PLS （Partial Least Squares regression） is introduced into an automatic estimation of fundamental stellar spectral parameters. It extracts the most correlative spectral component to the parameters （Teff, log g and [...PLS （Partial Least Squares regression） is introduced into an automatic estimation of fundamental stellar spectral parameters. It extracts the most correlative spectral component to the parameters （Teff, log g and [Fe/H]）, and sets up a linear regression function from spectra to the corresponding parameters. Considering the properties of stellar spectra and the PLS algorithm, we present a piecewise PLS regression method for estimation of stellar parameters, which is composed of one PLS model for Teff, and seven PLS models for log g and [Fe/H] estimation. Its performance is investigated by large experiments on flux calibrated spectra and continuum normalized spectra at different signal-to-noise ratios （SNRs） and resolutions. The results show that the piecewise PLS method is robust for spectra at the medium resolution of 0.23 nm. For low resolution 0.5 nm and 1 nm spectra, it achieves competitive results at higher SNR. Experiments using ELODIE spectra of 0.23 nm resolution illustrate that our piecewise PLS models trained with MILES spectra are efficient for O ～ G stars： for flux calibrated spectra, the systematic offsets are 3.8%, 0.14 dex, and -0.09 dex for Teff, log g and [Fe/H], with error scatters of 5.2%, 0.44 dex and 0.38 dex, respectively; for continuum normalized spectra, the systematic offsets are 3.8%, 0.12dex, and -0.13 dex for Teff, log g and [Fe/H], with error scatters of 5.2%, 0.49 dex and 0.41 dex, respectively. The PLS method is rapid, easy to use and does not rely as strongly on the tightness of a parameter grid of templates to reach high precision as Artificial Neural Networks or minimum distance methods do.展开更多
The aim of this study was to highlight the effect of tide on the variation of the physicochemical parameter in the Kienké estuary. Six (06) environmental variables were monitored at nine (09) stations with the ti...The aim of this study was to highlight the effect of tide on the variation of the physicochemical parameter in the Kienké estuary. Six (06) environmental variables were monitored at nine (09) stations with the time step of one hour from 7 am to 7 pm on 4th</sup> August 2019. The hovmuller analysis showed that salinity, conductivity, total dissolved solids, and pH values increased during the flood phase and decreased during the ebb phase while oxygen concentration decreased during the flood and increased during the ebb phase. The stratification parameter has shown that the influx of seawater during high tide shifts the Kienké estuary from a well-mixed to a partially mixed environment.展开更多
In total 36 superior clones of Dalbergia sissoo Roxb., screened from 300 selections conducted in natural and growing range of India and Nepal, were multiplied using single nodal cuttings and estab- lished to evaluate ...In total 36 superior clones of Dalbergia sissoo Roxb., screened from 300 selections conducted in natural and growing range of India and Nepal, were multiplied using single nodal cuttings and estab- lished to evaluate genotypexenvironmental interactions for adaptability and stability at the age of 30 months in three geographical locations in the state of Punjab, India. Clone 124 had maximum adaptability and stability （bi = 1.04） to perform exceedingly well over the locations. Clones 36 and 1 were stable with mean regression coefficient of 0.84 and 1.22, respectively. Nonetheless, clone 4 1 performed exceedingly well for all the characters to attain maximum population mean, and the perform- ance varied substantially across the locations. Therefore, clone 41 was considered as productive but non-adaptive clone. Though some of the clones were sensitive to sites, 14 clones for height, 16 for collar diameter, 12 for DBH and 7 for volume were relatively un-sensitive with higher regression coefficient. Nonetheless, clone 124 was the most Stable with average bi value of 1.04 and productive, which could play an important role in future breeding and commercial deployment of stable and produc- tive planting stock of Dalbergia sissoo.展开更多
基金Supported by the National Natural Science Foundation of China
文摘PLS （Partial Least Squares regression） is introduced into an automatic estimation of fundamental stellar spectral parameters. It extracts the most correlative spectral component to the parameters （Teff, log g and [Fe/H]）, and sets up a linear regression function from spectra to the corresponding parameters. Considering the properties of stellar spectra and the PLS algorithm, we present a piecewise PLS regression method for estimation of stellar parameters, which is composed of one PLS model for Teff, and seven PLS models for log g and [Fe/H] estimation. Its performance is investigated by large experiments on flux calibrated spectra and continuum normalized spectra at different signal-to-noise ratios （SNRs） and resolutions. The results show that the piecewise PLS method is robust for spectra at the medium resolution of 0.23 nm. For low resolution 0.5 nm and 1 nm spectra, it achieves competitive results at higher SNR. Experiments using ELODIE spectra of 0.23 nm resolution illustrate that our piecewise PLS models trained with MILES spectra are efficient for O ～ G stars： for flux calibrated spectra, the systematic offsets are 3.8%, 0.14 dex, and -0.09 dex for Teff, log g and [Fe/H], with error scatters of 5.2%, 0.44 dex and 0.38 dex, respectively; for continuum normalized spectra, the systematic offsets are 3.8%, 0.12dex, and -0.13 dex for Teff, log g and [Fe/H], with error scatters of 5.2%, 0.49 dex and 0.41 dex, respectively. The PLS method is rapid, easy to use and does not rely as strongly on the tightness of a parameter grid of templates to reach high precision as Artificial Neural Networks or minimum distance methods do.
文摘The aim of this study was to highlight the effect of tide on the variation of the physicochemical parameter in the Kienké estuary. Six (06) environmental variables were monitored at nine (09) stations with the time step of one hour from 7 am to 7 pm on 4th</sup> August 2019. The hovmuller analysis showed that salinity, conductivity, total dissolved solids, and pH values increased during the flood phase and decreased during the ebb phase while oxygen concentration decreased during the flood and increased during the ebb phase. The stratification parameter has shown that the influx of seawater during high tide shifts the Kienké estuary from a well-mixed to a partially mixed environment.
文摘In total 36 superior clones of Dalbergia sissoo Roxb., screened from 300 selections conducted in natural and growing range of India and Nepal, were multiplied using single nodal cuttings and estab- lished to evaluate genotypexenvironmental interactions for adaptability and stability at the age of 30 months in three geographical locations in the state of Punjab, India. Clone 124 had maximum adaptability and stability （bi = 1.04） to perform exceedingly well over the locations. Clones 36 and 1 were stable with mean regression coefficient of 0.84 and 1.22, respectively. Nonetheless, clone 4 1 performed exceedingly well for all the characters to attain maximum population mean, and the perform- ance varied substantially across the locations. Therefore, clone 41 was considered as productive but non-adaptive clone. Though some of the clones were sensitive to sites, 14 clones for height, 16 for collar diameter, 12 for DBH and 7 for volume were relatively un-sensitive with higher regression coefficient. Nonetheless, clone 124 was the most Stable with average bi value of 1.04 and productive, which could play an important role in future breeding and commercial deployment of stable and produc- tive planting stock of Dalbergia sissoo.
