Central Composite Design-response Surface Methodology Research Articles

Urinary biomonitoring of fuel ether oxygenates using a needle trap device packed with a novel molecularly imprinted polymer surface modified Zeolite Y

This study introduces an innovative needle trap device (NTD) featuring a molecularly imprinted polymer (MIP) surface-modified Zeolite Y. The developed NTD was integrated with gas chromatography-flame ionization detector (GC-FID) and employed for analysis of fuel ether oxygenates (methyl tert‑butyl ether, MTBE, ethyl tert‑butyl ether, ETBE, and tert‑butyl formate, TBF) in urine samples. To optimize the key experimental variables including extraction temperature, extraction time, salt concentration, and stirring speed, a central composite design-response surface methodology (CCD-RSM) was employed. The optimal values for extraction in the study were found to be 51.2 °C extraction temperature, 46.2 min extraction time, 27 % salt concentration, and 620 rpm stirring speed. Under the optimized conditions, the calibration curves demonstrated excellent linearity within the range of 0.1–100 μg L−1, with correlation coefficients (R2) exceeding 0.99. The limits of detection (LODs) for MTBE, ETBE, and TBF were obtained 0.06, 0.08, and 0.09 μg L−1, respectively. Moreover, the limits of quantification (LOQs) for MTBE, ETBE, and TBF were obtained 0.18, 0.24, and 0.27 μg L−1, respectively. The enrichment factor was also found to be in the range of 98–129.The NTD-GC-FID procedure demonstrated a high extraction efficiency, making it a promising tool for urinary biomonitoring of fuel ether oxygenates with improved sensitivity and selectivity compared to current methods.

Selection of performance indicators on dielectric strength and viscosity for chlorinated polyvinyl chloride with N-Methyl-2-pyrrolidone: Optimization using central composite design-response surface methodology

N-methyl-2-pyrrolidone is a highly polar aprotic solvent that is frequently utilized across a broad range of applications in industry. The composition of chlorinated polyvinyl chloride is commonly flame-resistant and mechanically strong. In this research, the central composite design technique uses response surface methodology to perform a parametric study. The effect of the input variables wt.% (16%, 20%, 24%), stirring speed (300, 600, 900 r/min), and stirring time (20 min, 30 min, 40 min) on the output responses (dielectric strength kV/mm, and viscosity Pascal) were examined. The output responses were recorded during the experiments according to the experimental design. The factors impacting the response were identified through analysis of variance. According to the predicted vs. actual diagram, the confirmed experiments fit well with the predictions. Based on the response surface, the parameter interaction profile was analyzed. According to the contour plots related to each interaction, the maximum value can be achieved within different stirring parameters. Based on the result of optimization, the optimum values of dielectric strength and viscosity were found in (wt.% of chlorinated polyvinyl chloride—18.101%), (stirring speed—664 r/min), (stirring time—21.860 min). The output response obtained from the response surface methodology is the dielectric strength (18.5 kV/mm) and viscosity (37.67 Pa).

Improvement of Cross-linked Alginate Hydrogel Microparticles Loaded with Galangin-β-Cyclodextrin Complex by Response Surface Methodology

AbstractGalangin is a phenolic compound with antioxidant and anti-tyrosinase activity, which makes it highly useful in cosmetics and medicine. However, the poor solubility of galangin in water limits its usefulness in these areas. This study it is aimed to increase the solubility of galangin in water by encapsulation method. Therefore, in this study, ethanolic and methanolic extracts were obtained from Alpinia officinarum Hance, and the phenolic compound profile and content of the extracts were determined by HPLC-DAD. Galangin was purified and fractionated from Alpinia officinarum Hance extracts by column chromatography. Galangin was encapsulated with β-cyclodextrin, and galangin-β-cyclodextrin loaded alginate hydrogel microparticles were developed. The central composite design-response surface methodology was used to develop galangin-β-cyclodextrin loaded alginate hydrogel microparticles under optimum conditions with maximum galangin release. The encapsulation efficiency and release of galangin in galangin-β-cyclodextrin loaded alginate hydrogel microparticles developed under optimum conditions were characterized by HPLC-DAD, surface morphology by SEM, and structural properties by FTIR.

Oxidation of Allura Red AC Using the NaHCO3-activated H2O2 System Catalyzed with Cobalt Supported on Al-PILC

The oxidation of aqueous solutions containing Allura Red AC (AR–AC) using bicarbonate-activated peroxide (BAP) and cobalt-impregnated pillared clay (Co/Al–PILC) as the catalyst was investigated. Using the CCD-RMS approach (central composite design–response surface methodology), the effects of dye, H2O2, and NaHCO3 concentrations on AR–AC degradation were studied. The decolorization, total nitrogen (TN), and total carbon (TC) removals were the analyzed responses, and the experimental data were fitted to empirical quadratic equations for these responses, obtaining coefficients of determination R2 and adjusted-R2 higher than 0.9528. The multi-objective optimization conditions were [dye] = 21.25 mg/L, [H2O2] = 2.59 mM, [NaHCO3] = 1.25 mM, and a catalyst loading of 2 g/L. Under these conditions, a decolorization greater than 99.43% was obtained, as well as TN and TC removals of 72.82 and 18.74%, respectively, with the added advantage of showing cobalt leaching below 0.01 mg/L. Chromatographic analyses (GC–MS and HPLC) were used to identify some reaction intermediates and by-products. This research showed that wastewater containing azo dyes may be treated using the cobalt-catalyzed BAP system in heterogeneous media.

Comparison of an Ultrasound-Assisted Aqueous Two-Phase System Extraction of Anthocyanins from Pomegranate Pomaces by Utilizing the Artificial Neural Network-Genetic Algorithm and Response Surface Methodology Models.

As a by-product of pomegranate processing, the recycling and reuse of pomegranate pomaces (PPs) were crucial to environmentally sustainable development. Ultrasound-assisted aqueous two-phase extraction (UA-ATPE) was applied to extract the anthocyanins (ACNs) from PPs in this study, and the central composite design response surface methodology (CCD-RSM) and artificial neural network-genetic algorithm (ANN-GA) models were utilized to optimize the extraction parameters and achieve the best yield. The results indicated that the ANN-GA model built for the ACN yield had a greater degree of fit and accuracy than the RSM model. The ideal model process parameters were optimized to have a liquid-solid ratio of 49.0 mL/g, an ethanol concentration of 28 g/100 g, an ultrasonic time of 27 min, and an ultrasonic power of 330 W, with a maximum value of 86.98% for the anticipated ACN yield. The experimental maximum value was 87.82%, which was within the 95% confidence interval. A total of six ACNs from PPs were identified by utilizing UHPLC-ESI-HRMS/MS, with the maximum content of cyanidin-3-O-glucoside being 57.01 ± 1.36 mg/g DW. Therefore, this study has positive significance for exploring the potential value of more by-products and obtaining good ecological and economic benefits in the future.

Optimization for Removal of COD and BOD through RSM-CCD by Activated Sludge Treatment Process for Pharmaceutical Wastewater

Wastewater generated from home and commercial operations is a polluting component of water. One of the main contributors for the production of wastewater by various manufacturing processes is the pharmaceutical industry. The commercial operations of industry are causing an increase in the amount of organic and inorganic contaminants, such as total suspended solids, chemical oxygen demand (COD) and biological oxygen demand (BOD). Activated sludge process reduces COD, BOD and Total Suspended Solids (TSS), with three input variables: pH, time and Mixed Liquor Suspended Solids (MLSS). The Central Composite Design-Response Surface Methodology (CCD-RSM) is used to optimize responses for COD and BOD removal efficiency. To achieve optimization results, numerous sets of trials were conducted for the input variables - pH (4.2–6.5), time (12–30 h) and MLSS (2520–4310 mg/l). The analyzed models were shown to be quadratic and highly significant by the F-value and P-value. The regression coefficients (R2) for the quadratic models developed for removal efficiency, COD, and BOD5 are 0.9996, 0.9995 and 0.9996, respectively. According to CCD-RSM, the optimal matching input factors for the greatest removal efficiency of BOD and COD were: MLLS = 3415 mg/l, time = 21 h and pH = 5.35. Using the traditional method, the maximum removal (95%) of BOD and COD was seen at pH = 6.5, time = 12 h and MLLS = 4310 mg/l.

Study on the Mechanical Properties of Polyurethane-Cement Mortar Containing Nanosilica: RSM and Machine Learning Approach

Polymer-modified cement mortar has been increasingly used as a runway/road pavement repair material due to its improved bending strength, bonding strength, and wear resistance. The flexural strength of polyurethane–cement mortar (PUCM) is critical in achieving a desirable maintenance effect. This study aims to evaluate and optimize the flexural strength of PUCM involving nano silica (NS) using a central composite design/response surface methodology (CCD/RSM) to design and establish statistical models. The PU binder and NS were utilized as input parameters to evaluate the responses, such as compressive and flexural strength. Moreover, machine learning (ML) algorithms including artificial neural networks (ANN) and Gaussian regression process (GPR) were used. The PUCM mixtures were prepared by adding a PU binder at 0%, 10%, 15%, and 25% by weight of cement. At the same time, NS was incorporated into the mortar mixes at 0 to 3% (interval of 1%) by cement weight. The results showed that the simultaneous effect of PU binder at the optimal content and NS improved the performance of PUCM. Adding NS to the mortar mixture mitigated some of the strength lost due to the PU binder, which remarkably reduces the strength properties at a high content. The optimized PUCM can be obtained by partly adding 3.5% PU binder and 2.93% NS particles by the weight of cement. The performance of the machine learning algorithms was tested using performance indicators such as the determination of coefficient (R2), mean absolute error (MAE), mean-square error (MSE), and root-mean-square error (RMSE). The GPR algorithm outperformed the ANN with higher R2 and lower MAE values in the training and testing phases. The GPR can predict flexural strength with 90% accuracy, while ANN can predict it with 75% accuracy.

Enhanced adsorption performance of tetracycline in aqueous solutions using Mg-Al-LDH/AC nanocomposite

Water contamination with antibiotics promotes environmental antibiotic resistance. Tetracycline(TC), commonly used in agriculture, pollutes water and enables bacteria to develop resistance genes. Mg-Al-layered double hydroxides/Activated carbon (Mg-Al-LDH/AC) nanocomposite effectively removes tetracycline from water in this study. The synthesized adsorbent was characterized using Brunauer–Emmett–Teller (BET), Fourier-transform Infrared Spectroscopy (FT-IR), Field Emission Scanning Electron Microscopy (FESEM), X-Ray Diffraction (XRD), and Energy-dispersive X-ray spectroscopy (EDS) tests, and exhibited a large surface area of 105.46 m2/g, a total pore volume of 0.4571 cm3/g, and an average pore diameter of 27.99 nm. The optimal conditions for eliminating TC using the Mg-Al-LDH/AC nanocomposite were determined via the central composite design response surface methodology (CCD-RSM) approach. The responses were evaluated using a second-order polynomial multiple regression model, which was found to be a satisfactory fit to the data based on the analysis of variance (R2 = 0.9690, R2Adj = 0.9478, and R2Pred = 0.9042). The ideal conditions were identified as pH = 5.1, 0.11 g of adsorbent, a TC concentration of 50 mg/L, and a contact time of 90 min. The adsorption isotherms showed that TC elimination follows the Langmuir model with a maximum adsorption capacity of 106.4 mg/g and a high R2 value of 0.9986. The kinetics of the TC adsorption process was found to fit the pseudo-second-order model with a correlation value of 0.9997. The values of ΔG, ΔH, and ΔS for TC were determined to be 1.90 kJ/mol (at 333.15 K), −41.97 kJ/mol, and −0.131 kJ/(mol·K), respectively. Additionally, the study showed that ionic strength did not affect the effectiveness of TC removal, and the adsorbent was effective in removing TC antibiotics in a range of ionic strengths. Finally, the study found that adding 20% by weight of AC to LDH resulted in the best TC removal efficiency.

Development of A Nanostructured Lipid Carrier-Based Drug Delivery Strategy for Apigenin: Experimental Design Based on CCD-RSM and Evaluation against NSCLC In Vitro.

Non-small-cell lung cancer (NSCLC) is the main cause of cancer-related deaths worldwide, with a low five-year survival rate, posing a serious threat to human health. In recent years, the delivery of antitumor drugs using a nanostructured lipid carrier (NLC) has become a subject of research. This study aimed to develop an apigenin (AP)-loaded nanostructured lipid carrier (AP-NLC) by melt sonication using glyceryl monostearate (GMS), glyceryl triacetate, and poloxamer 188. The optimal prescription of AP-NLC was screened by central composite design response surface methodology (CCD-RSM) based on a single-factor experiment using encapsulation efficiency (EE%) and drug loading (DL%) as response values and then evaluated for its antitumor effects on NCI-H1299 cells. A series of characterization analyses of AP-NLC prepared according to the optimal prescription were carried out using transmission electron microscopy (TEM), differential scanning calorimetry (DSC), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR). Subsequent screening of the lyophilization protectants revealed that mannitol could better maintain the lyophilization effect. The in vitro hemolysis assay of this formulation indicated that it may be safe for intravenous injection. Moreover, AP-NLC presented a greater ability to inhibit the proliferation, migration, and invasion of NCI-H1299 cells compared to AP. Our results suggest that AP-NLC is a safe and effective nano-delivery vehicle that may have beneficial potential in the treatment of NSCLC.

Optimization of subtilisin production from Bacillus subtilis strain ZK3 and biological and molecular characterization of synthesized subtilisin capped nanoparticles

The increase and dissemination of multi-drug resistant bacteria have presented a major healthcare challenge, making bacterial infections a significant concern. The present research contributes towards the production of bioactive subtilisin from a marine soil isolate Bacillus subtilis strain ZK3. Custard apple seed powder (raw carbon) and mustard oil cake (raw nitrogen) sources showed a pronounced effect on subtilisin production. A 7.67-fold enhancement in the production was evidenced after optimization with central composite design-response surface methodology. Subtilisin capped silver (AgNP) and zinc oxide (ZnONP) nanoparticles were synthesized and characterized by UV–Visible spectroscopy. Subtilisin and its respective nanoparticles revealed significant biological properties such as, antibacterial activity against all tested pathogenic strains with potential against Escherichia coli and Pseudomonas aeruginosa. Prospective antioxidant behavior of subtilisin, AgNP and ZnONP was evidenced through radical scavenging assays with ABTS and DPPH. Subtilisin, AgNP and ZnONP revealed cytotoxic effect against cancerous breast cell lines MCF-7 with IC50of 83.48, 3.62 and 7.57 µg/mL respectively. Characterizations of nanoparticles were carried out by Fourier transform infrared spectroscopy, scanning electron microscopy with energy dispersive X-ray, X-ray diffraction, thermogravimetric analysis and atomic force microscopy analysis to elucidate the structure, surface and thermostability properties. The study proposes the potential therapeutic applications of subtilisin and its nanoparticles, a way forward for further exploration in the field of healthcare.

Unleashing synergistic potential of microbially enhanced anaerobic co-digestion of petroleum refinery biosludge and yard waste: Impact of nutrient balance and microbial diversity

Petroleum refinery sludge, an egregious solid residue generated from the wastewater treatment plants poses an environmental hazard owing to its intricate hydrocarbon composition, necessitating competent treatment for secure disposal. The study proposes a green solution through anaerobic co-digestion of nitrogen-rich petroleum refinery sludge (PS) with carbon-rich yard waste (YW), balancing the nutrients and moisture content for efficient microbial proliferation. Using Central Composite Design-Response Surface Methodology, 1 L batch experiments were conducted with varying carbon/nitrogen (C/N) ratios and pH to achieve maximum biogas yield within 50 days of co-digestion. However, the sluggish biogas recovery (40%) indicated a slow rate-limiting hydrolysis, necessitating pretreatment. Feedstock incubation with Bacillus subtilis IH1 strain, isolated from the microbially-enriched PS, at 108 colony forming units (CFU) per mL for 5 days maximized the soluble chemical oxygen demand and volatile fatty acids by 2.2 and 1.4 folds respectively compared to untreated feedstock. Scale-up Bacillus subtilis aided co-digestion studies further augmented biogas by 76% against untreated monodigestion of PS with significant total petroleum hydrocarbons, emulsions, and lignocellulosic degradation. Further identification of major organic pollutants in the batch digestate revealed significant degradation of the toxic organic hydrocarbon pollutants apotheosizing the efficacy of the synergistic sustainable technique for the management of PS. Environmental implicationThe effluent treatment plants (ETPs) of petroleum refining industries generate sludge which is a complex mixture of petroleum hydrocarbons, oil–water (O/W) emulsions and heavy metals. These petroleum hydrocarbon constituents can be linear/cyclic alkanes, polyaromatics, resins and asphaltenes, whose intricate composition is reportedly carcinogenic, cytogenic and mutagenic, classifying it as hazardous waste. Biological treatment of these sludge through anaerobic digestion leads to utilization of petroleum hydrocarbons with subsequent energy recovery. Co-digestion of these sludge with competent co-substrates leads to nutrient balance, diverse microbial proliferation and toxicant dilution. Microbially aided co-digestion further augments methane rendering a digestate with utmost pollutant degradation.

Zanthoxylum bungeanum amides ameliorates nonalcoholic fatty liver via regulating gut microbiota and activating AMPK/Nrf2 signaling

Ethnopharmacological relevanceZanthoxylum bungeanum Maxim. (Rutaceae) is a known herbal medicine with various bioactivities, including anti-obesity, lipid-lowering, learning & memory improving and anti-diabetes, and amides in Z. bungeanum (AZB) are considered as the major active agents for its bioactivities. Aim of the studyThis research was carried out to uncover the anti-NAFL effect of AZB and its corresponding molecular mechanisms. MethodsThe central composite design-response surface methodology (CCD-RSM) was utilized to optimize the AZB extraction process, and the anti-NAFL effect of AZB was investigated on high fat diet (HFD) fed mice (HFD mice). The levels of ROS in liver tissues were determined using laser confocal microscopy with DCFH-DA probe staining, and anti-enzymes (such as HO-1, SOD, CAT & GSH-PX) and MDA in liver tissues were measured using commercial detecting kits. GC-MS was used to determine the short-chain fatty acids (SCFAs) contents in feces and blood of mice. 16S high-throughput sequencing, western blotting (WB) assay and immunofluorescence (IF) were used to explore the intestinal flora changes in mice and the potential mechanisms of AZB for treatment of NAFL. ResultsOur results showed AZB reduced body weight, alleviated liver pathological changes, reduced fat accumulation, and improved oxidative stress in HFD mice. In addition, we also found AZB improved OGTT and ITT, reduced TG, TC, LDL-C, whereas increased HDL-C in HFD mice. AZB increased total number of the species and interspecies kinship of gut microbiota and reduced the richness and diversity of gut microbiota in HFD mice. Moreover, AZB decreased the ratio of Firmicutes/Bacteroidota, whereas increased the abundance of Allobaculum, Bacteroides and Dubosiella in feces of HFD-fed mice. Furthermore, AZB increased the production of SCFAs, and up-regulated the phosphorylation of AMPK and increased the nuclear transcription of Nrf2 in liver of HFD mice. ConclusionCollectively, our results suggested AZB can improve NAFL, which could reduce body weight, reverse liver lesions and fat accumulation, improve oxidative stress in liver tissues of HFD mice. Furthermore, the mechanisms are related to increase of the abundance of high-producing bacteria for SCFAs (e.g. Allobaculum, Bacteroides and Dubosiella) to activate AMPK/Nrf2 signaling.

Optimization of adsorption performance of cerium-loaded intercalated bentonite by CCD-RSM and GA-BPNN and its application in simultaneous removal of phosphorus and ammonia nitrogen

Excessive phosphorus (P) and ammonia nitrogen (NH3–N) in water bodies can lead to eutrophication of the aquatic environment. Therefore, it is important to develop a technology that can efficiently remove P and NH3–N from water. Here, the adsorption performance of cerium-loaded intercalated bentonite (Ce-bentonite) was optimized based on single-factor experiments using central composite design-response surface methodology (CCD-RSM) and genetic algorithm-back propagation neural network (GA-BPNN) models. Based on the determination coefficient (R2), mean absolute error (MAE), mean square error (MSE), mean absolute percentage error (MAPE), and root mean square error (RMSE), the GA-BPNN model was found to be more accurate in predicting adsorption conditions than the CCD-RSM model. The validation results showed that the removal efficiency of P and NH3–N by Ce-bentonite under optimal adsorption conditions (adsorbent dosage = 1.0 g, adsorption time = 60 min, pH = 8, initial concentration = 30 mg/L) reached 95.70% and 65.93%. Furthermore, based on the application of these optimal conditions in simultaneous removal of P and NH3–N by Ce-bentonite, pseudo-second order and Freundlich models were able to better analyze adsorption kinetics and isotherms. It is concluded that the optimization of experimental conditions by GA-BPNN has some guidance and provides a new approach to explore adsorption performance after optimizing the conditions.

Integrating chemical coagulation with fixed-bed column adsorption using rice husk-derived biochar for shipboard bilgewater treatment: Scale-up design and cost estimation

Discharging shipboard bilgewater (SBW) into seas and oceans without proper treatment could poison marine organisms and negatively impact transportation-related activities. This study focuses on the treatment of synthetic SBW using a simple and cost-efficient physico-chemical process. This treatment system included coagulation-flocculation (CF) using alum coagulant and fixed-bed column adsorption using rice husk-derived biochar (RHB). The optimization and effect of CF process parameters, viz., pH, fast stirring speed, and alum dosage, on surfactant and COD removal efficiencies were studied using a central composite design-response surface methodology (CCD-RSM). At optimum conditions (pH of 6.4, rapid mixing speed of 160 rpm, and coagulant dosage of 140 mg/L), the surfactants and COD removal efficiencies were 46.31±1.48% and 84.67±2.61%, respectively. The adsorption column optimum conditions were flow rate= 5 mL/min and bed depth= 16 cm, giving a surfactant removal efficiency of 96.6%. The primary adsorption mechanism was physisorption, including electrostatic attraction, hydrogen bonding, pore-filling, and hydrophobic interaction, as revealed by SEM, EDX, and FTIR characterizations. The adsorption data fitted well with Thomas model predictions, giving the best kinetic constant (KTh)= 0.305 mL/min/mg and equilibrium surfactant uptake (qo)= 11.05 mg/g (R2= 0.996). The Thomas model's coefficients were successfully used to predict the breakthrough curves and determine the column dimensions for pilot-scale (3 L/h) and large-scale (300 L/h) fixed-bed adsorption units. The estimated cost for the on-board treatment of SBW by the proposed system was 2.51 US$/m3. Future studies are required to implement the proposed combined coagulation/flocculation/adsorption system to treat real SBW from medium-sized ships.

Ex-situ biodiesel production from Simmondsia chinensis (Jojoba) biomass: Process evaluation and optimization

Biodiesel production is explored in the current study through the ex-situ extraction and trans-esterification approach from commercially available Jojoba seed. This biomass is regarded as a beneficial feedstock for biodiesel production as it contains non-edible oil. Also, this feedstock can be cultivated and grown in wastewater and in variable climate conditions. According to the characteristic analysis Jojoba oil is composed of 6.9% saturated fatty acids (4.6% C16:0, 1.3% C18:0 and 0.2% C20:0), 68.7% monounsaturated fatty acids (48% C20:1, 20.2% C18:1 and 0.5% C16:1) and 24.4% polyunsaturated fatty acids (14.8% C18:2, 9.2% C20:2 and 0.4% C18:3). The acid value of crude Jojoba oil is 0.05 mg KOH/ g sample, which feasible the alkaline catalyzed trans-esterification. The effect of variables on oil extraction was explored preliminary through the time-efficient and low-cost central composite design response surface methodology (CCD-RSM). According to the results, 67.51 wt.% saponifiable oil can be extracted from Jojoba seed at 64.5 °C, reaction duration of 187.7 min, rotation rate of 393.2 rpm, and solvent to biomass ratio of 14.6 cc:1 g. The maximum yield of biodiesel production is also obtained at 50 °C, methanol to oil molar ratio (MeOH: Oil) of 5.5:1, reaction time of 2.25 h, and 0.475 wt.% (KOH weight/ oil weight) KOH loading.

Optimitimization of sorghum protein isolates as a by-product of starch extraction using enzymatic methods

The lack of protein consumption in Indonesian society has caused an increase in malnutrition sufferers in the country. One of the prevention efforts is making protein isolates with sorghum as raw materials because sorghum is a cereal with the highest protein content compared to other grains. To produce food-grade isolates, the isolation process is carried out with the help of the α-amylase enzyme, which has an activity of 6,666,563 units/ml. This study aimed to determine the optimization value and functional characteristics of sorghum protein isolate produced using enzymatic methods. This research was conducted with an experimental method followed by hypothesis testing using a CCD (Central Composite Design) RSM (Response Surface Methodology) test with α-amylase enzyme variables and 0.9 % -1.8% and 1.5-2.5 hours for reaction times of each upper and lower limit. The desired response variable is protein content. Protein isolates with the highest levels or 58.40% were obtained with an enzyme amount of 1.35% with a hydrolysis length of time of 3.4 hours. Estimation validation will get optimum levels or more than 90% will be produced using the α-amylase enzyme of 2.63% and hydrolyzed for 2 hours.

Development of a Liquid-Phase Microextraction Method Prior to HPLC Analysis of Quercetin in Food Samples.

In this research, an efficient, fast, low-cost and easy-to-use liquid-phase microextraction method was established to measure quercetin in onion and tomato before analysis by HPLC instrument. Herein, a rotatable central composite design-response surface methodology and artificial neural network were applied to model, optimize and predict the affecting factors on the microextraction procedure. Here, a minimal level of extractant was applied in the absence of a disperser. The cloudy state was formed by repeatedly suctioning and injecting the mixture of the aqueous solution and extractant with a glass syringe. Due to this procedure, a turbid solution composed of the very fine droplets of extractant dispersed in the aqueous solution was created, the contact surface was significantly enlarged and the quercetin was promptly extracted. The optimum values for the proposed method included 284μL of 1-undecanol as the organic extractive solvent, pH of sample 3.3, the number of air injected nine times and speed and duration of centrifugation 4,000rpm and 5min. The linear range and detection of limit were achieved at 20-4,000 and 6μgL-1, respectively. RSD% was obtained ˂4.93% (n = 5). This model was applied to monitor quercetin in tomato and onion samples.

Modeling and optimization of photo-fermentation biohydrogen production from co-substrates basing on response surface methodology and artificial neural network integrated genetic algorithm

The main aim of the present study was to establish a relationship model between bio-hydrogen yield and the key operating parameters affecting photo-fermentation hydrogen production (PFHP) from co-substrates. Central composite design-response surface methodology (CCD-RSM) and artificial neural network-genetic algorithm (ANN-GA) models were used to optimize the hydrogen production performance from co-substrates. Compared to CCD-RSM, the ANN-GA had higher determination coefficient (R2 = 0.9785) and lower mean square error (MSE = 9.87), average percentage deviation (APD = 2.72) and error (4.3%), indicating the ANN-GA was more suitable, reliable and accurate in predicting biohydrogen yield from co-substrates by PFHP. The highest biohydrogen yield (99.09 mL/g) predicted by the ANN-GA model at substrate concentration 35.62 g/L, temperature 30.94 °C, initial pH 7.49 and inoculation ratio 32.98 %(v/v), which was 4.20 % higher than the CCD-RSM model (95.10 mL/g).

Optimization of a lipase/reduced graphene oxide/metal-organic framework electrode using a central composite design-response surface methodology approach.

Lipase has been gaining attention as the recognition element in electrochemical biosensors. Lipase immobilization is important to maintain its stability while providing excellent conductivity. In this study, a lipase electrochemical biosensor immobilized on a copper-centred metal-organic framework integrated with reduced graphene oxide (lipase/rGO/Cu-MOF) was synthesized by a facile method at room temperature. Response surface methodology (RSM) via central composite design (CCD) was used to optimize the synthesis parameters, which are rGO weight, ultrasonication time, and lipase concentration, to maximize the current response for the detection of p-nitrophenyl acetate (p-NPA). The results of the analysis of variance (ANOVA) showed that all three parameters were significant, while the interaction between the ultrasonication time and lipase concentration was the only significant interaction with a p-value of less than 0.05. The optimized electrode with parameters of 1 mg of rGO, 30 min ultrasonication time, and 30 mg mL-1 lipase exhibited the highest current response of 116.93 μA using cyclic voltammetry (CV) and had a residual standard error (RSE) of less than 2% in validation, indicating that the model is suitable to be used. It was characterized by X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), and Fourier transform infrared spectroscopy (FTIR), where the integration of the composite was observed. Immobilization using ultrasonication altered the lipase's secondary structure, but reduced its unorderly coils. The electrochemical and thermal analysis showed that the combination of Cu-MOF with rGO enhanced the electrochemical conductivity and thermostability.

High removal efficiency of volatile phenol from coking wastewater using coal gasification slag via optimized adsorption and multi-grade batch process

Abstract Powder adsorbent made by coal gasification slag (CGS) was used to adsorb pollutants from coking wastewater (CW). This study initially focused on the removal efficiency of volatile phenol, NH3–N, and chemical oxygen demand (COD) from CW. The removal rate of volatile phenol increased from 48.90% to 70.50% after acid precipitation of CW by 4.0 mL reagent of sulfuric acid (3.0 M) and optimization of adsorption process by central composite design-response surface methodology with optimized conditions. Volume ratio of liquid and solid adsorbent (V L/S) and pH were the significant factors in the adsorption process. Batch experiment improved the volatile phenol, NH3–N, and COD removal rate to 85.1%, 41.6%, and 77.3%, respectively. Multi-grade batch process in grade 3 made a further promotion of pollutants removal rate as 98.5%, 73.6%, and 80.5%, respectively. Scanning electron microscope-energy dispersive spectrum and Fourier-transform infrared spectrometer were used to confirm the adsorption effect. CGS-based adsorbent for CW treatment has potential advantages due to the features of good adsorption performance and low cost.