72 research outputs found
Vertical distribution of suspended particulate matter and its response to river discharge and seawater intrusion: a case study in the Pearl River Estuary during the 2020 dry season
The vertical distribution of suspended particulate matter (SPM) in the Pearl River Estuary (PRE) during winter has not been widely reported. The aim of this paper is to describe the high-resolution vertical distribution of SPM along the transect based on the in-situ observations (including SPM, attenuation coefficient, and particle backscattering coefficient) from three transects of the winter cruise in the northern South China Sea in 2020. The empirical relationship between SPM and bio-optical parameters with correlation coefficients greater than 0.7 is also established and combined with model data to further discuss the mechanism of river discharge and seawater intrusion effects on the vertical distribution of SPM. In the horizontal distribution, the mass concentration of SPM was high in the nearshore region and was low in the offshore region. In the vertical direction, the mass concentration of SPM in the offshore region was more homogeneous, while the mass concentration of SPM in the nearshore region varied greatly, showing a pattern of high bottom and middle layer or high bottom and surface layer. The difference in the vertical distribution of SPM in the nearshore area is the combined effect of river discharge and seawater intrusion on the resuspension of sediment and the inhibition of the spread of high SPM
Gender differences in the clinical management of patients with angina pectoris: a cross-sectional survey in primary care
Non peer reviewedPublisher PD
A comparison of empirical BLUP with different considerations of residual error variance for genotype evaluation of multi-location trials
AbstractThe empirical best linear unbiased prediction (eBLUP) is usually based on the assumption that the residual error variance (REV) is homogenous. This may be unrealistic, and therefore limits the accuracy of genotype evaluations for multi-location trials, where the REV often varies across locations. The objective of this contribution was to investigate the direct implications of the eBLUP with different considerations about REV based on the mixed model for evaluation of genotype simple effects (i.e. genotype effects at individual locations). A series of 14 multi-location trials from a rape-breeding program in the north of China were simultaneously analyzed from 2012 to 2014 using a randomized complete block design at each location. The results showed that the model with heterogeneous REV was more appropriate than the one with homogeneous REV in all of the trials according to model fitting statistics. Whether the REV differences across locations were accounted for in the analysis procedure influenced the variance estimate of related random effects and testing of the variance of genotype-location (G-L) interactions. Ignoring REV differences by use of the eBLUP could result not only in an inflation or deflation of statistical Type I error rates for pair-wise testing but also in an inaccurate ranking of genotype simple effects for these trials. Therefore, it is suggested that in application of the eBLUP for evaluation of genotype simple effects in multi-location trials, the heterogeneity of REV should be accounted for based on mixed model approaches with appropriate variance-covariance structure
A comparison of empirical BLUP with different considerations of residual error variance for genotype evaluation of multi-location trials
Abstract
The empirical best linear unbiased prediction (eBLUP) is usually based on the assumption that the residual error variance (REV) is homogenous. This may be unrealistic, and therefore limits the accuracy of genotype evaluations for multi-location trials, where the REV often varies across locations. The objective of this contribution was to investigate the direct implications of the eBLUP with different considerations about REV based on the mixed model for evaluation of genotype simple effects (i.e. genotype effects at individual locations). A series of 14 multi-location trials from a rape-breeding program in the north of China were simultaneously analyzed from 2012 to 2014 using a randomized complete block design at each location. The results showed that the model with heterogeneous REV was more appropriate than the one with homogeneous REV in all of the trials according to model fitting statistics. Whether the REV differences across locations were accounted for in the analysis procedure influenced the variance estimate of related random effects and testing of the variance of genotype-location (G-L) interactions. Ignoring REV differences by use of the eBLUP could result not only in an inflation or deflation of statistical Type I error rates for pair-wise testing but also in an inaccurate ranking of genotype simple effects for these trials. Therefore, it is suggested that in application of the eBLUP for evaluation of genotype simple effects in multi-location trials, the heterogeneity of REV should be accounted for based on mixed model approaches with appropriate variance-covariance structure
Precatalyst Evolution in PBiP-Pd Complexes for Electrocatalytic Proton Reduction
Main-group metals as supporting ligands for transition metals offer potential for bimetallic
synergistic effects. We investigated a bismuth-palladium system utilizing a PBiP pincer ligand
(BiPdCl) as precatalysts for electrocatalytic proton reduction with thiophenol. Rinse tests revealed
the formation of a surface-bound active species, likely comprised of Pd-based heterogenous
materials. NMR and UV-visible spectroscopic studies unveiled that in diluted solutions of polar
coordinating solvents, the chloride trans to the bismuthane readily dissociates, affording the
solvent-coordinated species (BiPdsolvent) as the predominant solution species. Following thiol–
solvent ligand exchange, an equilibrium mixture of the solvent-bound species and the thiolate
complex (BiPdS) forms. The crystal structures of BiPdS and an acetonitrile-coordinated model
complex (BiPdAcN) shows the thermodynamic trans influence of the bismuthane ligand. Structural
analysis, corroborated by computational investigations, suggests that the reduction of BiPdsolvent is
primarily ligand-based than Pd-centered, hinting at a Bi(III)–Pd(0) oxidation states rather than the
Bi(I)–Pd(II) model suggested by the Lewis structure of BiPdsolvent. The electron-rich Pd and
electron-poor Bi centers explain its electrochemical decomposition similar to other Pd(0) species.
Our findings shed light on the electronic properties and reactivities of the studied Bi–Pd
compounds, offering an example of ambiguous oxidation states within this system
Progressive Bilateral-Context Driven Model for Post-Processing Person Re-Identification
Most existing person re-identification methods compute pairwise similarity by extracting robust visual features and learning the discriminative
metric. Owing to visual ambiguities, these content-based methods that determine the pairwise relationship only based on the similarity between
them, inevitably produce a suboptimal ranking list. Instead, the pairwise similarity can be estimated more accurately along the geodesic path of
the underlying data manifold by exploring the rich contextual information of the sample. In this paper, we propose a lightweight post-processing
person re-identification method in which the pairwise measure is determined by the relationship between the sample and the counterpart's
context in an unsupervised way. We translate the point-to-point comparison into the bilateral point-to-set comparison. The sample's context is
composed of its neighbor samples with two different definition ways: the first order context and the second order context, which are used to
compute the pairwise similarity in sequence, resulting in a progressive post-processing model. The experiments on four large-scale person
re-identification benchmark datasets indicate that (1) the proposed method can consistently achieve higher accuracies by serving as a
post-processing procedure after the content-based person re-identification methods, showing its state-of-the-art results, (2) the proposed
lightweight method only needs about 6 milliseconds for optimizing the ranking results of one sample, showing its high-efficiency. Code is available
at: https://github.com/123ci/PBCmodel
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