Extraction of eutrophic and green ponds from segmentation of high-resolution imagery based on the EAF-Unet algorithm.

Inland ponds exhibit remarkable ubiquity across the globe, playing a vital role in the sustainability of global continental freshwater resources and contributing significantly to their biodiversity. Numerous ponds are eutrophic and experience recurrent seasonal or year-round algal blooms or persistent duckweed cover, conferring a characteristic green hue. Here, we denote these eutrophic and green ponds as EGPs.

Noninvasive prenatal testing of trisomies 21 and 18 by massively parallel sequencing of maternal plasma DNA in twin pregnancies.

Objective: The objective of this study is to assess the performance of noninvasive prenatal testing for trisomies 21 and 18 on the basis of massively parallel sequencing of cell-free DNA from maternal plasma in twin pregnancies.

Method: A double-blind study was performed over 12 months. A total of 189 pregnant women carrying twins were recruited from seven hospitals.

QSAR models for predicting toxicity of polychlorinated dibenzo-p-dioxins and dibenzofurans using quantum chemical descriptors.

By partial least square regression, simple quantitative structure-activity relationship (QSAR) models were developed for the toxicity of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs). Quantum chemical descriptors computed by semi-empirical PM3 method were used as predictor variables. Three optimal QSAR models are developed for 25 PCDDs, 35 PCDFs, 25 PCDDs and 35 PCDFs together, respectively.

[Research on quantitative structure-property relationships for n-octanol/water partition coefficients of phthalic acid esters].

Quantum chemical parameters based on the PM3 method were calculated for phthalic acid esters (PAEs). Using partial least squares (PLS) algorithm, a quantitative structure-property relationships (QSAR) model for the n-octanol/water partition coefficients (K(ow)) of PAEs was developed. The result indicates that the model has a good stability and predicting ability.

Quantitative structure-activity relationships for prediction of the toxicity of hydroxylated and quinoid PCB metabolites.

Quantitative structure-activity relationship (QSAR) models were developed for the in vitro potencies to downregulate gap junctional intercellular communication (GJIC) of hydroxylated polychlorinated biphenyls (OH-PCBs) and PCB quinines using partial least squares (PLS) regression. Quantum chemical descriptors computed by the semiempirical AM1, PM3 and MNDO methods were used as predictor variables. The cross-validated Q2cum values for the three optimal QSAR models are 0.