Response surface methodological (RSM) approach for optimizing the removal of trihalomethanes (THMs) and its precursor's by surfactant modified magnetic nanoadsorbents (sMNP) - An endeavor to diminish probable cancer risk

Optimizing the extract yield of bioactive compounds in Valeriana officinalis root: a D-optimal design

It is estimated that 80% of all synthetic drugs are derived from medicinal plants, and nowadays, many synthetic drugs are derived from medicinal plants. Valeriana officinalis can treat many diseases of the nervous system. A crucial aspect of valerian extract is that it inhibits the proliferation of breast cancer cells. To optimize the yield of bioactive compounds in the V. officinalis root extraction, a response surface methodology-based D-optimal design was used. To fulfill this aim, the effects of various factors such as solvent type and concentration, mixing temperature, ultrasound time, and drying method were examined. The optimal conditions for solvent percentages, mixing temperature, ultrasound time, solvent type, and drying methods were determined to be 94.88%, 25 °C, 48.95 min, methanol, and microwave, respectively, with a desirability of 0.921. The predicted valerenic acid, total phenols, total flavonoids, and antioxidant activity in V. officinalis extract were 1.19 (mg/g DW), 8.22 (mg/g DW), 5.27 (mg/g DW), and 92.64%, respectively. In optimal conditions, the extracted amounts of valerenic acid, total phenols, total flavonoids, and antioxidant activity were 2.07 mg/g DW, 7.96 mg/g DW, 5.52 mg/g DW, and 78.68%, respectively, which were consistent with the model predicted amounts (based on 95% prediction interval). This study could be useful as a model for demonstrating the efficacy of microwave drying to maximize the biochemical content of V. officinalis, as well as the antioxidant activity of the root extracts of V. officinalis on industrial scale.

Optimization of Production Parameters for Fabrication of Gum Arabic/Whey Protein-Based Walnut Oil Loaded Nanoparticles and Their Characterization

The encapsulation of fatty acids, including walnut oil, within complexes is a promising strategy to address challenges, for instance, low water solubility and susceptibility to oxidation while incorporating these oils into food products. Additionally, encapsulation can effectively mask undesirable odor and flavor. The current study focuses on the optimization of walnut oil nanoparticles (WON) using complexes fabricated from gum arabic and whey protein by applying a response surface methodology. The impact of three different independent variables were determined, such as surfactant mixture (33-66%), walnut oil (5-25%), and sonication time (60-300 s), under three distinct desired conditions (low, medium, and high) on four different responses, i.e., particle size, polydispersity index (PDI), moisture level, and encapsulation efficiency (EE). The findings of the present study indicate that the point prediction-based WON resulted in significantly low particle size (82.94 nm), PDI (0.19), moisture content (3.49%), and high EE (77.26%). Fourier transform infrared spectroscopy (FTIR) study demonstrated the successful encapsulation of walnut oil and wall material into nanocapsules. Differential scanning calorimetry (DSC) verified the improved thermal stability property of WON after incorporation, and scanning electron microscopy (SEM) indicated that the WON had relatively fragile and smooth surfaces, along with the presence of few porous structures. The recorded experimental data from the existing study showed that the developed formulation of WON was potentially useful as a value-added ingredient for food industries.

QbD Based Formulation Development and Optimisation of Ozenoxacin Topical Nano-Emulgel and Efficacy Evaluation Using Impetigo Mice Model

To formulate and optimize Ozenoxacin nano-emulsion using Quality by Design (QbD) concept by means of Box-Behnken Design (BBD) and converting it to a gel to form Ozenoxacin nano-emulgel followed by physico-chemical, in-vitro, ex-vivo and in-vivo evaluation. This study demonstrates the application of QbD methodology for the development and optimization of an effective topical nanoemulgel formulation for the treatment of Impetigo focusing on the selection of appropriate excipients, optimization of formulation and process variables, and characterization of critical quality attributes. BBD was used to study the effect of "% of oil, % of Smix and homogenization speed" on critical quality attributes "globule size and % entrapment efficiency" for the optimisation of Ozenoxacin Nano-emulsion. Ozenoxacin loaded nano-emulgel was characterized for "description, identification, pH, specific gravity, amplitude sweep, viscosity, assay, organic impurities, antimicrobial effectiveness testing, in-vitro release testing, ex-vivo permeation testing, skin retention and in-vivo anti-bacterial activity". In-vitro release and ex-vivo permeation, skin retention and in-vivo anti-bacterial activity were found to be significantly (p < 0.01) higher for the nano-emulgel formulation compared to the innovator formulation (OZANEX™). Antimicrobial effectiveness testing was performed and found that even at 70% label claim of benzoic acid is effective to inhibit microbial growth in the drug product. The systematic application of QbD principles facilitated the successful development and optimization of a Ozenoxacin Nano-Emulsion. Optimised Ozenoxacin Nano-Emulgel can be considered as an effective alternative and found to be stable at least for 6 months at 40 °C / 75% RH and 30 °C / 75% RH.

Production of hydrogen-rich fuel gas from waste plastics using continuous plasma pyrolysis reactor

There is a serious concern about the large amount of accumulated plastic waste all around the world. Synthetic polymers such as polyethylene terephthalate (PET), polypropylene (PP), and polyethylene (HDPE, LDPE) are substantially present in the plastic waste generated. There are various methods reported to minimise such plastics waste with certain limitations. To overcome such limitations the present study have been carried out in which thermal decomposition of plastic waste of PET, PP, HDPE, and LDPE studied using a novel plasma pyrolysis reactor. The major objective of this work is to investigate the viability of the continuous plasma pyrolysis process for the treatment of various plastic wastes with respect to waste volume reduction and production of combustible hydrogen-rich fuel gas. The effect of temperature and feed flow rate on product gas yield, product gas efficiency, solid residue yield, and H2/CO ratio has been evaluated. The experiments have been carried out at different temperatures within the range of 700-1000 °C. Plasma pyrolysis system exhibited combustible hydrogen-rich gas as a product and solid residue. Liquid products have not been observed during plasma pyrolysis, unlike conventional pyrolysis. The reaction mechanism of plastic cracking has been discussed based on literature and products obtained in the present work. The effects of feed flow rate and temperature on exergy efficiency were studied using the response surface method. The mass, energy, and exergy analyses have also been carried out for all the experiments, which are in the range of 0.95-0.99, 0.48 to 0.77, and 0.30 to 0.69, respectively.

Reclamation of iron and copper from BCL slag in Botswana

High-grade copper ores have been depleted over the years, making it a challenge in the mining industry. This investigation focused on a methodology to recover iron (Fe) and copper (Cu) from a copper/nickel slag obtained from the Bamangwato Concession Limited (BCL) mine in Botswana. In this modified flotation approach, the Response Surface Methodology (RSM) was used in conjunction with the Central Composite Design (CCD) and Analysis of Variance (ANOVA) to obtain the best optimal flotation conditions for the recovery of iron and copper. Using the RSM - CCD methodology, the optimal predicted responses were illustrated by a coefficient of determination R2 = 0. 9839 for recovery for Fe and 0.9655 for recovery for Cu. The recovery of copper increased with the increasing dosage of Na2S and collector dosage, while the increase of pH, had a decrease in recovery of copper due to the decline in the stability of the froth, which led to the resistance to form stable bubbles for efficient recovery of copper. Selective flotation of copper and iron was achieved by varying the Na2S dosage to achieve maximum recovery. Under these flotation conditions of PAX (800 g/t), pH (8), -75 μm, sulfurizing agent (Na2S, 1000 g/t), flotation time of 8 min, pH regulator of NaOH and H 2 S O 4 and Methyl Isobutyl Carbinol (MIBC) from the experimental runs merited a grade upgrade of Cu in froth concentrate from 0.581 mass% to 0.884 mass%. An enrichment ratio of 2 was realised, with the recovery of Cu being 62%, whereas Fe in the froth concentrate increased from 69.8 mass% to 71.8 mass%. The main aim was to upgrade the grade and recovery of copper and iron to enhance the recovery for copper and iron in the next experimental stage of leaching.

Production of iron enriched Saccharomyces boulardii: impact of process variables

About half of the 1.62 billion cases of anemia are because of poor diet and iron deficiency. Currently, the use of iron-enriched yeasts can be used as the most effective and possible way to prevent and treat anemia due to the ability of biotransformation of mineral compounds into the organic form. In this research, for the first time, Saccharomyces (S.) boulardii was used for iron enrichment with the aim that the probiotic properties of yeast provide a potential iron supplement besides improving the bioavailability of iron. Also, due to its higher resistance than other Saccharomyces strains against stresses, it can protect iron against processing temperatures and stomach acidic-enzymatic conditions. So, the effect of three important variables, including concentration of iron, molasses and KH2PO4 on the growth and biotransformation of yeast was investigated by the Box-Behnken design (BBD). The best conditions occurred in 3 g/l KH2PO4, 20 g/l molasses and 12 mg/l FeSO4 with the highest biotransformation 27 mg Fe/g dry cell weight (DCW) and 6 g/l biomass weight. Such yeast can improve fermented products, provide potential supplement, and restore the lost iron of bread, which is a useful iron source, even for vegetarians-vegans and play an important role in manage with anemia. It is recommended that in future researches, attention should be paid to increasing the iron enrichment of yeast through permeabilizing the membrane and overcoming the structural barrier of the cell wall.

Optimization of Microwave-Assisted Extraction Process of Total Flavonoids from Salicornia bigelovii Torr. and Its Hepatoprotective Effect on Alcoholic Liver Injury Mice

The objective of this study was to determine the optimal extraction conditions for total flavonoids from S. bigelovii using microwave-assisted extraction and to analyze the protective effect of total flavonoids from S. bigelovii on alcoholic liver injury in mice. The optimization of the process conditions for the microwave-assisted extraction of total flavonoids from S. bigelovii was performed using response surface methodology, and an alcohol-induced acute liver injury model in mice was used to investigate the effects of different doses of total flavonoids (100 mg/kg, 200 mg/kg, and 400 mg/kg) on the levels and activities of serum alanine aminotransferase kits (ALT), glutamic oxaloacetic transaminase kits (AST), superoxide dismutase kits (SOD), glutathione peroxidase kits (GSH-Px), and malondialdehyde (MDA). We performed hematoxylin-eosin (H&E) staining analysis on pathological sections of mouse liver tissue, and qRT-PCR technology was used to detect the expression levels of the inflammatory factors IL-1 β, IL-6, and TNF-α. The results revealed that the optimal extraction process conditions for total flavonoids in S. bigelovii were a material-to-liquid ratio of 1:30 (g/mL), an ethanol concentration of 60%, an extraction temperature of 50 °C, an ultrasound power of 250 W, and a yield of 5.71 ± 0.28 mg/g. Previous studies have demonstrated that the flavonoids of S. bigelovii can significantly inhibit the levels of ALT and AST in the serum (p < 0.001), reduce MDA levels (p < 0.001), increase the activity of the antioxidant enzymes SOD and GSH-Px (p < 0.001), and inhibit the IL-1 β, IL-6, and TNF-α gene expression levels (p < 0.001) of inflammatory factors. The total flavonoids of S. bigelovii exert a protective effect against alcoholic liver injury by reducing the levels of inflammation, oxidative stress, and lipid peroxidation caused by alcohol. The results of this study lay the foundation for the high-value utilization of S. bigelovii and provide new resources for the development of liver-protective drugs.

Optimization of atmospheric leaching parameters for cadmium and zinc recovery from low-grade waste by response surface methodology (RSM)

This study is focused on the optimization of effective parameters on Cadmium and Zinc recovery by atmospheric acid leaching of low-grade waste by response surface methodology (RSM) and using the Central Composite Design (CCD) method. The effects of parameters including time (0.5-2.5 h), temperature (40-80 °C), solid/liquid (S/L) (0.05-0.09 g/cc), particle size (174-44 mic), oxygen injection (0-1%) and pH (0.5-4.5) were statistically investigated at 5 surfaces. The sample of low-grade waste used in this study was mainly zinc factory waste. Two quadratic models for the correlation of independent parameters for the maximum recovery were proposed. The properties of waste were evaluated by X-ray diffraction (XRD) and X-ray fluorescence (XRF). Atomic absorption spectroscopy was used to determine the amount of Cadmium and Zinc in the leaching solution. The correlation coefficient (R2) for the predicted and experimental data of Cadmium and Zinc are 0.9837 and 0.9368, respectively. Time, S/L and size were the most effective parameters for the recovery efficiency of cadmium and zinc. 75.05% of Cadmium and 86.13% of Zinc were recovered in optimal conditions of leaching: S/L 0.08, pH 2.5, size 88 µm, 70 °C and 2.5 h. with air injection.

Synergistic photocatalytic effect of α-Fe2O3-ZnO binary nanocatalyst toward methylene blue: An experimental design study

Due to the potential ecosystem protection and management applications, searching for highly optimized semiconductor-based solar energy photocatalysts is still a significant challenge. Coupled α-Fe2O3-ZnO nanoparticles were prepared in situ and characterized by various identification techniques such as XRD, SEM-EDX, TEM, DRS, and FT-IR. Its pHpzc was about 8.1. The band gap energies of ZnO, α-Fe2O3, and the coupled α-Fe2O3-ZnO system were 3.22, 2.08, and 2.09 eV, respectively. The boosted photocatalytic activity of the coupled catalysts was designed via the RSM approach, and the optimal RSM conditions were pH 5, 25 min irradiation time, and 0.3 g/L of the α-Fe2O3-ZnO containing 75 % ZnO. The center point conditions' run included 0.5 g/L of the coupled catalyst containing 50 % ZnO, pH 7, and 22.5 min illumination time. The study on scavenger agents showed the highest role of hydroxyl radicals in MB photodegradation by the proposed catalyst.

Using design of experiments to guide genetic optimization of engineered metabolic pathways

Design of experiments (DoE) is a term used to describe the application of statistical approaches to interrogate the impact of many variables on the performance of a multivariate system. It is commonly used for process optimization in fields such as chemical engineering and material science. Recent advances in the ability to quantitatively control the expression of genes in biological systems open up the possibility to apply DoE for genetic optimization. In this review targeted to genetic and metabolic engineers, we introduce several approaches in DoE at a high level and describe instances wherein these were applied to interrogate or optimize engineered genetic systems. We discuss the challenges of applying DoE and propose strategies to mitigate these challenges.

ONE-SENTENCE SUMMARY

This is a review of literature related to applying Design of Experiments for genetic optimization.

Synthesis of tapioca starch/palm oil encapsulated urea-impregnated biochar derived from peppercorn waste as a sustainable controlled-release fertilizer

Nutrient leaching and volatilization cause environmental pollution, thus the pursuit of developing controlled-release fertilizer formulation is necessary. Biochar-based fertilizer exhibits slow-release characteristic, however the nutrient release mechanism needs to be improved. To overcome this limitation, the approach of applying encapsulation technology with biochar-based fertilizer has been implemented in this study. Black peppercorn waste was used to synthesize urea-impregnated biochar (UIB). Central composite design was used to investigate the effects of pyrolysis temperature, residence time and urea:biochar ratio on nitrogen content of UIB. The optimum condition to synthesize UIB was at 400 °C pyrolysis temperature, 120 min residence time and 0.6:1 urea:biochar ratio, which resulted in 16.07% nitrogen content. The tapioca starch/palm oil (PO) biofilm formulated using 8 g of tapioca starch and 0.12 µL of PO was coated on the UIB to produce encapsulated urea-impregnated biochar (EUIB). The UIB and EUIB pellets achieved complete release of nitrogen in water after 90 min and 330 min, respectively. The nutrient release mechanism of UIB and EUIB was best described by the Higuchi model and Korsmeyer-Peppas model, respectively. The improvement of water retention ratio of UIB and EUIB pellets was more significant in sandy-textural soil as compared to clayey-textural soil. The EUIB derived from peppercorn waste has the potential to be utilized as a sustainable controlled-release fertilizer for agriculture.

Enhancing uric acid electrochemical detection with copper ion-activated mini protein mimicking uricase within ZIF-8: response surface methodology (RSM) optimization

This study aims to investigate the influence of copper(II) ions as a cofactor on the electrochemical performance of a biocomposite consisting of a mini protein mimicking uricase (mp20) and zeolitic immidazolate framework-8 (ZIF-8) for the detection of uric acid. A central composite design (CCD) was utilized to optimize the independent investigation, including pH, deposition potential, and deposition time, while the current response resulting from the electrocatalytic oxidation of uric acid was used as the response. The statistical analysis of variance (ANOVA) showed a good correlation between the experimental and predicted data, with a residual standard error percentage (RSE%) of less than 2% for predicting optimal conditions. The synergistic effect of the nanoporous ZIF-8 host, Cu(II)-activated mp20, and reduced graphene oxide (rGO) layer resulted in a highly sensitive biosensor with a limit of detection (LOD) of 0.21 μM and a reproducibility of the response (RSD = 0.63%). The Cu(II)-activated mp20@ZIF-8/rGO/SPCE was highly selective in the presence of common interferents, and the fabricated layer exhibited remarkable stability with signal changes below 4.15% after 60 days. The biosensor's reliable performance was confirmed through real sample analyses of human serum and urine, with comparable recovery values to conventional HPLC.

Design of Experiment for Optimizing Microencapsulation by the Solvent Evaporation Technique

We employed microemulsion combined with the solvent evaporation technique to produce biodegradable polycaprolactone (PCL) MCs, containing encapsulated isophorone diisocyanate (IPDI), to act as crosslinkers in high-performance adhesive formulations. The MC production process was optimized by applying a design of experiment (DoE) statistical approach, aimed at decreasing the MCs' average size. For that, three different factors were considered, namely the concentration of two emulsifiers, polyvinyl alcohol (PVA) and gum arabic (GA); and the oil-to-water phase ratio of the emulsion. The significance of each factor was evaluated, and a predictive model was developed. We were able to decrease the average MC size from 326 μm to 70 µm, maintaining a high encapsulation yield of approximately 60% of the MCs' weight, and a very satisfactory shelf life. The MCs' average size optimization enabled us to obtain an improved distributive and dispersive mixture of isocyanate-loaded MCs at the adhesive bond. The MCs' suitability as crosslinkers for footwear adhesives was assessed following industry standards. Peel tests revealed peel strength values above the minimum required for casual footwear, while the creep test results indicated an effective crosslinking of the adhesive. These results confirm the ability of the MCs to release IPDI during the adhesion process and act as crosslinkers for new adhesive formulations.

Effect of Sulfide and Chloride Ions on Pitting Corrosion of Type 316 Austenitic Stainless Steel in Groundwater Conditions Using Response Surface Methodology

This study investigates the corrosion resistance of Type 316 stainless steel as a candidate material for radioactive waste disposal canisters. The viability of stainless steel is examined under groundwater conditions with variations in pH, bisulfide ions (HS-), and chloride ions (Cl-) concentrations. Utilizing response surface methodology, correlations between corrosion factors and two crucial response variables, passive film breakdown potential and protection potential, are established. Cyclic potentiodynamic polarization tests and advanced analytical techniques provide detailed insights into the material's behavior. This research goes beyond, deriving an equation through response surface methodology that elucidates the relationship between the factors and breakdown potential. HS- weakens the passive film and reduces the pitting corrosion resistance of the stainless steel. However, this study highlights the inhibitory effect of HS- on pitting corrosion when Cl- concentrations are below 0.001 M and at equivalent concentrations of HS-. Under these conditions, immediate re-passivation occurs from the destroyed passive film to metal sulfides such as FeS2, MoS2, and MoS3. As a result, no hysteresis loop occurs in the cyclic polarization curve in these conditions. This research contributes to the understanding of Type 316 stainless-steel corrosion behavior, offering implications for the disposal of radioactive waste in geological repositories.

Investigation of Biomaterial Ink Viscosity Properties and Optimization of the Printing Process Based on Pattern Path Planning

Extruded bioprinting is widely used for the biomanufacturing of personalized, complex tissue structures, which requires biomaterial inks with a certain viscosity to enable printing. However, there is still a lack of discussion on the controllable preparation and printability of biomaterial inks with different viscosities. In this paper, biomaterial inks composed of gelatin, sodium alginate, and methylcellulose were utablesed to investigate the feasibility of adjustment of rheological properties, thereby analyzing the effects of different rheological properties on the printing process. Based on the response surface methodology, the relationship between the material components and the rheological properties of biomaterial inks was discussed, followed by the prediction of the rheological properties of biomaterial inks. The prediction accuracies of the power-law index and consistency coefficient could reach 96% and 79%, respectively. The material group can be used to prepare biomaterial inks with different viscosity properties in a wide range. Latin hypercube sampling and computational fluid dynamics were used to analyze the effects of different rheological properties and extrusion pressure on the flow rate at the nozzle. The relationship between the rheological properties of the biomaterial ink and the flow rate was established, and the simulation results showed that the changes in the rheological properties of the biomaterial ink in the high-viscosity region resulted in slight fluctuations in the flow rate, implying that the printing process for high-viscosity biomaterial inks may have better versatility. In addition, based on the characteristics of biomaterial inks, the printing process was optimized from the planning of the print pattern to improve the location accuracy of the starting point, and the length accuracy of filaments can reach 99%. The effect of the overlap between the fill pattern and outer frame on the print quality was investigated to improve the surface quality of complex structures. Furthermore, low- and high-viscosity biomaterial inks were tested, and various printing protocols were discussed for improving printing efficiency or maintaining cell activity. This study provides feasible printing concepts for a wider range of biomaterials to meet the biological requirements of cell culture and tissue engineering.

Maximizing diesel removal from contaminated sand using Scirpus mucronatus and assessment of rhizobacteria addition effect

Phytoremediation is one of the green technologies that is friendly to nature, utilizes fewer chemicals, and exhibits good performance. In this study, phytoremediation was used to treat diesel-contaminated sand using a local aquatic plant species, Scirpus mucronatus, by analyzing the amount of total petroleum hydrocarbons (TPHs). Optimization of diesel removal was performed according to Response Surface Methodology (RSM) using Box-Behnken Design (BBD) under pilot-scale conditions. The quadratic model showed the best fit to describe the obtained data. Actual vs. predicted values from BBD showed a total of 9.1 % error for the concentration of TPH in sand and 0 % error for the concentration of TPH in plants. Maximum TPH removal of 42.3 ± 2.1 % was obtained under optimized conditions at a diesel initial concentration of 50 mg/kg, an aeration rate of 0.48 L/min, and a retention time of 72 days. The addition of two species of rhizobacteria (Bacillus subtilis and Bacillus licheniformis) at optimum conditions increased the TPH removal to 51.9 ± 2.6 %. The obtained model and optimum condition can be adopted to treat diesel-contaminated sand within the same TPH range (50-3000 mg/kg) in sand.

Optimisation of process parameters of a thermal digester for the rapid conversion of food waste into value-added soil conditioner

A novel thermal digester for converting food waste (FW) into nutrient-rich soil conditioner was designed and explored. The process variables, that is, temperature, the volume of the digestion chamber and the rotational speed of the digester were optimised using response surface methodology (RSM). The study revealed that the digester temperature of 150°C and rotational speed of 40 RPM required minimum time (180 minutes) for attaining the equilibrium moisture with a minimum energy consumption of 0.218 kWh kg-1. The process resulted in 80 ± 2.5% reduction in total volume of the FW. Detailed characterisation revealed that the end product was comparable to the organic fertiliser as per the Fertiliser Association of India norms. The digestion helps in breakdown of cellulose content of FW into hemicellulose which supports formation of primary and secondary walls, seed storage carbohydrates, and facilitates plant growth. 1H-Nuclear magnetic resonance (1H-NMR) spectra of the end product revealed mineralisation of organics during digestion. Decrease in ultraviolet (UV) absorbance value at 280 nm also revealed the humification of the end product. X-ray diffraction (XRD) analysis disclosed extremely low crystallinity and non-recalcitrant nature of the end product. A low humification index value (HI-3.43), high fertilising index (FI-4.8), and clean index (CI-5.0) revealed that the end product could safely be utilised as an organic fertiliser. The cost-benefit analysis revealed that thermal digestion technique is profitable and economically viable with benefit-cost ratio (BCR) of 1.35. The study offers a unique approach for the rapid and hassle-free production of value-added soil conditioner from FW.

Domestic greywater treatment using electrocoagulation-electrooxidation process: optimisation and experimental approaches

A synergistic combination of electrocoagulation-electrooxidation (EC-EO) process was used in the current study to treat domestic greywater. The EC process consisted of an aluminium (Al) anode and an iron (Fe) cathode, and the EO process consisted of titanium with platinum coating mesh (Ti/Pt) as an anode and stainless steel as a cathode. The effect of operative variables, namely current density, pH, EC time and EO time, on the removal of chemical oxygen demand (COD), colour, turbidity, and total organic carbon (TOC) was studied and optimised using Response Surface Methodology (RSM). The results showed that although the pH affected the removal of all studied pollutants, it had more effect on turbidity removal with a contribution of 88.44%, while the current density had the main dominant effect on colour removal with a contribution of 73.59%. It was also found that at optimal operation conditions for a current density of 2.6 A, an initial pH of 4.67, an EC time of 31.67 min, and an EO time of 93.28 min led to a COD, colour, turbidity, and TOC removal rates of 96.1%, 97.5%, 90.9%, and 98%, respectively, which were close to the predicted results. The average operating cost and energy consumption for the removal of COD, colour, turbidity, and TOC were 0.014 $/m3 and 0.01 kWh/kg, 0.083 $/m3 and 0.008 kWh/kg, 0.075 $/m3 and 0.062 kWh/kg, and 0.105 $/m3 and 0.079 kWh/kg, respectively.

Response Surface Methodology Application for Bacteriophage-Antibiotic Antibiofilm Activity Optimization

Phage-antibiotic combination-based protocols are presently under heightened investigation. This paradigm extends to engagements with bacterial biofilms, necessitating novel computational approaches to comprehensively characterize and optimize the outcomes achievable via these combinations. This study aimed to explore the Response Surface Methodology (RSM) in optimizing the antibiofilm activity of bacteriophage-antibiotic combinations. We employ a combination of antibiotics (gentamicin, meropenem, amikacin, ceftazidime, fosfomycin, imipenem, and colistin) alongside the bacteriophage vB_AbaP_AGC01 to combat Acinetobacter baumannii biofilm. Based on the conducted biofilm challenge assays analyzed using the RSM, the optimal points of antibiofilm activity efficacy were effectively selected by applying this methodology, enabling the quantifiable mathematical representations. Subsequent optimization showed the synergistic potential of the anti-biofilm that arises when antibiotics are judiciously combined with the AGC01 bacteriophage, reducing biofilm biomass by up to 80% depending on the antibiotic used. The data suggest that the phage-imipenem combination demonstrates the highest efficacy, with an 88.74% reduction. Notably, the lower concentrations characterized by a high maximum reduction in biofilm biomass were observed in the phage-amikacin combination at cA = 0.00195 and cP = 0.38 as the option that required minimum resources. It is worth noting that only gentamicin antagonism between the phage and the antibiotic was detected.

Adsorption of ibuprofen using waste coffee derived carbon architecture: Experimental, kinetic modeling, statistical and bio-inspired optimization

Pharmaceuticals in water are a growing environmental concern, as they can harm aquatic life and human health. To address this issue, an adsorbent made from coffee waste that effectively removes ibuprofen (a common pharmaceutical pollutant) from wastewater was developed. The experimental adsorption phase was planned using a Design of Experiments approach with Box-Behnken strategy. The relation between the ibuprofen removal efficiency and various independent variables, including adsorbent weight (0.01-0.1 g) and pH (3-9), was evaluated via a regression model with 3-level and 4-factors using the Response surface methodology (RSM) . The optimal ibuprofen removal was achieved after 15 min using 0.1 g adsorbent at 32.4 °C and pH = 6.9. Moreover, the process was optimized using two powerful bio-inspired metaheuristics (Bacterial Foraging Optimization and Virus Optimization Algorithm). The adsorption kinetics, equilibrium, and thermodynamics of ibuprofen onto waste coffee-derived activated carbon were modeled at the identified optimal conditions. The Langmuir and Freundlich adsorption isotherms were implemented to investigate adsorption equilibrium, and thermodynamic parameters were also calculated. According to the Langmuir isotherm model, the adsorbent's maximum adsorption capacity was 350.00 mg g-1 at 35 °C. The findings revealed that the ibuprofen adsorption was well-matched with the Freundlich isotherm model, indicating multilayer adsorption on heterogeneous sites. The computed positive enthalpy value showed the endothermic nature of ibuprofen adsorption at the adsorbate interface.

Washing Bottom Sediment for The Removal of Arsenic from Contaminated Italian Coast

Among various forms of anthropogenic pollution, the release of toxic metals in the environment is a global concern due to the high toxicity of these metals towards living organisms. In the last 20 years, sediment washing has gained increasing attention thanks to its capability to remove toxic metals from contaminated matrices. In this paper, we propose a Response Surface Methodology method for the washing of selected marine sediments of the Bagnoli-Coroglio Bay (Campania region, Italy) polluted with arsenic and other contaminants. We focused our attention on different factors affecting the clean-up performance (i.e., liquid/solid ratio, chelating concentration, and reaction time). The highest As removal efficiency (i.e., >30 μg/g) was obtained at a liquid/solid ratio of 10:1 (v/w), a citric acid concentration of 1000 mM, and a washing time of 94.22 h. Based on these optimum results, ecotoxicological tests were performed and evaluated in two marine model species (i.e., Phaeodactylum tricornutum and Aliivibrio fischeri), which were exposed to the washing solutions. Reduced inhibition of the model species was observed after nutrient addition. Overall, this study provides an effective tool to quickly assess the optimum operating conditions to be set during the washing procedures of a broad range of marine sediments with similar physicochemical properties (i.e., grain size and type of pollution).

Drinking water treatment and associated toxic byproducts: Concurrence and urgence

Reclaimed water is highly required for environmental sustainability and to meet sustainable development goals (SDGs). Chemical processes are frequently associated with highly hazardous and toxic by-products, like nitrosamines, trihalomethanes, haloaldehydes, haloketones, and haloacetic acids. In this context, we aim to summarize the formation of various commonly produced disinfection by-products (DBPs) during wastewater treatment and their treatment approaches. Owing to DBPs formation, we discussed permissible limits, concentrations in various water systems reported globally, and their consequences on humans. While most reviews focus on DBPs detection methods, this review discusses factors affecting DBPs formation and critically reviews various remediation approaches, such as adsorption, reverse osmosis, nano/micro-filtration, UV treatment, ozonation, and advanced oxidation process. However, research in the detection of hazardous DBPs and their removal is quite at an early and initial stage, and therefore, numerous advancements are required prior to scale-up at commercial level. DBPs abatement in wastewater treatment approach should be considered. This review provides the baseline for optimizing DBPs formation and advancements in the remediation process, efficiently reducing their production and providing safe, clean drinking water. Future studies should focus on a more efficient and rigorous understanding of DBPs properties and degradation of hazardous pollutants using low-cost techniques in wastewater treatment.

The assessment of response surface methodology (RSM) and artificial neural network (ANN) modeling in dry flue gas desulfurization at low temperatures

The performance of a flue gas desulfurization (FGD) system is characterized by SO₂ removal efficiency (Y1) and reagent conversion (Y2). Achieving a near-perfect reaction environment has been of concern in dry FGD (DFGD) due to the low reactivity compared to the wet and semi-dry units. This study will appraise output responses using modeling by response surface methodology (RSM) and artificial neural networks (ANN) approaches. The impacts of input parameters like hydration time, hydration temperature, diatomite to hydrated lime (Ca(OH)₂), sulfation temperature and inlet gas concentration will be studied using a randomized central composite design (CCD). ANN fitting tool mapped the CCD metadata using the Levenberg-Marquardt (LM) algorithm activated by the hyperbolic tangent (tansig) function. The hidden cells ranged from 7 to 10 to ascertain the effect node architecture on modeling accuracy. Validation of each procedure was assessed using root mean square error (RMSE), mean square error (MSE) and R-Squared studies. The outcomes presented a more accurate 5-10-2 ANN model in the mapping of the DFGD from R² data of Y1 = 0.993 and Y2 = 0.9986 with a mapping deviation from the RMSE values of Y1 = 0.48465; Y2 = 0.44971 and MSE results of Y1 = 0.23488; Y2.= 0.20229.

Modeling and Optimization of Geraniol ((2E)-3,7-Dimethyl-2,6-Octadiene-l-ol) Transformation Process Using Response Surface Methodology (RSM)

This paper presents the modeling of the geraniol transformation process using response surface methodology (RSM). It uses a combination of both statistical and mathematical modeling methods to study the relationships occurring between several explanatory variables and one or more response variables. Interactions occurring between process variables are studied using statistical techniques. In this paper, the influence of the most important process parameters, such as temperature 20–110 °C, catalyst concentration (mironecuton) 1.0–5.0 (wt.%), and reaction time 0.25–2 (h), is presented. The response functions were the conversion of geraniol (GA), the selectivity of conversion to thumbergol (TH), and the selectivity of conversion to 6,11-dimethyl-2,6,10-dodecatriene-1-ol (DMC). In addition, the effects of all control parameters on each of the response parameters were presented in the form of second-order polynomials. Attempts were made to identify process conditions that would allow high values of the process function.

Develop a hybrid machine learning model for promoting microbe biomass production

Since the cultivation condition of microbe biomass production (mycelia yield) involves a variety of factors, it's a laborious process to obtain the optimal cultivation condition of Antrodia cinnamomea (A. cinnamomea). This study proposed a hybrid machine learning approach (i.e., ANFIS-NM) to identify the potent factors and optimize the cultivation conditions of A. cinnamomea based on a 32 fractional factorial design with seven factors. The results indicate that the ANFIS-NM approach successfully identified three key factors (i.e., glucose, potato dextrose broth, and agar) and significantly boosted mycelia yield. The interpretability of ANFIS rules made the cultivation conditions visually interpretable. Subsequently, a three-factor five-level central composite design was used to probe the optimal yield. This study demonstrates the proposed hybrid machine learning approach could significantly reduce the time consumption in laboratory cultivation and increase mycelia yield that meets SDGs 7 and 12, hitting a new milestone for biomass production.

Optimisation of process parameters using response surface methodology to improve the liquid fraction yield from pyrolysis of water hyacinth

The water hyacinth has been identified as a persistent threat to the pillars of sustainability, resulting in an increased demand for cost-effective mitigation measures. Existing control measures such as chemical and mechanical methods have proved ineffective and expensive, although their use in a biorefinery is deemed sustainable. The study focused on using the response surface methodology of Design-Expert to optimise process parameters, emphasising temperature and particle size, to improve the liquid fraction yield from the pyrolysis of water hyacinths. The experiment was conducted in the temperature range of 273.22 and 676.78 °C, with a particle size range of 380 and 2620 µm, and subjected to a heating rate of 30 °C/min and a nitrogen flow rate of 25 l/min. The results suggest that an increase in temperature and particle size led to a rise in the liquid fraction and a decrease in char. The liquid fraction increased from 24.36 wt.% at 273.22 °C to 48.45 wt.% at 575 °C and reduced to 25.56 wt.% at 626.78 °C. Char decreased from 58.21 to 33.84 wt.% at 626.78 °C. Given this, the quadratic model was found fit for optimisation. Statistical analysis of variance showed good agreement between actual data and the predicted model. This study argues that the valorisation of water hyacinths, if accompanied by policies and strategies, can trigger comprehensive socio-economic and environmental benefits by implementing optimum conditions to generate an improved liquid fraction that tends to influence its commercialisation. It is envisaged that the study's findings will inform policy discussions and formulation.

A sensitivity analysis of MHD nanofluid flow across an exponentially stretched surface with non-uniform heat flux by response surface methodology

The current study investigates the MHD flow of nanofluid across an elongating surface while taking into account non-uniform heat flux. For this, we have considered the flow of a boundary layer over a stretched sheet containing (water-based) Al₂O₃ nanoparticles. The convective boundary conditions for temperature have been invoked. The flow created by a surface that is exponentially expanding in the presence of a magnetic field and a non-uniform heat flux has been mathematically formulated by using laws of conservation. Transformed non-dimensional systems of governing equations have been analyzed numerically by using Adam’s Bashforth predictor corrector approach. The effects of emerging parameters on the fluid velocity and temperature profiles have been further described by plotting graphs. An experimental design and a sensitivity analysis based on Response Surface Methodology (RSM) are used to examine the effects of various physical factors and the dependence of the response factors of interest on the change of the input parameter. To establish the model dependencies of the output response variables, which include the skin friction coefficient and the local Nusselt number, on the independent input parameters, which include the magnetic field parameter, the nanoparticle volume fraction, and the heat transfer Biot number, RSM is used. On the basis of statistical measures such as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Q - Q$$\end{document}Q-Q residual plots, adjusted and hypothesis testing using p values, it is observed that both of our models for Skin Friction Coefficient (SFC) and the Local Nusselt Number (LNN) are best fitted. Further, it is concluded that the sensitivity of the SFC, as well as the LNN through heat transfer Biot number, is greater than that of nanoparticle volume fraction and magnetic field parameter. The SFC is sensitive to all combinations of the input parameters. At high levels of heat transfer Biot number, the LNN displays negative sensitivity via magnetic field parameters.

Electrocoagulation of Corrugated Box Industrial Effluents and Optimization by Response Surface Methodology

The electrocoagulation method using stainless steel anodes was applied to a corrugated cardboard box manufacturing plant's wastewater with high COD content. The effects of current density, processing time and stirring speed on response functions were studied using the Response Surface Methodology (RSM). The removal efficiency of chemical oxygen demand (COD) and energy consumption were selected as response functions. The Central Composite Design (CCD) was chosen to explain the single and combined effects of independent variables on response functions. The COD concentration of the real industrial wastewater used in the experiments was 9130 mg L-1. The maximum COD removal efficiency of 91.6% is obtained with 19.78 Wh g-1 energy consumption. Current density and treatment time were effective parameters for both COD removal and energy consumption. Optimization for maximum COD removal with minimum energy consumption showed 80.9% of COD removal with 6.7 Wh g-1 of energy consumption at 15 mA cm-2, 700 rpm, and 28 min treatment time. The variables are optimized with a few experiments using the response surface method.

Graphical abstract

Performance study of fly-ash-derived coagulant in removing natural organic matter from drinking water: synthesis, characterization, and modelling

This study is an attempt to develop a liquid coagulant using fly ash (FAC) for removing natural organic matter (NOM) from drinking water systems. Acid-alkali leaching and polymerization technique was used for developing FAC. Characterization of FAC was performed using Fourier-transform infrared spectroscopy (FESEM), field emission scanning electron microscopy (FTIR), and X-ray diffraction (XRD) to assess the surface morphology and functional groups present. FE SEM analysis revealed uneven, coarse, and irregular structure with numerous pores, an indicative of their high adsorption capacity. XRD study revealed that Al, Fe, and Si are the major constituent group of FAC. FAC demonstrated excellent potential in removing THMs precursors: dissolved organic carbon (84.46%), UV₂₅₄ (90.57%), and turbidity (96.85%) from the drinking water systems. Charge neutralization followed by adsorption is the main mechanism behind NOM removal. Moreover, FAC also showed good capability in minimizing the reactivity of NOM (ASI-72.86%) towards THM formation. FAC proved to be a good alternative for conventional coagulant used in drinking water treatment and can be effectively used for reducing NOM content of raw water which leads to the formation of THMs on chlorination.

Bio-fabricated silver nanoparticles for controlling dengue and filaria vectors and their characterization, as well as toxicological risk assessment in aquatic mesocosms

The present study is focused on synthesis of silver nanoparticles from weeds and an assessment of their mosquito larvicidal efficacy. This study also presented the toxicological effects as well as the stability of these nanoparticles in aquatic mesocosms. The weed Digiteria sanguinallis was first time used for the synthesis of silver nanoparticles. The synthesized nanoparticles were characterized by various analytical techniques, such as UV-VIS, TEM, FESEM, EDX, XRD, FTIR, and zeta potential study. The result revealed that the nanoparticles are crystalline, spherical shape with band gap 2.44 eV, and average size 18 nm. The LC₅₀ value of synthesized AgNPs were recorded as 7.47 and 6.31 mg/L at 24 h against Cx. quinquefasciatus and A. albopictus respectively. In contrast, larvicidal activity of weed extract was insignificant against two target species. In aquatic mesocosm study, AgNPs (LC₅₀ dose) does not alter the nature of water parameters within experimental period. However only EC % and ORP were changes because of silver ion oxidation. In biochemical parameters, only stress enzymes for animal and plant species were moderately altered under long term exposure. But glycogen, protein, and AchE of two mosquito species were significantly changed under same mesocosm setup within short exposure. Comparatively, in control mesocosm, synthesized AgNPs are naturally change their nano form within 20 days with the presence of all non-target species and pond sediment. Therefore, it can be concluded that biosynthesized AgNPs could be used as a larvicidal agent in near future with negligible effects on aquatic organisms.

Using chemometric models to predict the biosorption of low levels of dysprosium by Euglena gracilis

The critical rare earth element dysprosium (Dy) is integral for sustainable technologies. What is concerning is that Dy is in imminent short supply and no current replacements yet exist, coupled with increasing environmental Dy levels influenced by anthropogenic activities. This study applies chemometric methods such as response surface methodology and artificial neural networks to predict low Dy removal levels using the biosorbent Euglena gracilis. A three-factor Box-Behnken experimental design was conducted with initial concentration (1 to 100 µg L^-1), contact time (30 to 180 min), and pH (3 to 8) as the three independent variables, and percentage removal and sorption capacity (q) as dependent variables. Using Dy percentage removal as response, for the worst and best conditions ranged from 0 to 92% respectively, with an average removal of 66 ± 4%. Using sorption capacity (q) as a different response variable, q varied from 0 to 93 µg/g with 27 ± 4 µg/g capacity as average. Maximum removal was 92% (q = 93 µg/g) was at pH 3, a contact time of 105 min and at a concentration of 100 µg/L. Using sorption capacity as the response variable for ANOVA, pH and metal concentrations were statistically significant factors, with lower pH and higher metal concentration having improved Dy removal, with a desirability near 1. Statistical tests such as analysis of variance, lack-of-fit, and coefficient of determination (R²) confirmed model validity. A 3-10-1 ANN network array was used to model experimental responses (q). RSM and ANN effectively modeled Dy biosorption. E. gracilis proved to be a cheap and effective biosorbent for Dy biosorption and has the potential to remediate acid mine drainage areas exhibiting low Dy concentrations.

Comparative Study of Chemical Coagulation and Electrocoagulation for the Treatment of Real Textile Wastewater: Optimization and Operating Cost Estimation

Pollutants derived from real textile wastewater present a high environmental risk. This work involves the study of the removal of chemical oxygen demand (COD), color, and turbidity from Tunisian real textile wastewater by two different water treatment technologies: chemical coagulation (CC) and electrocoagulation (EC). A comparative study between these two methods was conducted based on the separation performance and operating cost (OC). The effects of different operational parameters including electrolysis time (t), voltage, and pH for EC and the coagulant concentration, initial pH, and time of slow mixing (t _sm) for CC were studied using response surface methodology. The developed quadratic models for the responses were in good agreement with the experimental data. The experiments proved the efficiency of both chemical and electrochemical techniques for the treatment of textile effluent. Indeed, by using EC, the reduction efficiencies of COD, color, and turbidity were 63.05, 99.07, and 96.31%, respectively, under optimal conditions (pH 9, t = 36.26 min, and voltage 4 V). For CC treatment, the achieved removal efficiencies of COD, color, and turbidity were 54.02, 96.21, and 93.7%, respectively, at pH 8.57, a coagulant concentration of 204.75 mg/L, and a t _sm of 28.41 min as optimal operating conditions. The OC obtained for EC and CC was about 0.47 and 0.2 USD/m³, respectively. Even if the OC of the EC process was higher as compared to the CC process, the treated water obtained by EC meets the Tunisian Standards (NT 106.03 and NT 09-14) for textile wastewater discharge into the environment and demonstrates a high potential for its reuse in various industrial activities. EC technology can be integrated into a wastewater management system that ensures a zero liquid discharge of wastewater into the environment.

OsbHLHq11, the Basic Helix-Loop-Helix Transcription Factor, Involved in Regulation of Chlorophyll Content in Rice

Photosynthesis is an important factor in determining the yield of rice. In particular, the size and efficiency of the photosynthetic system after the heading has a great impact on the yield. Research related to high-efficiency photosynthesis is essential to meet the growing demands of crops for the growing population. Chlorophyll is a key molecule in photosynthesis, a pigment that acts as an antenna to absorb light energy. Improvement of chlorophyll content characteristics has been emphasized in rice breeding for several decades. It is expected that an increase in chlorophyll content may increase photosynthetic efficiency, and understanding the genetic basis involved is important. In this study, we measured leaf color (CIELAB), chlorophyll content (SPAD), and chlorophyll fluorescence, and quantitative trait loci (QTL) mapping was performed using 120 Cheongcheong/Nagdong double haploid (CNDH) line after the heading date. A major QTL related to chlorophyll content was detected in the RM26981-RM287 region of chromosome 11. OsbHLHq11 was finally selected through screening of genes related to chlorophyll content in the RM26981-RM287 region. The relative expression level of the gene of OsbHLHq11 was highly expressed in cultivars with low chlorophyll content, and is expected to have a similar function to BHLH62 of the Gramineae genus. OsbHLHq11 is expected to increase photosynthetic efficiency by being involved in the chlorophyll content, and is expected to be utilized as a new genetic resource for breeding high-yield rice.

Effect of pine essential oil and rotating magnetic field on antimicrobial performance

This work presents the results ofa study which concerns the influence of rotating magnetic field (RMF) on the antibacterial performance of commercial pine essential oil. A suspension of essential oil in saline solution and Escherichia coli were exposed to the rotating magnetic Afield (the frequency of electrical current supplied by a RMF generator f = 1–50 Hz; the averaged values of magnetic induction in the cross-section of the RMF generator B = 13.13 to − 19.92 mT, time of exposure t = 160 min, temperature of incubation 37 °C). The chemical composition of pine (Pinus sylvestris L.) essential oil was determined by gas chromatography coupled with mass spectrometry (GC–MS). The main constituents were α-pinene (28.58%), β-pinene (17.79%), δ-3-carene (14.17%) and limonene (11.58%). The present study indicates the exposition to the RMF, as compared to the unexposed controls causing an increase in the efficacy of antibacterial properties of pine oil. We have shown that rotating magnetic fields (RMF) at a frequency, f, between 25 Hz to and 50 Hz increased the antimicrobial efficiency of oil a concentration lower than 50%.

Applicability of bio-synthesized nanoparticles in fungal secondary metabolites products and plant extracts for eliminating antibiotic-resistant bacteria risks in non-clinical environments

The abundance of antibiotic-resistant bacteria in the prawn pond effluents can substantially impact the natural environment. The settlement ponds, which are the most common treatment method for farms wastewater, might effectively reduce the suspended solids and organic matter. However, the method is insufficient for bacterial inactivation. The current paper seeks to highlight the environmental issue associated with the distribution of antibiotic resistant bacteria (ARB) from prawn farm wastewater and their impact on the microbial complex community in the surface water which receiving these wastes. The inactivation of antibiotic-resistant bacteria in prawn wastewater is strongly recommended because the presence of antibiotic-resistant bacteria in the environment causes water pollution and public health issues. The nanoparticles are more efficient for bacterial inactivation. They are widely accepted due to their high chemical and mechanical stability, broad spectrum of radiation absorption, high catalytic activity, and high antimicrobial activity. Many studies have examined the use of fungi or plants extract to synthesis zinc oxide nanoparticles (ZnO NPs). It is evident from recent papers in the literature that green synthesized ZnO NPs from microbes and plant extracts are non-toxic and effective. ZnO NPs inactivate the bacterial cells as a function for releasing reactive oxygen species (ROS) and zinc ions. The inactivation of antibiotic-resistant bacteria tends to be more than 90% which exhibit strong antimicrobial behavior against bacterial species.

Optimized Roasting Conditions of Germinated Wheat for a Novel Cereal Beverage and Its Sensory Properties

The objective of this study was to investigate the possibility of using germinated wheat as a nutritionally improved novel cereal beverage. To enhance the health-related functionality of a germinated wheat beverage (GWB), the roasting time and temperature of germinated wheat were optimized using a central composite design and response surface methodology. The optimum roasting conditions were determined as roasting temperature of 180 °C and roasting time of 44.56 min, resulting in maximum total flavonoid content (0.74 mg CE/g), total phenolic content (1.95 mg GE/g), 2,2-diphnyl-1-picrylhydrazyl (DPPH) radical scavenging activity (5.10 μM TE/g), Trolox equivalent antioxidant capacity (9.45 mM TE/g), and γ-aminobutyric acid content (2.25 mg/g). The germinated wheat roasted with optimum conditions was prepared in two types of GWB (hot and cold), and the sensory characteristics were tested by consumers (n = 102). The cold GWB showed relatively high preferences compared to hot GWB in appearance, odor, taste, and overall acceptabilities. In the intensity results of the sensory properties of GWB, the cold GWB tended to have stronger browning, grain odor, and nutty taste than the hot GWB. Conclusively, this study showed that optimizing the roasting conditions of germinated wheat could achieve desirable sensory properties and consumer acceptance while improving the health-related functionality of GWB.

Optimization of the extraction conditions of Nypa fruticans Wurmb. using response surface methodology and artificial neural network

In this study, we conducted response surface methodology (RSM) and artificial neural network (ANN) to predict and estimate the optimized extraction condition of Nypa fruticans Wurmb. (NF). The effect of ethanol concentration (X₁; 0-100%), extraction time (X₂; 6-24 h), and extraction temperature (X₃; 40-60 °C) on the antioxidant potential was confirmed. The optimal conditions (57.6% ethanol, 19.0 h extraction time, and 51.3 °C extraction temperature) of 2,2-diphenyl-1-1picrylhydrazyl (DPPH) scavenging activity, cupric reducing antioxidant capacity (CUPRAC) and ferric reducing antioxidant power (FRAP), total phenolic content (TPC), and total flavonoid contents (TFC) resulted in a maximum value of 62.5%, 41.95 and 48.39 µM, 143.6 mg GAE/g, and 166.8 CAE/g, respectively. High-resolution mass spectroscopic technique was performed to profile phenolic and flavonoid compounds. Upon analyzing, total 48 compounds were identified in NF. Altogether, our findings can provide a practical approach for utilizing NF in various bioindustries.

Optimization of fluoride removal by Al doped ZnO nanoparticles using response surface methodology from groundwater

The current novel work presents the optimization of factors affecting defluoridation by Al doped ZnO nanoparticles using response surface methodology (RSM). Al doped ZnO nanoparticles were synthesized by the sol-gel method and validated by FTIR, XRD, TEM/EDS, TGA, BET, and particle size analysis. Moreover, a central composite design (CCD) was developed for the experimental study to know the interaction between Al doped ZnO adsorbent dosage, initial concentration of fluoride, and contact time on fluoride removal efficiency (response) and optimization of the process. Analysis of variance (ANOVA) was achieved to discover the importance of the individual and the effect of variables on the response. The model predicted that the response significantly correlated with the experimental response (R² = 0.97). Among the factors, the effect of adsorbent dose and contact time was considered to have more influence on the response than the concentration. The optimized process parameters by RSM presented the adsorbent dosage: 0.005 g, initial concentration of fluoride: 1.5 g/L, and contact time: 5 min, respectively. Kinetic, isotherm, and thermodynamic studies were also investigated. The co-existing ions were also studied. These results demonstrated that Al doped ZnO could be a promising adsorbent for effective defluoridation for water.

Dummy template based molecularly imprinted solid-phase microextraction coating for analysis of trace disinfection by-product of 2,6-dichloro-1,4-benzoquinone using high-performance liquid chromatography

Trace disinfection by-products (DBPs) produced during the disinfection of drinking water are potentially carcinogenic, teratogenic and mutagenic, which has aroused much attention recently. In this study, a molecularly imprinted (MIP) solid -phase microextraction (SPME) fiber coating was prepared by an in-situ polymerization method using a dummy template molecule for the analysis of trace 2,6-dichloroindole-1,4-benzoquinone (2,6-DCBQ), a typical DBP. The characterization results suggested that this monolithic SPME fiber under the optimized conditions had the porous structure, large surface area and good thermal stability. Due to the strong structural recognition and molecular interaction between MIP SPME coating and target molecule, it showed good extraction selectivity and capacity to trace 2,6-DCBQ with an imprinting factor of 4.7. Then, coupling with high-performance liquid chromatography (HPLC)-ultraviolet (UV) detection, a sensitive analytical method for trace 2,6-DCBQ in water samples was successfully established with a detection limit down to 2.3 ng/mL. The recoveries of the proposed method were in range of 84.4-122% with the relative standard deviations of 1.0-13% (n = 3). The results showed that this MIP SPME-HPLC-UV method possessed high analytical selectivity and sensitivity for trace 2,6-DCBQ in water, which would benefit the improvement of the practicability of DBPs monitoring and detection methodology.

Evaluation of the Influence of the Combination of pH, Chloride, and Sulfate on the Corrosion Behavior of Pipeline Steel in Soil Using Response Surface Methodology

External damage to buried pipelines is mainly caused by corrosive components in soil solution. The reality that numerous agents are present in the corrosive environment simultaneously makes it troublesome to study. To solve that issue, this study aims to determine the influence of the combination of pH, chloride, and sulfate by using a statistical method according to the design of experiment (DOE). Response surface methodology (RSM) using the Box–Behnken design (BBD) was selected and applied to the design matrix for those three factors. The input corrosion current density was evaluated by electrochemical tests under variable conditions given in the design matrix. The output of this method is an equation that calculates the corrosion current density as a function of pH, chloride, and sulfate concentration. The level of influence of each factor on the corrosion current density was investigated and response surface plots, contour plots of each factor were created in this study.

Response surface methodology for strontium removal process optimization from contaminated water using zeolite nanocomposites

The effective removal of strontium from polluted water is an emerging issue worldwide, especially in Japan, after the destruction of Fukushima's Daiichi Nuclear Power Plant. In the strontium removal process, statistical optimization of associated factors is needed to reduce the quantity of chemicals and the number of experimental trials. In this study, response surface methodology based on the central composite design was employed for assessing the influence of different factors and their interaction effects on the efficiency of strontium removal. We have considered nanoscale zero-valent iron-zeolite (nZVI-Z) and nano-Fe/Cu zeolite (nFe/Cu-Z) as adsorbents for the effective removal of strontium. The results suggested that the studied three factors such as pH, contact time, and concentration are positively related to the adsorption of strontium. That is, the maximum strontium removal occurred at pH, initial concentration, and contact time of 12, 200 mg L^-1, and 30 min, respectively. The experimental maximum strontium adsorption capacity of nZVI-Z and nFe/Cu-Z adsorbents is 32.5 mg/g and 34 mg/g, respectively. The present study also showed that the most statistically significant potential contributor was initial concentration, followed by contact time in the removal process. The study indicated that the interaction effect between contact time and initial concentration was statistically important, suggesting the need for a multi-mechanism technique in the removal phase of strontium. Tόth, Langmuir, Dubinin-Astakhov (D-A), Freundlich, and Hill isotherm models were also fitted with the experimental strontium adsorption data, in which the Tόth model fitted best compared to the other models based on the RMSD and R².

Optimization of zinc bioleaching from paint sludge using Acidithiobacillus thiooxidans based on response surface methodology

The reduction of zinc metal in the paint sludge, a hazardous waste, was investigated using Acidithiobacillus thiooxidans by a two-stage bioleaching process. This process was performed using the response surface methodology (RSM) method based on the central composite design (CCD). Four variables, a temperature range of 32-34.5-37 °C, rotation speed of shaker 120-150-180 rpm, pH of 4.2-3.2-2.2, and particle sizes of 1-2-3 mm, were used to optimize the experiments. The results showed that with a constant pulp density of 10 g/L at 32 °C, shaker speed of 120 rpm, a particle size of 1 mm and pH of 4.2, the highest removal predicted by the software (Design Expert version 11) was 22.89%. Repeating the experiments confirmed a decrease in zinc to the nearest predicted point. According to the ANOVA result, the rotation speed of the shaker has the greatest effect on the bioleaching process, followed by the two variables of the rotation speed of shaker and pH together affects. After the bioleaching process, energy dispersive X-ray (EDX) and mapping analysis showed quantitative changes in the chemical composition of the paint sludge, and morphological changes of texture were confirmed by scanning electron microscopy (SEM).

Curve Fitting for Damage Evolution through Regression Analysis for the Kachanov-Rabotnov Model to the Norton-Bailey Creep Law of SS-316 Material

In a number of circumstances, the Kachanov–Rabotnov isotropic creep damage constitutive model has been utilized to assess the creep deformation of high-temperature components. Secondary creep behavior is usually studied using analytical methods, whereas tertiary creep damage constants are determined by the combination of experiments and numerical optimization. To obtain the tertiary creep damage constants, these methods necessitate extensive computational effort and time to determine the tertiary creep damage constants. In this study, a curve-fitting technique was proposed for applying the Kachanov–Rabotnov model into the built-in Norton–Bailey model in Abaqus. It extrapolates the creep behaviour by fitting the Kachanov–Rabotnov model to the limited creep data obtained from the Omega-Norton–Bailey regression model and then simulates beyond the available data points. Through the Omega creep model, several creep strain rates for SS-316 were calculated using API-579/ASME FFS-1 standards. These are dependent on the type of the material, the flow stress, and the temperature. In the present work, FEA creep assessment was carried out on the SS-316 dog bone specimen, which was used as a material coupon to forecast time-dependent permanent plastic deformation as well as creep behavior at elevated temperatures and under uniform stress. The model was validated with the help of published experimental creep test data, and data optimization for sensitivity study was conducted by applying response surface methodology (RSM) and ANOVA techniques. The results showed that the specimen underwent secondary creep deformation for most of the analysis period. Hence, the method is useful in predicting the complete creep behavior of the material and in generating a creep curve.

Development and Optimization of Chitosan-Hydroxypropyl Methylcellulose In Situ Gelling Systems for Ophthalmic Delivery of Bupivacaine Hydrochloride

The aim of this study was the development and optimization of chitosan and hydroxypropyl methylcellulose (HPMC) in situ gelling systems, loaded with bupivacaine hydrochloride for topical ocular administration. This study is based on the properties of two polymers: chitosan, which has mucoadhesive action and is a pH-sensitive polymer, but also the cellulose derivative hydroxypropyl methylcellulose, a thermosensitive polymer which has mucoadhesive properties and increases the viscosity of systems. The analysis and optimization of in situ gelling systems were performed based on an experimental design and response surface methodology. The following formulation parameters were considered: X1 = chitosan concentration (0.5%, 1%), X2 = HPMC E 5 LV concentration (2%, 5%) and X3 = Chitosan/HPMC E 5 LV ratio (1/1, 2/1). In addition, the parameters to be optimized were represented by the contact angle (CA (°)), viscosity and cumulative percentage of bupivacaine hydrochloride released in vitro. The results indicate that the designed in situ gelling systems are suitable for bupivacaine prolonged ophthalmic release and overcome the principal disadvantages of the liquid’s ocular formulations. An immediate therapeutic effect corresponding to ocular anesthetic installation was assured in the first stage: burst bupivacaine release. In the second phase, the gradual drug release was assured for over 6 h. This drug release profile, together with the corresponding rheological profile and a collection of superficial properties for good ocular adhesion balanced with an adequate hydrophilic character, assured the desired quality of the attributes for the proposed systems. The system, based on chitosan 1%, HPMC E 5 LV 5% and a 1/1 polymer ratio, could be a solution for the proposed formulation of in situ gelling colloidal systems, since the viscosity of the system was within the range of the optimal viscosity of the eye, and the amount of bupivacaine hydrochloride released after 6 h was the highest at 69.55%.

Ultrasound-Assisted Extraction Optimization of Proanthocyanidins from Kiwi (Actinidia chinensis) Leaves and Evaluation of Its Antioxidant Activity

Using ultrasound (US) in proanthocyanidin (PA) extraction has become one of the important emerging technologies. It could be the next generation for studying the US mechnophore impact on the bioactive compound’s functionality. The objective of this study was to demonstrate the potential of US treatment on PAs extracted from kiwifruit (Actinidia chinensis) leaves, and to provide a comprehensive chemical composition and bioactivity relationship of the purified kiwifruit leaves PAs (PKLPs). Several methods like single-factor experiments and response surface methodology (RSM) for the four affected factors on US extraction efficiency were constructed. HPLC-QTOF-MS/MS, cytotoxicity analysis, and antioxidant activity were also demonstrated. In the results, the modeling of PA affected factors showed that 40% US-amplitude, 30 mL/g dry weight (DW) solvent to solid ration (S/S), and 70 °C for 15 min were the optimum conditions for the extraction of PAs. Furthermore, PKLPs exhibited significant radical scavenging and cellular antioxidant activity (p < 0.05). In conclusion, this study’s novelty comes from the broad prospects of using US in PKLP green extraction that could play an important role in maximizing this phytochemical functionality in drug discovery and food science fields.