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Papers by Othmane Benkortbi

Research paper thumbnail of Machine learning approach for the prediction of surface tension of binary mixtures containing ionic liquids using σ‐profile descriptors

International Journal of Quantum Chemistry, Oct 17, 2022

Research paper thumbnail of A new hybrid quantitative structure property relationships‐support vector regression (<scp>QSPR‐SVR</scp>) approach for predicting the solubility of drug compounds in supercritical carbon dioxide

Aiche Journal, May 2, 2023

The purpose of this work was to compare the performance of 7 meta‐heuristics algorithms namely: D... more The purpose of this work was to compare the performance of 7 meta‐heuristics algorithms namely: Dragonfly (DA), Ant Lion (ALO), Grey Wolf (GWO), Artificial Bee Colony (ABC), Particle Swarm (PSO), Whale (WAO), and a hybrid Particle Swarm with Grey Wolf (HPSOGWO) optimizers in terms of fine‐tuning hyper‐parameters of a hybrid quantitative structure property relationships (QSPR)‐support vector regression (SVR) for the prediction of molar fraction solubilities of drug compounds in supercritical carbon dioxide (SC‐CO2). A dataset of 168 drug compounds, 13 inputs, and 4490 experimental data points was used to achieve the goal. All 7 models were statistically and graphically approved while the HPSOGWO‐SVR was found to over‐perform with an average absolute relative deviation (AARD) of 0.706% and an AIC of −14,434,249. The model was subjected to an external test (validation) using 160 experimental data points that were not used in the training and the test set. The overall results proved that the obtained model has good predictivity ability and robustness.

Research paper thumbnail of Contribution of Chemometric Modeling to Chemical Risks Assessment for Aquatic Plants

Chemometrics and Cheminformatics in Aquatic Toxicology, 2021

Research paper thumbnail of A Quantitative Structure Activity Relationship for acute oral toxicity of pesticides on rats: Validation, domain of application and prediction

Journal of Hazardous Materials, Feb 1, 2016

Quantitative Structure Activity Relationship (QSAR) models are expected to play an important role... more Quantitative Structure Activity Relationship (QSAR) models are expected to play an important role in the risk assessment of chemicals on humans and the environment. In this study, we developed a validated QSAR model to predict acute oral toxicity of 329 pesticides to rats because a few QSAR models have been devoted to predict the Lethal Dose 50 (LD50) of pesticides on rats. This QSAR model is based on 17 molecular descriptors, and is robust, externally predictive and characterized by a good applicability domain. The best results were obtained with a 17/9/1 Artificial Neural Network model trained with the Quasi Newton back propagation (BFGS) algorithm. The prediction accuracy for the external validation set was estimated by the Q 2 ext and the Root Mean Square error (RMS) which are equal to 0.948 and 0.201, respectively. 98.6% of external validation set is correctly predicted and the present model proved to be superior to models previously published. Accordingly, the model developed in this study provides excellent predictions and can be used to predict the acute oral toxicity of pesticides, particularly for those that have not been tested as well as new pesticides.

Research paper thumbnail of Removal of Methylene Blue by Adsorption onto Retama Raetam Plant: Kinetics and Equilibrium Study

Chemistry Journal of Moldova, 2016

The feasibility of using medicinal plants species Retama raetam as a low cost and an eco-friendly... more The feasibility of using medicinal plants species Retama raetam as a low cost and an eco-friendly adsorbent for the adsorption of cationic dye methylene blue from simulated aqueous solution has been investigated. Adsorption kinetics of methylene blue onto Retama raetam plants was studied in a batch system. The effects of pH and contact time were examined. The methylene blue maximum adsorption occurred at pH 8 and the lowest adsorption occurred at pH 2. The apparent equilibrium was reached after 120 min. Optimal experimental conditions were determined. Adsorption modelling parameters for Freundlich and Langmuir isotherms were determined and, based on R 2 , various error distribution functions were evaluated as well. Adsorption isotherm was best described by non linear Freundlich isotherm model. Thermodynamic studies show that adsorption was spontaneous and exothermic. For determining the best-fi t-kinetic adsorption model, the experimental data were analyzed by using pseudo-fi rst-order, pseudo-second-order, pseudo-third-order, Esquivel, and Elovich models. Linear regressive and non-linear regressive method was used to obtain the relative parameters. The statistical functions were estimated to fi nd the suitable method that fi t better the experimental data. Both methods were appropriate for obtaining the parameters. The linear pseudo-second-order (type 9 and type 10) models were the best to fi t the equilibrium data. The present work showed that plant Retama raetam can be used as a low cost adsorbent for the removal of methylene blue from water.

Research paper thumbnail of QSPR Modelling of the Solubility of Drug and Drug‐like Compounds in Supercritical Carbon Dioxide

Molecular Informatics

A quantitative structure-property relationship (QSPR) modeling was carried out for predicting dru... more A quantitative structure-property relationship (QSPR) modeling was carried out for predicting drug and drug-like compounds solubility in supercritical carbon dioxide. For the first time, a dataset of 148 drug\drug-like compounds, accounting for 3971 experimental data points (EDPs), was collected and used for modelling the relationship between selected molecular descriptors and solubility fraction data achieved by a nonlinear approached (Artificial neural network, ANN) based on molecular descriptors. Experimental solubility data for a given drug are published as a function of temperature and pressure. In this study, 11 significant PaDEL descriptors (AATS3v, MATS2e, GATS4c, GATS3v, GATS4e, GATS3s, nBondsM, AVP-0, SHBd, MLogP, and MLFER_S), the temperature and the pressure were statistically proved to be sufficient inputs. The architecture of the optimised model was found to be {13,10,1}. Validation of the model was checked using several recommended statistical metrics, including Average absolute relative deviation (AARD=3.7748%), Root Mean Square Error (RMSE=0.5162), Coefficient of Correlation (r=0.9761), Coefficient of Determination (R²=0.9528), and Robustise (Q²=0.9528). The model was also subjected to an external test by using 143 EDPs. Sensitivity analysis and domain of application were examined. The overall results confirm that the optimised ANN-QSPR model can be used reliably for the correlation and prediction of this property.

Research paper thumbnail of In silico prediction of the inhibition of new molecules on 3CLpro SARS-CoV-2 enzyme by using QSAR-SVRPSO approach

Continuous effort is dedicated to the discovery of potential drugs for the novel coronavirus-2 bo... more Continuous effort is dedicated to the discovery of potential drugs for the novel coronavirus-2 both clinically and computationally. Computer-Aided Drug Design CADD is the backbone of drug discovery, and shifting to computational approaches has become a need. Quantitative Structure-Activity Relationship QSAR is a widely used approach in predicting the activity of potential molecules and is an early step in drug discovery. 3CLpro is a highly conserved enzyme in the coronaviruses characterized by its role in the viral replication cycle. Despite the existence of various vaccines, the development of a new drug for SARS-CoV-2 is a necessity to provide cures to patients. In the pursuit of exploring new potential 3CLpro SARS-CoV-2 inhibitors and contributing to the existing literature, this work opted to build and compare three models of QSAR to correlate between the molecules’ structure and their activity: IC50, through the application of MLR, SVR, and SVR-PSO algorithms. The database was ...

Research paper thumbnail of A Numerical Simulation Under Milk Fouling in A Plate Heat Exchanger in The Presence of a Porous Medium

Journal of Advanced Research in Fluid Mechanics and Thermal Sciences

Fouling is a known dairy industry issue during thermal treatments using a plate heat exchanger (P... more Fouling is a known dairy industry issue during thermal treatments using a plate heat exchanger (PHE) it directly affects not only energy costs and maintenance but also production, energy and water losses during cleaning operations. Therefore, a considerable attention has been paid to the modelling of the fouling phenomena in order to improve the PHE performances. In this paper, a mathematical model describing the steady state was established for the flow at the macroscopic scale; the model account for constant and turbulent flows between two flat parallel plates at imposed temperature in the presence of a porous medium. The closure k-ε model has been chosen and the conservation of equations has been developed. The numerical procedure adopted was based on the finite volume method on the Fluent CFD software. The accuracy of the Fluent software was validated by comparing our results with those previously published in the literature. The numerical results showed a good reliability of th...

Research paper thumbnail of Comparative Therapeutic Properties of Garlic Extract and Metformin on Hyperglycaemia, Hypercholesterolaemia, and Hypertriglyceridaemia in Alloxan-induced Type1-like Diabetic Rats

Kemija u industriji

The current pilot study was conducted to compare the triple effect of garlic extract and metformi... more The current pilot study was conducted to compare the triple effect of garlic extract and metformin on hyperglycaemia, hypercholesterolaemia, and hypertriglyceridaemia in alloxan-induced type 1-like diabetic rats. Wistar rats were randomly divided into four groups. Control group included normal rats. The second group included alloxan-induced type 1-like diabetic rats, receiving no treatment. The other two groups of diabetic rats were orally treated with 0.75 g of garlic extract per kg of body weight and 0.05 of metformin g per kg of body weight respectively for four weeks. The pharmacological impact of garlic compounds on serum glucose and lipids as opposed to the glucose-lowering and lipid-lowering was highlighted in these experiments. These results revealed that garlic extract has a triple action on hyperglycaemia, hypertriglyceridemia, and hypercholesterolemia. Its effect on hyperglycaemia is long lasting, and more pronounced compared to the metformin. Interestingly, it had a regulatory effect on glycaemia as highlighted in the control group.

Research paper thumbnail of Contribution of Chemometric Modeling to Chemical Risks Assessment for Aquatic Plants

Chemometrics and Cheminformatics in Aquatic Toxicology, 2021

Research paper thumbnail of Response surface methodology for the study of interactions between components in a micellar system formulation

Journal of the Serbian Chemical Society, 2021

This work aims to examine the interaction of certain physicochemical properties on micellar syste... more This work aims to examine the interaction of certain physicochemical properties on micellar systems constituted of a polymer (sodium alginate), two surfactants (CTand tween 80), and Algerian olive oil. Response surface modelling (RSM) was applied to study the combined effects of systems containing each type of surfactant. The monitoring of four independent parameters such as the interfacial tension (Y1), the conductivity (Y2), the viscosity (Y3), and the turbidity (Y4) as responses for the experimental design model allowed to determine the performance of the models established. Based on statistical analyzes, the coefficients R2 and Q2 for the interfacial tension, the conductivity, the viscosity and the turbidity are: 0.998 and 0.805; 0.982 and 0.742; 0.976 and 0.734, and 0.985 and 0.723; respectively. The obtained results indicate that these models showed a good predictive power for an optimal system composed of CTAB, Tween 80, AlgNa, and olive oil. For the CT/ AlgNa and CT/ olive o...

Research paper thumbnail of Artificial neural network-based equation to predict the toxicity of herbicides on rats

Chemometrics and Intelligent Laboratory Systems, 2016

The use of herbicides is increasing around the world. The benefits achieved by the use of these h... more The use of herbicides is increasing around the world. The benefits achieved by the use of these herbicides are indisputable. Despite their importance in agriculture, herbicides can be dangerous to the environment and the human health, depending on their toxicity, and the degree of contamination. Also, it is essential and evident that the risk assessment of herbicides is an important task in the environmental protection. The objective of this work was to investigate and implement an Artificial Neural Network (ANN) model for the prediction of acute oral toxicity of 77 herbicides to rats. Internal and external validations of the model showed high and values, in the range 0.782-0.997 for the training and the test. In addition, the major contribution of the current work was to develop artificial neural network-based equation to predict the toxicity of 13 other herbicides; the mathematical equation using the weights of the network gave very significant results, leading to an R 2 value of 0.959. The agreement between calculated and experimental values of acute toxicity confirmed the ability of ANN-based equation to predict the toxicity for herbicides that have not been tested as well as new herbicides.

Research paper thumbnail of Removal of Amoxicillin Antibiotic from Aqueous Solution Using an Anionic Surfactant

Water, Air, & Soil Pollution, 2015

A novel separation technique based on an aqueous surfactant extraction to remove organic contamin... more A novel separation technique based on an aqueous surfactant extraction to remove organic contaminants from aqueous solutions was investigated. A model was developed regarding the kinetic partitioning of amoxicillin and regarding the mechanism governing the forward transfer of amoxicillin in a reverse micelle system. Results were interpreted in terms of a two-film theory for flat interface. To confirm the relevance of the developed separation technique, it was applied to the elimination of amoxicillin by adsorption on an anionic surfactant, sodium dodecyl sulfate. The effects of various parameters such as contact time, pH, temperature, and initial concentration of sodium dodecyl sulfate were investigated at an agitation speed of 350 rpm. The percentage of maximum adsorption capacity of amoxicillin was found to be 87.7 % for the following optimal conditions: amoxicillin concentration of 4 mg/L, 40 min contact time, pH 4, 50 °C, and 0.01 g/L initial sodium dodecyl sulfate concentration. The results showed that the pseudo-first-order model provides most adequate correlation of experimental data compared to the pseudo-second-order model. Three statistical functions were used to estimate the error deviations between experimental and theoretically predicted kinetic adsorption values, including the average relative error deviation (ARED), the sum of the squares of the errors (SSE), and the standard deviation of residuals (Sres). The results showed that, both Freundlich equation and pseudo-first-order equation provide the best fit to experimental data. Adsorption isotherm data appeared to be accurately described by a Freundlich model. The thermodynamic parameters (∆G, ∆H, and ∆S) showed that the process was feasible, spontaneous, and exothermic.

Research paper thumbnail of Prediction of Acute Herbicide Toxicity in Rats from Quantitative Structure–Activity Relationship Modeling

Environmental Engineering Science, 2014

Extensive use of herbicides raises concerns about adverse effects on the environment. Studies on ... more Extensive use of herbicides raises concerns about adverse effects on the environment. Studies on toxicity of herbicides are few and relatively old. The purpose of this study was to use multiple linear regressions (MLR) and Multilayered Perceptron artificial neural networks (MLP-ANN) to predict the oral acute toxicity (halfmaximal lethal dose [LD 50 ]) of a diverse set of 62 herbicides on rats. Quantitative structure-activity relationship (QSAR) models obtained by using relevant descriptors showed good predictability. Primary contributions to toxicity were the following descriptors: HATS0m, HATSe, and nS. Comparison of results obtained using the MLP-ANN model with those from the MLR model revealed the superiority of the MLP-ANN model. Statistics for prediction of oral acute toxicity for MLR and MLP-ANN were, respectively: R 2 = 0.855, RMSE = 0.270; and R 2 = 0.960, RMSE = 0.118. Comparison of validation results with those of other studies have shown the superiority of the model developed in this work.

Research paper thumbnail of Mass transfer modelling of the extraction of antibiotics from aqueous solution using Biosurfactants

Le Centre pour la Communication Scientifique Directe - HAL - Archive ouverte HAL, 2019

The objective of this work is to modelling a new separation technique based on the removal of ant... more The objective of this work is to modelling a new separation technique based on the removal of antibiotics such as amoxicillin and ampicillin produced by antibiotical company Saidal Médéa (Algeria) from pharmaceutical effluents using biosurfactants and commercial surfactants. The kinetic distribution of amoxicillin and ampicillin between the two phases was modelled in order to well understand the mechanism governing the direct transfer of antibiotics from the aqueous phase to the micellar phase. The results were interpreted in terms of a two-film theory for flat interface. The model of the kinetic transfer developed in this study provides excellent predictions. A very good correlation between predicted and experimental values was found : R2 = 0.98 for the sorption onto biosurfactant and R2 = 0.99 onto a synthetic surfactant. The model coefficients were used to estimate the overall combined mass transfer coefficient and the individual mass transfer coefficients.

Research paper thumbnail of Synthesis and characterization of activated carbon from asphalt

Applied Surface Science, 2006

Asphalt (cheap and available in huge amount in Jordan) was converted into activated carbon powder... more Asphalt (cheap and available in huge amount in Jordan) was converted into activated carbon powder by chemical treatment with sulphuric and nitric acids at 450°C. The final product was characterized and found effective as adsorbent material. Its cation exchange capacity reaches 191.2meq/100-g carbons when treated with 30wt% acid/asphalt ratio without airflow rate injection and 208meq/100-g carbons when 6.5ml air/min was

Research paper thumbnail of Batch kinetics and modelling of Pleuromutilin production by Pleurotus mutilis

Biochemical Engineering Journal, 2007

Research paper thumbnail of Optimization and modelling of the analysis of pleuromutilin antibiotic extracted from biomass

Asian Journal of Chemistry, 2010

Research paper thumbnail of Preventive Activity of Giner (Zingiber officinale) Against Myelotoxicity and Hepatotoxicity Induced by Cyclohexatriene and Identification of the Most Active Compounds by GC-MS

Kemija u industriji, 2021

This study aimed to uncover the preventive capability of Zingiber officinale against myelotoxicit... more This study aimed to uncover the preventive capability of Zingiber officinale against myelotoxicity, leukaemia, and hepatotoxicity. For the most part, this work depended on the subcutaneous injection of cyclohexatriene in rabbits to cause the illness by a synthetic strategy. In parallel, another group of rabbits was exposed to the injection of cyclohexatriene under similar conditions with the feeding Zingiber officinale, where it was discovered that the cyclohexatriene-induced myelotoxicity was counteracted. The histological examination additionally uncovered the hepato-defensive intensity of Zingiber officinale. The most pharmacologically active molecules of Zingiber officinale were recognised by gas chromatography–mass spectrometry (GC-MS).

Research paper thumbnail of QSAR Approaches and Ecotoxicological Risk Assessment

Hundreds of thousands of chemicals that can affect human health or the quality of aquatic and ter... more Hundreds of thousands of chemicals that can affect human health or the quality of aquatic and terrestrial ecosystems are introduced directly or indirectly into the air, water, or soil. Therefore, the awareness of the serious and harmful effects caused by these chemical compounds has revealed the absolute and compelling need to resort to the evaluation of potential risks incurred as a result of exposure to these compounds. In the aim to provide a high level of protection for human, animal, and environmental health, many regulatory agencies have established strict legislation for both toxicological and ecotoxicological risk assessments of existing and new chemical compounds. To limit the in vivo experiments which are a tedious and costly practice and generate a large sacrifice of animals, the REACH regulation recommends the use of in silico methods, such as quantitative structure-activity relationship (QSAR) models.

Research paper thumbnail of Machine learning approach for the prediction of surface tension of binary mixtures containing ionic liquids using σ‐profile descriptors

International Journal of Quantum Chemistry, Oct 17, 2022

Research paper thumbnail of A new hybrid quantitative structure property relationships‐support vector regression (<scp>QSPR‐SVR</scp>) approach for predicting the solubility of drug compounds in supercritical carbon dioxide

Aiche Journal, May 2, 2023

The purpose of this work was to compare the performance of 7 meta‐heuristics algorithms namely: D... more The purpose of this work was to compare the performance of 7 meta‐heuristics algorithms namely: Dragonfly (DA), Ant Lion (ALO), Grey Wolf (GWO), Artificial Bee Colony (ABC), Particle Swarm (PSO), Whale (WAO), and a hybrid Particle Swarm with Grey Wolf (HPSOGWO) optimizers in terms of fine‐tuning hyper‐parameters of a hybrid quantitative structure property relationships (QSPR)‐support vector regression (SVR) for the prediction of molar fraction solubilities of drug compounds in supercritical carbon dioxide (SC‐CO2). A dataset of 168 drug compounds, 13 inputs, and 4490 experimental data points was used to achieve the goal. All 7 models were statistically and graphically approved while the HPSOGWO‐SVR was found to over‐perform with an average absolute relative deviation (AARD) of 0.706% and an AIC of −14,434,249. The model was subjected to an external test (validation) using 160 experimental data points that were not used in the training and the test set. The overall results proved that the obtained model has good predictivity ability and robustness.

Research paper thumbnail of Contribution of Chemometric Modeling to Chemical Risks Assessment for Aquatic Plants

Chemometrics and Cheminformatics in Aquatic Toxicology, 2021

Research paper thumbnail of A Quantitative Structure Activity Relationship for acute oral toxicity of pesticides on rats: Validation, domain of application and prediction

Journal of Hazardous Materials, Feb 1, 2016

Quantitative Structure Activity Relationship (QSAR) models are expected to play an important role... more Quantitative Structure Activity Relationship (QSAR) models are expected to play an important role in the risk assessment of chemicals on humans and the environment. In this study, we developed a validated QSAR model to predict acute oral toxicity of 329 pesticides to rats because a few QSAR models have been devoted to predict the Lethal Dose 50 (LD50) of pesticides on rats. This QSAR model is based on 17 molecular descriptors, and is robust, externally predictive and characterized by a good applicability domain. The best results were obtained with a 17/9/1 Artificial Neural Network model trained with the Quasi Newton back propagation (BFGS) algorithm. The prediction accuracy for the external validation set was estimated by the Q 2 ext and the Root Mean Square error (RMS) which are equal to 0.948 and 0.201, respectively. 98.6% of external validation set is correctly predicted and the present model proved to be superior to models previously published. Accordingly, the model developed in this study provides excellent predictions and can be used to predict the acute oral toxicity of pesticides, particularly for those that have not been tested as well as new pesticides.

Research paper thumbnail of Removal of Methylene Blue by Adsorption onto Retama Raetam Plant: Kinetics and Equilibrium Study

Chemistry Journal of Moldova, 2016

The feasibility of using medicinal plants species Retama raetam as a low cost and an eco-friendly... more The feasibility of using medicinal plants species Retama raetam as a low cost and an eco-friendly adsorbent for the adsorption of cationic dye methylene blue from simulated aqueous solution has been investigated. Adsorption kinetics of methylene blue onto Retama raetam plants was studied in a batch system. The effects of pH and contact time were examined. The methylene blue maximum adsorption occurred at pH 8 and the lowest adsorption occurred at pH 2. The apparent equilibrium was reached after 120 min. Optimal experimental conditions were determined. Adsorption modelling parameters for Freundlich and Langmuir isotherms were determined and, based on R 2 , various error distribution functions were evaluated as well. Adsorption isotherm was best described by non linear Freundlich isotherm model. Thermodynamic studies show that adsorption was spontaneous and exothermic. For determining the best-fi t-kinetic adsorption model, the experimental data were analyzed by using pseudo-fi rst-order, pseudo-second-order, pseudo-third-order, Esquivel, and Elovich models. Linear regressive and non-linear regressive method was used to obtain the relative parameters. The statistical functions were estimated to fi nd the suitable method that fi t better the experimental data. Both methods were appropriate for obtaining the parameters. The linear pseudo-second-order (type 9 and type 10) models were the best to fi t the equilibrium data. The present work showed that plant Retama raetam can be used as a low cost adsorbent for the removal of methylene blue from water.

Research paper thumbnail of QSPR Modelling of the Solubility of Drug and Drug‐like Compounds in Supercritical Carbon Dioxide

Molecular Informatics

A quantitative structure-property relationship (QSPR) modeling was carried out for predicting dru... more A quantitative structure-property relationship (QSPR) modeling was carried out for predicting drug and drug-like compounds solubility in supercritical carbon dioxide. For the first time, a dataset of 148 drug\drug-like compounds, accounting for 3971 experimental data points (EDPs), was collected and used for modelling the relationship between selected molecular descriptors and solubility fraction data achieved by a nonlinear approached (Artificial neural network, ANN) based on molecular descriptors. Experimental solubility data for a given drug are published as a function of temperature and pressure. In this study, 11 significant PaDEL descriptors (AATS3v, MATS2e, GATS4c, GATS3v, GATS4e, GATS3s, nBondsM, AVP-0, SHBd, MLogP, and MLFER_S), the temperature and the pressure were statistically proved to be sufficient inputs. The architecture of the optimised model was found to be {13,10,1}. Validation of the model was checked using several recommended statistical metrics, including Average absolute relative deviation (AARD=3.7748%), Root Mean Square Error (RMSE=0.5162), Coefficient of Correlation (r=0.9761), Coefficient of Determination (R²=0.9528), and Robustise (Q²=0.9528). The model was also subjected to an external test by using 143 EDPs. Sensitivity analysis and domain of application were examined. The overall results confirm that the optimised ANN-QSPR model can be used reliably for the correlation and prediction of this property.

Research paper thumbnail of In silico prediction of the inhibition of new molecules on 3CLpro SARS-CoV-2 enzyme by using QSAR-SVRPSO approach

Continuous effort is dedicated to the discovery of potential drugs for the novel coronavirus-2 bo... more Continuous effort is dedicated to the discovery of potential drugs for the novel coronavirus-2 both clinically and computationally. Computer-Aided Drug Design CADD is the backbone of drug discovery, and shifting to computational approaches has become a need. Quantitative Structure-Activity Relationship QSAR is a widely used approach in predicting the activity of potential molecules and is an early step in drug discovery. 3CLpro is a highly conserved enzyme in the coronaviruses characterized by its role in the viral replication cycle. Despite the existence of various vaccines, the development of a new drug for SARS-CoV-2 is a necessity to provide cures to patients. In the pursuit of exploring new potential 3CLpro SARS-CoV-2 inhibitors and contributing to the existing literature, this work opted to build and compare three models of QSAR to correlate between the molecules’ structure and their activity: IC50, through the application of MLR, SVR, and SVR-PSO algorithms. The database was ...

Research paper thumbnail of A Numerical Simulation Under Milk Fouling in A Plate Heat Exchanger in The Presence of a Porous Medium

Journal of Advanced Research in Fluid Mechanics and Thermal Sciences

Fouling is a known dairy industry issue during thermal treatments using a plate heat exchanger (P... more Fouling is a known dairy industry issue during thermal treatments using a plate heat exchanger (PHE) it directly affects not only energy costs and maintenance but also production, energy and water losses during cleaning operations. Therefore, a considerable attention has been paid to the modelling of the fouling phenomena in order to improve the PHE performances. In this paper, a mathematical model describing the steady state was established for the flow at the macroscopic scale; the model account for constant and turbulent flows between two flat parallel plates at imposed temperature in the presence of a porous medium. The closure k-ε model has been chosen and the conservation of equations has been developed. The numerical procedure adopted was based on the finite volume method on the Fluent CFD software. The accuracy of the Fluent software was validated by comparing our results with those previously published in the literature. The numerical results showed a good reliability of th...

Research paper thumbnail of Comparative Therapeutic Properties of Garlic Extract and Metformin on Hyperglycaemia, Hypercholesterolaemia, and Hypertriglyceridaemia in Alloxan-induced Type1-like Diabetic Rats

Kemija u industriji

The current pilot study was conducted to compare the triple effect of garlic extract and metformi... more The current pilot study was conducted to compare the triple effect of garlic extract and metformin on hyperglycaemia, hypercholesterolaemia, and hypertriglyceridaemia in alloxan-induced type 1-like diabetic rats. Wistar rats were randomly divided into four groups. Control group included normal rats. The second group included alloxan-induced type 1-like diabetic rats, receiving no treatment. The other two groups of diabetic rats were orally treated with 0.75 g of garlic extract per kg of body weight and 0.05 of metformin g per kg of body weight respectively for four weeks. The pharmacological impact of garlic compounds on serum glucose and lipids as opposed to the glucose-lowering and lipid-lowering was highlighted in these experiments. These results revealed that garlic extract has a triple action on hyperglycaemia, hypertriglyceridemia, and hypercholesterolemia. Its effect on hyperglycaemia is long lasting, and more pronounced compared to the metformin. Interestingly, it had a regulatory effect on glycaemia as highlighted in the control group.

Research paper thumbnail of Contribution of Chemometric Modeling to Chemical Risks Assessment for Aquatic Plants

Chemometrics and Cheminformatics in Aquatic Toxicology, 2021

Research paper thumbnail of Response surface methodology for the study of interactions between components in a micellar system formulation

Journal of the Serbian Chemical Society, 2021

This work aims to examine the interaction of certain physicochemical properties on micellar syste... more This work aims to examine the interaction of certain physicochemical properties on micellar systems constituted of a polymer (sodium alginate), two surfactants (CTand tween 80), and Algerian olive oil. Response surface modelling (RSM) was applied to study the combined effects of systems containing each type of surfactant. The monitoring of four independent parameters such as the interfacial tension (Y1), the conductivity (Y2), the viscosity (Y3), and the turbidity (Y4) as responses for the experimental design model allowed to determine the performance of the models established. Based on statistical analyzes, the coefficients R2 and Q2 for the interfacial tension, the conductivity, the viscosity and the turbidity are: 0.998 and 0.805; 0.982 and 0.742; 0.976 and 0.734, and 0.985 and 0.723; respectively. The obtained results indicate that these models showed a good predictive power for an optimal system composed of CTAB, Tween 80, AlgNa, and olive oil. For the CT/ AlgNa and CT/ olive o...

Research paper thumbnail of Artificial neural network-based equation to predict the toxicity of herbicides on rats

Chemometrics and Intelligent Laboratory Systems, 2016

The use of herbicides is increasing around the world. The benefits achieved by the use of these h... more The use of herbicides is increasing around the world. The benefits achieved by the use of these herbicides are indisputable. Despite their importance in agriculture, herbicides can be dangerous to the environment and the human health, depending on their toxicity, and the degree of contamination. Also, it is essential and evident that the risk assessment of herbicides is an important task in the environmental protection. The objective of this work was to investigate and implement an Artificial Neural Network (ANN) model for the prediction of acute oral toxicity of 77 herbicides to rats. Internal and external validations of the model showed high and values, in the range 0.782-0.997 for the training and the test. In addition, the major contribution of the current work was to develop artificial neural network-based equation to predict the toxicity of 13 other herbicides; the mathematical equation using the weights of the network gave very significant results, leading to an R 2 value of 0.959. The agreement between calculated and experimental values of acute toxicity confirmed the ability of ANN-based equation to predict the toxicity for herbicides that have not been tested as well as new herbicides.

Research paper thumbnail of Removal of Amoxicillin Antibiotic from Aqueous Solution Using an Anionic Surfactant

Water, Air, & Soil Pollution, 2015

A novel separation technique based on an aqueous surfactant extraction to remove organic contamin... more A novel separation technique based on an aqueous surfactant extraction to remove organic contaminants from aqueous solutions was investigated. A model was developed regarding the kinetic partitioning of amoxicillin and regarding the mechanism governing the forward transfer of amoxicillin in a reverse micelle system. Results were interpreted in terms of a two-film theory for flat interface. To confirm the relevance of the developed separation technique, it was applied to the elimination of amoxicillin by adsorption on an anionic surfactant, sodium dodecyl sulfate. The effects of various parameters such as contact time, pH, temperature, and initial concentration of sodium dodecyl sulfate were investigated at an agitation speed of 350 rpm. The percentage of maximum adsorption capacity of amoxicillin was found to be 87.7 % for the following optimal conditions: amoxicillin concentration of 4 mg/L, 40 min contact time, pH 4, 50 °C, and 0.01 g/L initial sodium dodecyl sulfate concentration. The results showed that the pseudo-first-order model provides most adequate correlation of experimental data compared to the pseudo-second-order model. Three statistical functions were used to estimate the error deviations between experimental and theoretically predicted kinetic adsorption values, including the average relative error deviation (ARED), the sum of the squares of the errors (SSE), and the standard deviation of residuals (Sres). The results showed that, both Freundlich equation and pseudo-first-order equation provide the best fit to experimental data. Adsorption isotherm data appeared to be accurately described by a Freundlich model. The thermodynamic parameters (∆G, ∆H, and ∆S) showed that the process was feasible, spontaneous, and exothermic.

Research paper thumbnail of Prediction of Acute Herbicide Toxicity in Rats from Quantitative Structure–Activity Relationship Modeling

Environmental Engineering Science, 2014

Extensive use of herbicides raises concerns about adverse effects on the environment. Studies on ... more Extensive use of herbicides raises concerns about adverse effects on the environment. Studies on toxicity of herbicides are few and relatively old. The purpose of this study was to use multiple linear regressions (MLR) and Multilayered Perceptron artificial neural networks (MLP-ANN) to predict the oral acute toxicity (halfmaximal lethal dose [LD 50 ]) of a diverse set of 62 herbicides on rats. Quantitative structure-activity relationship (QSAR) models obtained by using relevant descriptors showed good predictability. Primary contributions to toxicity were the following descriptors: HATS0m, HATSe, and nS. Comparison of results obtained using the MLP-ANN model with those from the MLR model revealed the superiority of the MLP-ANN model. Statistics for prediction of oral acute toxicity for MLR and MLP-ANN were, respectively: R 2 = 0.855, RMSE = 0.270; and R 2 = 0.960, RMSE = 0.118. Comparison of validation results with those of other studies have shown the superiority of the model developed in this work.

Research paper thumbnail of Mass transfer modelling of the extraction of antibiotics from aqueous solution using Biosurfactants

Le Centre pour la Communication Scientifique Directe - HAL - Archive ouverte HAL, 2019

The objective of this work is to modelling a new separation technique based on the removal of ant... more The objective of this work is to modelling a new separation technique based on the removal of antibiotics such as amoxicillin and ampicillin produced by antibiotical company Saidal Médéa (Algeria) from pharmaceutical effluents using biosurfactants and commercial surfactants. The kinetic distribution of amoxicillin and ampicillin between the two phases was modelled in order to well understand the mechanism governing the direct transfer of antibiotics from the aqueous phase to the micellar phase. The results were interpreted in terms of a two-film theory for flat interface. The model of the kinetic transfer developed in this study provides excellent predictions. A very good correlation between predicted and experimental values was found : R2 = 0.98 for the sorption onto biosurfactant and R2 = 0.99 onto a synthetic surfactant. The model coefficients were used to estimate the overall combined mass transfer coefficient and the individual mass transfer coefficients.

Research paper thumbnail of Synthesis and characterization of activated carbon from asphalt

Applied Surface Science, 2006

Asphalt (cheap and available in huge amount in Jordan) was converted into activated carbon powder... more Asphalt (cheap and available in huge amount in Jordan) was converted into activated carbon powder by chemical treatment with sulphuric and nitric acids at 450°C. The final product was characterized and found effective as adsorbent material. Its cation exchange capacity reaches 191.2meq/100-g carbons when treated with 30wt% acid/asphalt ratio without airflow rate injection and 208meq/100-g carbons when 6.5ml air/min was

Research paper thumbnail of Batch kinetics and modelling of Pleuromutilin production by Pleurotus mutilis

Biochemical Engineering Journal, 2007

Research paper thumbnail of Optimization and modelling of the analysis of pleuromutilin antibiotic extracted from biomass

Asian Journal of Chemistry, 2010

Research paper thumbnail of Preventive Activity of Giner (Zingiber officinale) Against Myelotoxicity and Hepatotoxicity Induced by Cyclohexatriene and Identification of the Most Active Compounds by GC-MS

Kemija u industriji, 2021

This study aimed to uncover the preventive capability of Zingiber officinale against myelotoxicit... more This study aimed to uncover the preventive capability of Zingiber officinale against myelotoxicity, leukaemia, and hepatotoxicity. For the most part, this work depended on the subcutaneous injection of cyclohexatriene in rabbits to cause the illness by a synthetic strategy. In parallel, another group of rabbits was exposed to the injection of cyclohexatriene under similar conditions with the feeding Zingiber officinale, where it was discovered that the cyclohexatriene-induced myelotoxicity was counteracted. The histological examination additionally uncovered the hepato-defensive intensity of Zingiber officinale. The most pharmacologically active molecules of Zingiber officinale were recognised by gas chromatography–mass spectrometry (GC-MS).

Research paper thumbnail of QSAR Approaches and Ecotoxicological Risk Assessment

Hundreds of thousands of chemicals that can affect human health or the quality of aquatic and ter... more Hundreds of thousands of chemicals that can affect human health or the quality of aquatic and terrestrial ecosystems are introduced directly or indirectly into the air, water, or soil. Therefore, the awareness of the serious and harmful effects caused by these chemical compounds has revealed the absolute and compelling need to resort to the evaluation of potential risks incurred as a result of exposure to these compounds. In the aim to provide a high level of protection for human, animal, and environmental health, many regulatory agencies have established strict legislation for both toxicological and ecotoxicological risk assessments of existing and new chemical compounds. To limit the in vivo experiments which are a tedious and costly practice and generate a large sacrifice of animals, the REACH regulation recommends the use of in silico methods, such as quantitative structure-activity relationship (QSAR) models.