• Korean Journal of Environmental Agriculture
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• v.40 no.2
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• pp.127-133
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• 2021

BACKGROUND: Dithiocarbamte fungicides have been used in crop cultivation for diseases protection and treatment. And cultivated agricultrual products were used as feedstuff, and residual pesticides are likely to be absorbed and transferred to livestock. But the maximum residue limits (MRLs) were not established for dithiocarbate fungicides in livestock products, and thus an analysis method was developed and validated for dithiocarbamate fungicides to establish MRLs. METHODS AND RESULTS: Samples were prepared using CS₂ trap method and detected with UV/VIS spectrophotometer. Calibration line (0.1 ~ 10 ㎍/mL) was linear with r² > 0.99. For validation, the recovery tests were carried out at three fortification levels (MLOQ, 10 MLOQ and 50 MLOQ) from livestock samples (egg, milk, beef, pork, and chicken). The results for mancozeb, propineb, and thiram ranged between 76.8 to 109.6%, 79.4 to 108.8%, and 80.2 to 107.8%, respectively and % RSD (relative standard deviation) values were below 9.5%. Furthermore, inter-laboratory analysis was performed to validate the method. CONCLUSION: All values were corresponded with the criteria ranges requested by both the CODEX (CAC/GL 40-1993, 2003) and MFDS guidelines (2016). This might be used as an official analytical method for determination of dithiocarbamate fungicides at established MRLs and monitoring.

• Computers and Concrete
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• v.27 no.4
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• pp.319-332
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• 2021

The performance of gene expression programming (GEP) in predicting the compressive strength of bacteria-incorporated geopolymer concrete (GPC) was examined in this study. Ground-granulated blast-furnace slag (GGBS), new bacterial strains, fly ash (FA), silica fume (SF), metakaolin (MK), and manufactured sand were used as ingredients in the concrete mixture. For the geopolymer preparation, an 8 M sodium hydroxide (NaOH) solution was used, and the ambient curing temperature (28℃) was maintained for all mixtures. The ratio of sodium silicate (Na2SiO3) to NaOH was 2.33, and the ratio of alkaline liquid to binder was 0.35. Based on experimental data collected from the literature, an evolutionary-based algorithm (GEP) was proposed to develop new predictive models for estimating the compressive strength of GPC containing bacteria. Data were classified into training and testing sets to obtain a closed-form solution using GEP. Independent variables for the model were the constituent materials of GPC, such as FA, MK, SF, and Bacillus bacteria. A total of six GEP formulations were developed for predicting the compressive strength of bacteria-incorporated GPC obtained at 1, 3, 7, 28, 56, and 90 days of curing. 80% and 20% of the data were used for training and testing the models, respectively. R2 values in the range of 0.9747 and 0.9950 (including train and test dataset) were obtained for the concrete samples, which showed that GEP can be used to predict the compressive strength of GPC containing bacteria with minimal error. Moreover, the GEP models were in good agreement with the experimental datasets and were robust and reliable. The models developed could serve as a tool for concrete constructors using geopolymers within the framework of this research.

• Computers and Concrete
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• v.27 no.4
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• pp.333-341
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• 2021

Steel slag, an industrial reject from the steel rolling process, has been identified as one of the suitable, environmentally friendly materials for concrete production. Given that the coarse aggregate portion represents about 70% of concrete constituents, other economic approaches have been found in the use of alternative materials such as steel slag in concrete. Unfortunately, a standard framework for its application is still lacking. Therefore, this study proposed functional model equations for the determination of strength properties (compression and splitting tensile) of steel slag aggregate concrete (SSAC), using gene expression programming (GEP). The study, in the experimental phase, utilized steel slag as a partial replacement of crushed rock, in steps 20%, 40%, 60%, 80%, and 100%, respectively. The predictor variables included in the analysis were cement, sand, granite, steel slag, water/cement ratio, and curing regime (age). For the model development, 60-75% of the dataset was used as the training set, while the remaining data was used for testing the model. Empirical results illustrate that steel aggregate could be used up to 100% replacement of conventional aggregate, while also yielding comparable results as the latter. The GEP-based functional relations were tested statistically. The minimum absolute percentage error (MAPE), and root mean square error (RMSE) for compressive strength are 6.9 and 1.4, and 12.52 and 0.91 for the train and test datasets, respectively. With the consistency of both the training and testing datasets, the model has shown a strong capacity to predict the strength properties of SSAC. The results showed that the proposed model equations are reliably suitable for estimating SSAC strength properties. The GEP-based formula is relatively simple and useful for pre-design applications.

• Computers and Concrete
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• v.27 no.2
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• pp.99-109
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• 2021

Experimental and discrete element methods were used to investigate the effects of echelon non-persistent joint on the failure behaviour of joint's bridge area under uniaxial compressive test. Concrete samples with dimension of 150 mm×100 mm×50 mm were prepared. Uniaxial compressive strength and tensile strength of concrete were 14 MPa and 1MPa, respectivly. Within the specimen, three echelon non-persistent notches were provided. These joints were distributed on the three diagonal plane. the angle of diagonal plane related to horizontal axis were 15°, 30° and 45°. The angle of joints related to diagonal plane were 30°, 45°, 60°. Totally, 9 different configuration systems were prepared for non-persistent joint. In these configurations, the length of joints were taken as 2 cm. Similar to those for joints configuration systems in the experimental tests, 9 models with different echelon non-persistent joint were prepared in numerical model. The axial load was applied to the model by rate of 0.05 mm/min. the results show that the failure process was mostly governed by both of the non-persistent joint angle and diagonal plane angle. The compressive strengths of the specimens were related to the fracture pattern and failure mechanism of the discontinuities. It was shown that the shear behaviour of discontinuities is related to the number of the induced tensile cracks which are increased by increasing the joint angle. The strength of samples increase by increasing both of the joint angle and diagonal plane angle. The failure pattern and failure strength are similar in both methods i.e. the experimental testing and the numerical simulation methods.

• Computers and Concrete
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• v.32 no.2
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• pp.119-138
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• 2023

Concrete carbonation is a prevalent phenomenon that leads to steel reinforcement corrosion in reinforced concrete (RC) structures, thereby decreasing their service life as well as durability. The process of carbonation results in a lower pH level of concrete, resulting in an acidic environment with a pH value below 12. This acidic environment initiates and accelerates the corrosion of steel reinforcement in concrete, rendering it more susceptible to damage and ultimately weakening the overall structural integrity of the RC system. Lower pH values might cause damage to the protective coating of steel, also known as the passive film, thus speeding up the process of corrosion. It is essential to estimate the carbonation factor to reduce the deterioration in concrete structures. A lot of work has gone into developing a carbonation model that is precise and efficient that takes both internal and external factors into account. This study presents an ML-based adaptive-neuro fuzzy inference system (ANFIS) approach to predict the carbonation depth of fly ash (FA)-based concrete structures. Cement content, FA, water-cement ratio, relative humidity, duration, and CO2 level have been used as input parameters to develop the ANFIS model. Six performance indices have been used for finding the accuracy of the developed model and two analytical models. The outcome of the ANFIS model has also been compared with the other models used in this study. The prediction results show that the ANFIS model outperforms analytical models with R-value, MAE, RMSE, and Nash-Sutcliffe efficiency index values of 0.9951, 0.7255 mm, 1.2346 mm, and 0.9957, respectively. Surface plots and sensitivity analysis have also been performed to identify the repercussion of individual features on the carbonation depth of FA-based concrete structures. The developed ANFIS-based model is simple, easy to use, and cost-effective with good accuracy as compared to existing models.

• Computers and Concrete
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• v.34 no.2
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• pp.151-168
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• 2024

This research aimed to appraise the effectiveness of four optimization approaches - cuckoo optimization algorithm (COA), multi-verse optimization (MVO), particle swarm optimization (PSO), and teaching-learning-based optimization (TLBO) - that were enhanced with an artificial neural network (ANN) in predicting the bearing capacity of shallow foundations located on cohesionless soils. The study utilized a database of 97 laboratory experiments, with 68 experiments for training data sets and 29 for testing data sets. The ANN algorithms were optimized by adjusting various variables, such as population size and number of neurons in each hidden layer, through trial-and-error techniques. Input parameters used for analysis included width, depth, geometry, unit weight, and angle of shearing resistance. After performing sensitivity analysis, it was determined that the optimized architecture for the ANN structure was 5×5×1. The study found that all four models demonstrated exceptional prediction performance: COA-MLP, MVO-MLP, PSO-MLP, and TLBO-MLP. It is worth noting that the MVO-MLP model exhibited superior accuracy in generating network outputs for predicting measured values compared to the other models. The training data sets showed R² and RMSE values of (0.07184 and 0.9819), (0.04536 and 0.9928), (0.09194 and 0.9702), and (0.04714 and 0.9923) for COA-MLP, MVO-MLP, PSO-MLP, and TLBO-MLP methods respectively. Similarly, the testing data sets produced R² and RMSE values of (0.08126 and 0.07218), (0.07218 and 0.9814), (0.10827 and 0.95764), and (0.09886 and 0.96481) for COA-MLP, MVO-MLP, PSO-MLP, and TLBO-MLP methods respectively.

• Nutrition Research and Practice
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• v.2 no.4
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• pp.289-294
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• 2008

Pre-B-cell leukemia transcription factor 1 (PBX1), which is located on chromosome 1q23, was recently reported to be associated with type 2 diabetes mellitus. We examined whether single nucleotide polymorphisms (SNPs) of the PBX1 gene are associated with overweight/obesity in a Korean population. We genotyped 66 SNPs in the PBX1 gene and investigated their association with clinical phenotypes found in 214 overweight/obese subjects and 160 control subjects using the Affymetrix Targeted Genotyping chip array. Seven SNPs (g.+75l86C>T, g.+78350C>A, g.+80646C>T, g.+138004C>T, g.+185219G>A, g.+191272A>C, and g.+265317T>A) were associated with the risk of obesity in three models (codominant, dominant, and recessive) (P=0.007-0.05). Haplotype 1 (CAC) and 3 (TAC) of block 3 and haplotype 2 (GGAAT) of block 10 were also strongly associated with the risk of obesity. In the control group, subjects that had homozygote for the major allele for both g.+185219G>A and g.+191272A>C showed lower high density lipoprotein-cholesterol (HDL-C) level compared to those possessing the minor allele, suggesting that the association between the homozygote for the major allele for both g.+185219G>A and g.+191272A>C and HDL-C is attributable to the increased risk of obesity. This study suggests that the PBX1 gene is a possible risk factor in overweight/obese patients.

• Journal of Food Hygiene and Safety
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• v.32 no.4
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• pp.298-305
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• 2017

Benzovindiflupyr is a new pyrazole carboxamide fungicide that inhibits succinate dehydrogenase of mitochondrial respiratory chain. This study was carried out to develop an analytical method for the determination of benzovindiflupyr residues in agricultural commodities using LC-MS/MS. The benzovindiflupyr residues in samples were extracted by using acetonitrile, partitioned with dichloromethane, and then purified with silica solid phase extraction (SPE) cartridge. Correlation coefficient ($r^2$) of benzovindiflupyr standard solution was 0.99 over the calibration ranges ($0.001{\sim}0.5{\mu}g/mL$). Recovery tests were conducted on 5 representative agricultural commodities (mandarin, green pepper, potato, soybean, and hulled rice) to validate the analytical method. The recoveries ranged from 79.3% to 110.0% and then relative standard deviation (RSD) was less than 9.1%. Also the limit of detection (LOD) and limit of quantification (LOQ) were 0.0005 and 0.005 mg/kg, respectively. The recoveries of interlaboratory validation ranged from 83.4% to 117.3% and the coefficient of variation (CV) was 9.0%. All results were followed with Codex guideline (CAC/GL 40) and Ministry of Food and Safety guideline (MFDS, 2016). The proposed new analytical method proved to be accurate, effective, and sensitive for benzovindiflupyr determination and would be used as an official analytical method.

• Korean Journal of Environmental Agriculture
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• v.34 no.4
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• pp.318-327
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• 2015

BACKGROUND: Trinexapac-ethyl is a plant growth regulator (PGR) that inhibits the biosynthesis of plant growth hormone (gibberellin). It is used for the prevention of lodging, increasing yields of cereals, and reducing mowing of turf. The experiment was conducted to establish a determination method for trinexapac-ethyl and its metabolites trinexapac in agricultural products using LC-MS/MS.METHODS AND RESULTS: Trinexapac-ethyl and trinexapac were extracted from agricultural products with methanol/ distilled water and the extract was partitioned with dichloromethane and then detected by LC-MS/MS. Limit of detection(LOD) was 0.003 mg/kg and limit of quantification(LOQ) was 0.01 mg/kg, respectively. Matrix matched calibration curves were linear over the calibration ranges (0.01-1.0 mg/L) for all the analytes into blank extract withr²> 0.997. For validation purposes, recovery studies were carried out at three different concentration levels (LOQ, 10LOQ, 50LOQ,n=5). Recoveries of trinexapacethyl and trinexapac were within the range of 73.6-106.9%, 72.7-99.2%, respectively. The relative standard deviations (RSDs) were less than 9.0%. All values were consistent with the criteria ranges requested in the CODEX guideline(CAC/GL 40, 2003).CONCLUSION: The proposed analytical method was accurate, effective and sensitive for trinexapac-ethyl and trinexapac determination and it can be used to as an official method in Korea.

• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.140-147
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• 2019

An analytical method was developed for the determination of quinoxyfen in agricultural products using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The samples were extracted with 1% acetic acid in acetonitrile and water was removed by liquid-liquid partitioning with $MgSO_4$ (anhydrous magnesium sulfate) and sodium acetate. Dispersive solid-phase extraction (d-SPE) cleanup was carried out using $MgSO_4$, PSA (primary secondary amine), $C_{18}$ (octadecyl) and GCB (graphitized carbon black). The analytes were quantified and confirmed by using LC-MS/MS in positive mode with MRM (multiple reaction monitoring). The matrix-matched calibration curves were constructed using six levels ($0.001-0.25{\mu}g/mL$) and the coefficient of determination ($R^2$) was above 0.99. Recovery results at three concentrations (LOQ, 10 LOQ, and 50 LOQ, n=5) were in the range of 73.5-86.7% with RSDs (relative standard deviations) of less than 8.9%. For inter-laboratory validation, the average recovery was 77.2-95.4% and the CV (coefficient of variation) was below 14.5%. All results were consistent with the criteria ranges requested in the Codex guidelines (CAC/GL 40-1993, 2003) and Food Safety Evaluation Department guidelines (2016). The proposed analytical method was accurate, effective and sensitive for quinoxyfen determination in agricultural commodities. This study could be useful for the safe management of quinoxyfen residues in agricultural products.