In the current study, an artificial neural network (ANN) and multiple linear regressions (MLR) have been used to develop predictive models for the estimation of molecular diffusion coefficients of ...1252 polar and non-polar binary gases at multiple pressures over a wide range of temperatures and substances. The quality and reliability of each method were estimated in terms of the correlation coefficient (R), mean squared errors (MSE), root mean squared error (RMSE), and in terms of external validation coefficients (Q2ext). The comparison between the artificial neural network (ANN) and the multiple linear regressions (MLR) revealed that the neural network models showed a good predicting ability with lower errors (the roots of the mean squared errors in the total database were 0.1400 for ANN1 and 0.1300 for ANN2), and (root mean squared errors in the total databases were 0.5172 for MLR1 and 0.5000 for MLR2).
In the current study, an
artificial neural network
(ANN) and
multiple linear regressions
(MLR) have been used to develop predictive models for the estimation of molecular diffusion coefficients of ...1252 polar and non-polar binary gases at multiple pressures over a wide range of temperatures and substances. The quality and reliability of each method were estimated in terms of the
correlation coefficient
(R),
mean squared errors
(MSE),
root mean squared error
(RMSE), and in terms of
external validation coefficients
(Q2ext).
The comparison between the artificial neural network (ANN) and the multiple linear regressions (MLR) revealed that the neural network models showed a good predicting ability with lower errors (the roots of the mean squared errors in the total database were 0.1400 for ANN1 and 0.1300 for ANN2), and (root mean squared errors in the total databases were 0.5172 for MLR1 and 0.5000 for MLR2).
U ovoj studiji primijenjene su
umjetna neuronska mreža
(ANN) i
model višestruke linearne regresije
(MLR) za razvoj prediktivnih modela za procjenu koeficijenata molekularne difuzije 1252 polarnih i nepolarnih binarnih plinova pri višestrukim tlakovima u širokom rasponu temperatura i tvari. Kvaliteta i pouzdanost svake metode procijenjeni su pomoću
korelacijskog koeficijenta
(R),
srednjih kvadratnih pogrešaka
(MSE),
korijena srednje kvadratne pogreške
(RMSE) te
koeficijenata vanjske validacije
(Q2ext).
Usporedba između umjetne neuronske mreže (ANN) i višestrukih linearnih regresija (MLR) otkrila je da modeli neuronske mreže pokazuju dobru sposobnost predviđanja s nižim pogreškama (korijeni srednjih kvadratnih pogrešaka u ukupnoj bazi podataka bili su 0,1400 za ANN1 i 0 (1300 za ANN2 a pogreške korijena srednje vrijednosti u ukupnim bazama podataka bile su 0,5172 za MLR1 i 0,5000 za MLR2).
A set of 119 monatomic Gas was used to train validation and test the performance of the ANN, good correlations were found (R=0.993 for NN). The root mean squared errors for the total data set were ...l%, and mean square errors (MSE) 0.01 for NN. Moreover, it was revealed by the comparison between the forecasted out comes and other models that the neural network models provided greater results.
Particulate Matter (PM) is a complex and heterogeneous mixture of atmospheric particles recognized as a threat to human health. Oxidative Potential (OP) measurement is a promising and integrative ...method for estimating PM-induced health impacts since it is recognized as more closely associated with adverse health effects than ordinarily used PM mass concentrations. OP measurements could be introduced in the air quality monitoring, along with the parameters currently evaluated. PM deposition in the lungs induces oxidative stress, inflammation, and DNA damage.
The study aimed to compare the OP measurements with toxicological effects on BEAS-2B and THP-1 cells of winter and summer PM1 collected in the Po Valley (Italy) during 2021. PM1 was extracted in deionized water by mechanical agitation and tested for OP and, in parallel, used to treat cells. Cytotoxicity, genotoxicity, oxidative stress, and inflammatory responses were assessed by MTT test, DCFH-DA assay, micronucleus, γ-H2AX, comet assay modified with endonucleases, ELISA, and Real-Time PCR. The evaluation of OP was performed by applying three different assays: dithiothreitol (OPDTT), ascorbic acid (OPAA), and 2′,7′-dichlorofluorescein (OPDCFH), in addition, the reducing potential was also analysed (RPDPPH).
Seasonal differences were detected in all the parameters investigated. The amount of DNA damage detected with the Comet assay and ROS formation highlights the presence of oxidative damage both in winter and in summer samples, while DNA damage (micronucleus) and genes regulation were mainly detected in winter samples. A positive correlation with OPDCFH (Spearman's analysis, p < 0.05) was detected for IL-8 secretion and γ-H2AX.
These results provide a biological support to the implementation in air quality monitoring of OP measurements as a useful proxy to estimate PM-induced cellular toxicological responses. In addition, these results provide new insights for the assessment of the ability of secondary aerosol in the background atmosphere to induce oxidative stress and health effects.
•Implementation of OP measurements as a useful proxy to estimate PM-induced toxicity.•Secondary aerosol in the background atmosphere is able to induce oxidative stress.•PM1 induces DNA damage and alteration of gene expression in absence of cytotoxicity.
Particulate Matter (PM) is a complex and heterogeneous mixture of atmospheric particles recognized as a threat to human health. Oxidative Potential (OP) measurement is a promising and integrative ...method for estimating PM-induced health impacts since it is recognized as more closely associated with adverse health effects than ordinarily used PM mass concentrations. OP measurements could be introduced in the air quality monitoring, along with the parameters currently evaluated. PM deposition in the lungs induces oxidative stress, inflammation, and DNA damage. The study aimed to compare the OP measurements with toxicological effects on BEAS-2B and THP-1 cells of winter and summer PM
collected in the Po Valley (Italy) during 2021. PM
was extracted in deionized water by mechanical agitation and tested for OP and, in parallel, used to treat cells. Cytotoxicity, genotoxicity, oxidative stress, and inflammatory responses were assessed by MTT test, DCFH-DA assay, micronucleus, γ-H2AX, comet assay modified with endonucleases, ELISA, and Real-Time PCR. The evaluation of OP was performed by applying three different assays: dithiothreitol (OP
), ascorbic acid (OP
), and 2',7'-dichlorofluorescein (OP
), in addition, the reducing potential was also analysed (RP
). Seasonal differences were detected in all the parameters investigated. The amount of DNA damage detected with the Comet assay and ROS formation highlights the presence of oxidative damage both in winter and in summer samples, while DNA damage (micronucleus) and genes regulation were mainly detected in winter samples. A positive correlation with OP
(Spearman's analysis, p < 0.05) was detected for IL-8 secretion and γ-H2AX. These results provide a biological support to the implementation in air quality monitoring of OP measurements as a useful proxy to estimate PM-induced cellular toxicological responses. In addition, these results provide new insights for the assessment of the ability of secondary aerosol in the background atmosphere to induce oxidative stress and health effects.
PDF
