A New Rapid Determination Method of Soil Organic Carbon Adsorption Coefficients of Pesticides with Soil Column Liquid Chromatography

Soil column liquid chromatography (SCLC) was developed to determine soil organic carbon adsorption coefficients (E-oc) for chemicals. The uptake by soil of pesticides from water can be conveniently calculated from the related breakthrough curves (BTC). The nine pesticides chosen for determination in this study are soluble ones, with their water solubility ranging from 62 mg/L to Z mg/L. In comparing with existing methods of K-oc, SCLC possesses rapid, online and accurate characteristics.

Coefficient of consolidation by end of arc method

One of the most important issues in geotechnical engineering is excess pore pressure caused by clay soil loading and consolidation. Regarding uncertainties and complexities, this issue has long been the subject of attention of many researchers. In this work, a one-dimensional consolidation apparatus was equipped in a way that pore water pressure and settlement could be continuously read and recorded during consolidation process under static loading. The end of primary consolidation was obtained using water pressure changes helping to present a new method for determining the end of primary consolidation and consolidation coefficient. This method was then compared with two classical theory methods of lg t and t. Using Terzaghi's theory, the way of pore pressure dissipation for lg t, t and the new method was found and compared with experimental results. It is concluded that the new method has better results.

QSPR Studies on lgK_(ow) and lgK_(oc) of Fluorobenzenes and Property Parameters Based on HF and DFT Calculations

Quantum chemistry parameters of 22 fluorobenzenes were computed at six levels using Hartree-Fock and DFT methods. Based on the experimental data of n-octanol/water partition coefficient （lgKow）, a three-parameter （dipole moments （μ）, zero point energy （ZPE） and free energy （G°）） quantitative correlation equation that can predict IgKow was developed using structural and thermodynamic parameters as theoretical descriptors. Similarly, based on experimental data of soil organic carbon sorption coefficient （lgKoc）, the other three-parameter （the most negative atomic net charge of molecule （q^-）, dipole moments （μ） and molecular volume （Vi）） quantitative correlation equation that can predict lgKoc was given. Quantitative correlation equations based on B3LYP/6- 311 G^＊＊ calculation were validated by VIF （variance inflation factors） and t-test and used to predict IgKow and lgKoc of a series of compounds. The result showed that the correlation and prediction ability of lgKoc equations based on three levels of HF/STO-3G, B3LYP/6-31 G^＊ and B3LYP/6- 311G^＊＊ are all more advantageous than those based on AMI.

Dimensionality reduction and prediction of soil consolidation coefficient using random forest coupling with Relief algorithm

The consolidation coefficient of soil(C_(v))is a crucial parameter used for the design of structures leaned on soft soi.In general,the C_(v) is determined experimentally in the laboratory.However,the experimental tests are time-consuming as well as expensive.Therefore,researchers tried several ways to determine C_(v) via other simple soil parameters.In this study,we developed a hybrid model of Random Forest coupling with a Relief algorithm(RF-RL)to predict the C_(v) of soil.To conduct this study,a database of soil parameters collected from a case study region in Vietnam was used for modeling.The performance of the proposed models was assessed via statistical indicators,namely Coefficient of determination(R^(2)),Root Mean Squared Error(RMSE),and Mean Absolute Error(MAE).The proposal models were constructed with four sets of soil variables,including 6,7,8,and 13 inputs.The results revealed that all models performed well with a high performance(R^(2)>0.980).Although the RF-RL model with 13 variables has the highest prediction accuracy(R^(2)=0.9869),the difference compared with other models was negligible(i.e.,R^(2)=0.9824,0.9850,0.9825 for the cases with 6,7,8 inputs,respectively).Thus,it can be concluded that the hybrid model of RF-RL can be employed to predict C_(v) based on the basic soil parameters.