages of high power density, high efficiency and high reliability. This paper analyzes the cogging torque of generators with different slot and pole coordination, and selects the optimal pole–slot ratio. Then, this paper analyzes the structural differences between the outer rotor and the inner rotor of permanent magnet synchronous motor, and selects the structural form of the outer rotor for analysis. Based on the electromagnetic design parameters of the motor, a two-dimensional finite element model is established in Maxwell to simulate and analyze the performance at no-load, rated load and short-circuit. The internal magnetic field, the distortion rate of voltage waveform, torque and short circuit current of the motor are studied, and the demagnetization of the permanent magnet under the worst operating condition is investigated. The simulation results show that the design scheme meets the design objectives
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