Ecological risk assessment for difenoconazole in aquatic ecosystems using a web-based interspecies correlation estimation (ICE)-species sensitivity distribution (SSD) model

Shen, Chao; Pan, Xinglu; Wu, Xiaohu; Xu, Jun; Dong, Fengshou; Zheng, Yongquan

doi:10.1016/j.chemosphere.2021.133236

Cited by 18 publications

(4 citation statements)

References 59 publications

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“…Interspecies Correlation Estimation (ICE) models are log-linear least squares regressions of acute toxicity developed from measured toxicity of chemicals previously tested in two taxa. In application, ICE models use available toxicity data of tested species (i.e., surrogate species) as input to predict sensitivity of untested taxa (i.e., predicted species, genus, family) ( Bejarano et al, 2017 ; Feng et al, 2013a ; Feng et al, 2013b ; Raimondo et al, 2010 ; Shen et al, 2022 ; Willming et al, 2016 ). ICE models have been widely used to predict the acute toxicity of chemical substances and to derive protective toxicity thresholds with good predictive results ( Fan et al, 2019 ; Feng et al, 2013b ; Raimondo et al, 2010 ; Wang et al, 2020 ; Willming et al, 2016 ) and use of QSAR-estimated values for fish and invertebrates as input into ICE models has been shown to accurately predict acute toxicity to a diversity of species ( Bejarano et al, 2017 ; Douziech et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

A QSAR–ICE–SSD model prediction of the PNECs for alkylphenol substances and application in ecological risk assessment for rivers of a megacity

Hong

Feng²,

Jin³

et al. 2022

Environment International

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Section: Introductionmentioning

confidence: 99%

A QSAR–ICE–SSD model prediction of the PNECs for alkylphenol substances and application in ecological risk assessment for rivers of a megacity

Hong

Feng²,

Jin³

et al. 2022

Environment International

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“…Semi-field experiments performed in Sweden and the Netherlands show chronic toxic effects of azoxystrobin at concentrations that are an order of magnitude lower than the TWACs calculated in this study, with copepods and some Cladocera showing the largest abundance declines (Gustafsson et al, 2010; van Wijngaarden et al, 2014). Difenoconazole has proven to be very toxic to daphnids (Moreira et al ., 2020), fish and algae (Man et al ., 2021) in other ecosystems impacted by rice production (Shen et al ., 2022). On the other hand, MCPA is relatively toxic to eelgrass and dicotyledonous aquatic plants (Nielsen & Dahllöf, 2007), and has been highlighted as one of the most toxic compounds in other rice production areas such as the Ebro Delta in Spain (Barbieri et al ., 2020).…”

Section: Resultsmentioning

confidence: 99%

A Bayesian network approach to assess the influence of climate change and pesticide use practices on the ecological risks of pesticides in a protected Mediterranean wetland

Martínez‐Megías

Mentzel

Fuentes-Edfuf

et al. 2022

Preprint

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Pollution by agricultural pesticides is one of the most important pressures affecting Mediterranean coastal wetlands. Pesticide risks are expected to be influenced by climate change, which will result in an increase of temperatures and a decrease in annual precipitation rates in this region. On the other hand, pesticide dosages are expected to change given the increase in pest resistance and the implementation of environmental policies like the European Farm-to-Fork strategy, which aims for a 50% reduction in pesticide usage by 2030. The influence of climate change and pesticide use practices on the ecological risks of pesticides needs to be evaluated making use of realistic environmental scenarios. This study aimed to assess how different climate change and pesticide use practices affect the ecological risks of pesticides in the Albufera Natural Park (Valencia, Spain), a protected Mediterranean coastal wetland. We performed a probabilistic risk assessment for nine pesticides applied in rice production using scenarios comprised of three climatic regimes (the 2008 record, and projections for 2050 and 2100), three pesticide application regimes (the recommended dose, and 50% increase and 50% decrease), and their combinations. The scenarios were used to simulate pesticide exposure concentrations in the water column of the rice paddies using the RICEWQ model. Pesticide effects were characterized using acute and chronic Species Sensitivity Distributions built with laboratory toxicity data for aquatic organisms. Risk quotients were calculated as probability distributions making use of a Bayesian network approach, and best fitting distributions for the calculated exposure data and the SSDs. Our results show that future climate projections will influence exposure concentrations for some of the studied pesticides, yielding higher dissipation and lower exposure in scenarios dominated by an increase of temperatures, and higher exposure for scenarios in which heavy precipitation events occur after pesticide application. Our case study shows that pesticides such as azoxystrobin, difenoconazole and MCPA are posing high ecological risks for aquatic organisms, and that the implementation of the Farm-to-Fork strategy is crucial to reduce them, although will need additional measures to eliminate them.

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“…The data set of this study is the public wide face dataset. WIDER FACE dataset is utilized to test the designed SSD model, which has rich face samples and is widely used in face recognition and detection [21][22][23][24][25], where it contains a total of 32,203 face images under different conditions such as illumination, occlusion, and scale. This data set is actually extracted from 61 event category videos, which are extracted and divided according to each event category.…”

Section: Process Of "Face Recognition+preplacement Bar Code"mentioning

confidence: 99%

“…The basic form of loss function is as follows [ 23 – 25 ]:

where L loc and L conf are regression and classification loss functions, respectively, and smooth and softmax functions are used for them, respectively. N is the number of positive samples in the prediction box, c is the category confidence prediction value, l is the position prediction value corresponding to the prediction box, g is the position marked by GT, and a is the weight coefficient of position loss and confidence loss.…”

Section: Face Target Detection Based On Ssdmentioning

confidence: 99%

Design of Association Application System of Face Recognition and Test-Tube Barcode Based on CNN

Zhou

Niu

2022

Computational and Mathematical Methods in Medicine

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In order to improve the standardization and accuracy of business process management of laboratory department in hospitals, combined with convolutional neural networks (CNN) and face recognition technology, an association application system of laboratory face recognition and test-tube barcode is designed by inputting patient’s face and blood test-tube barcode into the system for storage. When the patient logs into the system again, the system uses the patient’s face to automatically search for a matching test-tube barcode to obtain the test results. The simulation results show that the system can accurately recognize the face and match the corresponding test-tube barcode, and the accuracy and ROC of face recognition are 0.85 and 0.94, respectively. In addition, when the patient’s face is within 5 m from the system camera, the accuracy of face recognition can reach 100%. It can be seen that the system designed in this paper shows good performance.

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Ecological risk assessment for difenoconazole in aquatic ecosystems using a web-based interspecies correlation estimation (ICE)-species sensitivity distribution (SSD) model

Cited by 18 publications

References 59 publications

A QSAR–ICE–SSD model prediction of the PNECs for alkylphenol substances and application in ecological risk assessment for rivers of a megacity

A QSAR–ICE–SSD model prediction of the PNECs for alkylphenol substances and application in ecological risk assessment for rivers of a megacity

A Bayesian network approach to assess the influence of climate change and pesticide use practices on the ecological risks of pesticides in a protected Mediterranean wetland

Design of Association Application System of Face Recognition and Test-Tube Barcode Based on CNN

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