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Globally, both industrialized and developing nations struggle with the issue of water pollution due to heavy metals. Human life depends on water, and when it is contaminated with dangerous heavy metals like arsenic, people's health suffers. The interactive influence of three independent sorption processes variables such as bio-adsorbent dosage (0.50–3.00 g/L), contact time (40.00–90.00 min), and initial concentration (10.00–30.00 mg/L) on the modeling and optimization of trivalent arsenic removal from wastewater was studied in a batch mode using multivariate experimental design. The quadratic models provided accurate predictions for the response variables with high coefficients of correlation of 0.9984 and 0.9994 for removal and uptake rates, respectively. The developed models were accurate and exhibited a remarkable correlation between the observed and projected data according to the diagnostic test analyses. Through the analysis of variance, all the studied adsorption factors were statistically significant (p-values < 0.0001) with initial concentration and bio-adsorbent dosage producing the main interactive effect on the percentage removal and adsorption capacity with F-values of 146.05 and 264.65, respectively. The optimum operating conditions attained were 90.00 min contact time, 0.50 g/L bio-adsorbent dosage, and an initial concentration of 10.00 mg/L, which gave arsenic maximum removal and uptake efficiencies of 93.14% and 7.04 mg/g, correspondingly with the desirability of 0.844. Confirmative tests were conducted under the optimized conditions to validate the accuracy of the models in which a maximum removal efficacy of 94.33% and adsorption capacity of 7.15 mg/g were achieved. The applicability of the bio-adsorbent in the adsorption of arsenic in textile industrial wastewater was also tested and the bio-adsorbent could competitively decontaminate over 99% of arsenic species from the wastewater. [ABSTRACT FROM AUTHOR]

Currently, pozzolanic materials are mostly recommended to improve the properties of cement composite materials and reduce environmental pollution, challenging the world owing to ordinary Portland cement (OPC) production. Bentonite is mostly available natural pozzolana, however, extensive studies conducted on other clays like kaolin and some studies reported that bentonite exists in a consolidated form which requires heating activation methods. Therefore, it is essential to investigate the properties of bentonite in detail for its sustainable use, and it is novel to model and optimize the optimum bentonite calcination temperature and time for the best performance replacement in mortar. Hence, the present study investigates the optimum bentonite calcination temperature, calcination time, and replacement dose for mortar strength and free lime using the central composite design-response surface method (CCD-RSM). The mortar was prepared by replacing the calcined bentonite with cement weight with different values of the factor variables, bentonite dose, calcination temperature, and calcination time. Durability tests were conducted after 56 days. Thus, the results indicate that the selected model of response variables for compressive strength and free lime were significant, accurate, reliable, and had excellent fitness to the experimental work. Hence, CCD-RSM predicted the optimum for independent factors of bentonite dose 19.99 %, calcination temperature 799.99 °C, and calcination time 135.04 min and experimentally validated, which improved the strength by 24.94% and reduced free lime by 3.08% compared to the control mortar, besides reducing CO2 emissions compared to OPC production, which requires 1450 °C. Furthermore, the optimized bentonite replacement parameters have highly enhanced durability in different environments such as water, acids, salt, and elevated temperature compared to the control mixture at the age of 56 days.

Heavy metal contamination is one of the key environmental complications. Due to some disadvantages of conventional methods, the use of active organisms is becoming more popular technique to remove it. In the present study, primarily 35 bacterial strains were discovered in metal containing media. After being identified resistance power to different copper concentrations (100–1000 mg/l), JRHM33 had the highest level of resistance up to 1000 mg/l of copper. Using the 16S rRNA sequencing, bacterial strain JRHM33 was discovered and revealed 99% similarity to pseudomonas aeruginosa. Sequencing and bioinformatics study using conserved domain analysis supported the laccase gene is present in JRHM33 and has classification as a member of the multicopper oxidase superfamily, which has reduction capacity of metal ions. Analysis of phenotype microarray (PM) technology provides an insight into the metabolic profiling of microbial cell into Pseudomonas aeruginosa JRHM33. Furthermore, Using the central composite design of response surface methodology (CCD-RSM), the successive optimization of the process parameters was attempted for the maximum reduction of the copper. Maximum 68.71% Cu reduction was achieved at 6.71 pH, 90.61 min of incubation time, 5 ml of inoculum size, and 113 rpm of agitation. The generated model has R2 value of 0.9834, indicating that the ANOVA gave it a very significant result. The findings of the validation experiment showed a remarkable similarity between the projected and experimental results. It is determined that bacterial strains isolated from metal-contaminated effluent employ their natural capacity to change toxic heavy metals into less harmful or nontoxic forms.

Real textile wastewater (RTWW) poses significant environmental challenges. RTWW typically contains high levels of organic compounds, such as dyes, as well as inorganic substances like salts. These contaminants can harm aquatic life when released into water bodies without appropriate treatment. RTWW was subjected to a series of sequential treatments: exchange resins for removing ions, advanced oxidation with bicarbonate-activated peroxide to degrade organic matter, and a biological treatment based on the Zahn–Wellens test to remove remaining chemical oxygen demand (COD) The advanced oxidation process based on the activation of H2O2 with NaHCO3 (catalyzed with cobalt impregnated on a pillared clay, Co/Al–PILC)) was optimized using central composite design (CCD) and response surface methodology (RSM). After the process integration, reductions in ion concentrations, chemical oxygen demand (COD), and total organic carbon content (TOC) were achieved. Reduced hardness (99.94%) and ions (SO42− and acid black 194 dye of 99.88 and 99.46%, respectively), COD (96.64%), and TOC (96.89%), guaranteeing complete treatment of RTWW, were achieved. Additionally, the biodegradability index of RTWW increased from 0.28 ± 0.01 to 0.90 ± 0.01, and phytotoxicity was reduced, going from a phytotoxic that inhibited the germination of lettuce seeds to a phytostimulant after biological treatment with activated sludge. [ABSTRACT FROM AUTHOR]

Heavy metal contamination is one of the key environmental complications. Due to some disadvantages of conventional methods, the use of active organisms is becoming more popular technique to remove it. In the present study, primarily 35 bacterial strains were discovered in metal containing media. After being identified resistance power to different copper concentrations (100–1000 mg/l), JRHM33 had the highest level of resistance up to 1000 mg/l of copper. Using the 16S rRNA sequencing, bacterial strain JRHM33 was discovered and revealed 99% similarity to pseudomonas aeruginosa. Sequencing and bioinformatics study using conserved domain analysis supported the laccase gene is present in JRHM33 and has classification as a member of the multicopper oxidase superfamily, which has reduction capacity of metal ions. Analysis of phenotype microarray (PM) technology provides an insight into the metabolic profiling of microbial cell into Pseudomonas aeruginosa JRHM33. Furthermore, Using the central composite design of response surface methodology (CCD-RSM), the successive optimization of the process parameters was attempted for the maximum reduction of the copper. Maximum 68.71% Cu reduction was achieved at 6.71 pH, 90.61 min of incubation time, 5 ml of inoculum size, and 113 rpm of agitation. The generated model has R² value of 0.9834, indicating that the ANOVA gave it a very significant result. The findings of the validation experiment showed a remarkable similarity between the projected and experimental results. It is determined that bacterial strains isolated from metal-contaminated effluent employ their natural capacity to change toxic heavy metals into less harmful or nontoxic forms. [ABSTRACT FROM AUTHOR]

Opioid use, particularly morphine, is linked to CNS-related disorders, comorbidities, and premature death. Morphine, a widely abused opioid, poses a significant global health threat and serves as a key metabolite in various opioids. Here, we present a turn-off fluorescent sensor capable of detecting morphine with exceptional sensitivity and speed in various samples. The fluorescent sensor was developed through the dimerization process of 7-methoxy-1-tetralone and subsequent demethylation to produce the final product. Despite morphine possessing inherent fluorophoric properties and emitting light in an approximately similar wavelength as the sensor's fluorescent blue light, the introduction of the target molecule (morphine) in the presence of the sensor caused a reduction in the sensor's fluorescence intensity, which is attributable to the formation of the sensor–morphine complex. By utilizing this fluorescence quenching sensor, the chemo-selective detection of morphine becomes highly feasible, encompassing a linear range from 0.008 to 40 ppm with an impressive limit of detection of 8 ppb. Consequently, this molecular probe demonstrates a successful application in determining trace amounts of morphine within urine, yielding satisfactory analytical results. The study also explores the effect of several variables on the sensor's response and optimizes the detection of morphine in urine using a response surface methodology with a central composite design. [ABSTRACT FROM AUTHOR]

Supplementary cementitious materials are beneficial in improving performance and lessening the cement consumption with highly lessening CO2 emission. Many researchers used blast furnace slag, bentonite, and active limestone separately or two of them together to improve the performance of cementing materials, however, it is not well known how all react together in cement composite materials. So, the present study used modeling and optimizing the replacement of blast furnace slag, raw bentonite, and active limestone each by the doses of 0 to 20% to maximize strength and minimize the fresh bulk density of cementing materials by central composite design-response surface method (CCD-RSM). The results found, the employment of blast furnace slag, bentonite, and active limestone in the cement composite materials generally lessens the early strength compared to the control mixture. However, the replacement of blast furnace slag and active limestone by 20% significantly improves the 28-days compressive strength while employing raw bentonite by 20% reduced compressive strength by 6.45% compared to the control mixture. However, blending raw bentonite with active limestone by half improved the compressive strength. Besides these, the substitution of bentonite and active limestone reduces the fresh bulk density and flexural strength than the control mixture. Generally, the study optimized depending on the criteria of maximizing strength and minimizing fresh density and found the mix design replacement of blast furnace slag 1.01%, raw bentonite 5.30%, and active limestone 20% that improves 28 days compressive strength simultaneously reduces fresh bulk density in addition to replacing more than 54 different optimized design mix results.

Lentinus tigrinus SSB_W2, isolated from Mahabaleshwar in the Western Ghats of Maharashtra, India, was employed to enhance laccase production in solid-state fermentation (SSF). The spectral analysis indicated that the laccase produced by L. tigrinus is a typical yellow laccase, exhibiting no absorption at 600 nm. Notably, this yellow laccase demonstrated exceptional catalytic activity, as confirmed by electrochemical analysis. Four agricultural processing wastes were evaluated as substrates for SSF, and the results showed that L. tigrinus effectively utilized wheat bran. Initial testing by one-factor-at-a-time method showed 3.79-fold increase in yellow laccase production, which subsequently increased to 6.51-fold after Plackett–Burman design. Moreover, employing response surface methodology resulted in 11.87-fold increase (108,472 IU gds−1) in laccase production. The utilization of yellow laccase for the biotransformation of various textile dyes was investigated, and it exhibited the highest degradation efficiency toward Reactive blue 4, a recalcitrant anthraquinone dye, with a rate of 18.36 mg L−1 h−1, for an initial concentration of 1000 mg L−1. [ABSTRACT FROM AUTHOR]

Real textile wastewater (RTWW) poses significant environmental challenges. RTWW typically contains high levels of organic compounds, such as dyes, as well as inorganic substances like salts. These contaminants can harm aquatic life when released into water bodies without appropriate treatment. RTWW was subjected to a series of sequential treatments: exchange resins for removing ions, advanced oxidation with bicarbonate-activated peroxide to degrade organic matter, and a biological treatment based on the Zahn–Wellens test to remove remaining chemical oxygen demand (COD) The advanced oxidation process based on the activation of H2O2 with NaHCO3 (catalyzed with cobalt impregnated on a pillared clay, Co/Al–PILC)) was optimized using central composite design (CCD) and response surface methodology (RSM). After the process integration, reductions in ion concentrations, chemical oxygen demand (COD), and total organic carbon content (TOC) were achieved. Reduced hardness (99.94%) and ions (SO42− and acid black 194 dye of 99.88 and 99.46%, respectively), COD (96.64%), and TOC (96.89%), guaranteeing complete treatment of RTWW, were achieved. Additionally, the biodegradability index of RTWW increased from 0.28 ± 0.01 to 0.90 ± 0.01, and phytotoxicity was reduced, going from a phytotoxic that inhibited the germination of lettuce seeds to a phytostimulant after biological treatment with activated sludge.

Dry reforming of methane (DRM) which utilizes CO2 and CH4, is a more efficient and environmentally friendly syngas production method. However, since the technique is endothermic, catalyst deactivation from sintering and carbon deposition has prevented its industrial implementation. This study investigated the effect of Strontium (Sr) promoter on Ni-based catalyst synthesized on SBA-15 support via the impregnation method. The incorporation of Sr as a promoter has demonstrated distinct advantages, primarily attributed to its remarkable capability to inhibit carbon formation. This property imparts a notable enhancement in the stability of the catalyst, thereby extending its operational lifespan and maintaining consistent catalytic performance. The physicochemical properties of the fresh catalyst were observed by using various characterization techniques such as X-Ray diffraction (XRD) analysis, N2 physisorption analysis, field emission scanning electron microscopy (FESEM), and temperature programmed reduction using hydrogen as the probing gas (TPR-H2). The catalysts were tested in DRM reaction using a tubular fixed bed reactor at 800 °C with an equimolar feed ratio. Overall, 1% Sr promoted Ni/SBA-15 showed enhanced performance having CO2 and CH4 initial conversions of 88.5% and 96.5%, respectively while remaining stable for 320 min on stream. Furthermore, the predicted optimal condition was 713.73 °C and a feed gas ratio (CH4:CO2) of 1.12, with CO2 and CH4 conversion rates of 69.59% and 84.83%, respectively, resulting in an H2:CO ratio of 1.00. Slight differences from the predicted values were considered insignificant, validating the Srb catalyst at a 95% confidence level with a 5% likelihood of error in the RSM model.

The unique physicochemical properties of magnesium amino clay nanoparticles (MgAC-NPs) tends to be beneficial in the application as a co-additive in treating microalgae. Also, MgAC-NPs can create oxidative stress in the environment, concurrently elective control bacteria in mixotrophic culture, and stimulate CO2 biofixation. The condition of the cultivation of newly isolated strains, Chlorella sorokiniana PA.91, was optimized for the first time for MgAC-NPs at various temperatures and light intensities in the culture medium of municipal wastewater (MWW) by central composite design in the response surface methodology (RSM-CCD). This study examined synthesized MgAC-NP with their FE-SEM, EDX, XRD, and FT-IR characteristics. The synthesized MgAC-NPs were naturally stable, cubic shaped, and within the size range of 30–60 nm. The optimization results show that at culture conditions of 20 °C, 37 μmol m−2 s−1, and 0.05 g L−1, microalga MgAC-NPs have the best growth productivity and biomass performance. Maximum dry biomass weight (55.41%), specific growth rate (30.26%), chlorophyll (81.26%), and carotenoids (35.71%) were achieved under the optimized condition. Experimental results displayed that C.S. PA.91 has a high capacity for lipid extraction (1.36 g L−1) and significant lipid efficiency (45.1%). Also, in 0.2 and 0.05 g L−1 of the MgAC-NPs, COD removal efficiency 91.1% and 81.34% from C.S. PA.91 showed, respectively. These results showed the potential of C.S. PA.91-MgAC-NPs for nutrient removal in wastewater treatment plants and their quality as sources of biodiesel. [ABSTRACT FROM AUTHOR]

[Display omitted] • Catalyst derived from waste − Angulyagra oxytropis and Bellamya crassa snail shells. • The synthesized catalyst is nano crystalline in structure and mesoporous. • CCD-RSM optimized biodiesel synthesis from waste cooking oil. • Maximum biodiesel yield of 95.91% achieved using Bellamya crassa catalyst. • Catalyst reused up to four cycle with biodiesel conversion above 83%. In the present study, labuk tharoi (Angulyagra oxytropis), and ningkhabi tharoi (Bellamya crassa) were utilized to produce CaO catalyst for biodiesel production using waste cooking oil (WCO). The snail shells were calcined at a temperature of 800−1000℃ for 4 h and characterized using XRD, FTIR, BET, SEM, and EDX analysis. Central composite design-response surface methodology (CCD-RSM) was employed, and the input parameters considered for optimization were (i) catalyst calcination temperature (800−1000℃), (ii) methanol: oil ratio (molar) (6:1−12:1), (iii) catalyst loading (3−7 wt.%), and (iv) reaction temperature (55−75℃). A quadratic regression model was aliased by CCD-RSM with R 2 values of 0.9291 and 0.976 for waste cooking oil methyl ester-labuk tharoi (WCOME-LT), and waste cooking oil methyl ester-ningkhabi tharoi (WCOME-NT) models indicating a good fit. An optimum biodiesel yield of (95.87, 95.91 %) was obtained at catalyst calcination temperature (891, 886℃), methanol to oil molar ratio (9.89:1, 9.67:1), catalyst loading weight % (7, 7 wt.%), and reaction temperature (75, 75℃) for WCOME-LT and WCOME-NT model respectively. The calcination temperature has a major impact on the biodiesel yield as per analysis of variance. The catalyst reusability was up to four cycles with a biodiesel yield of more than 83 %. [ABSTRACT FROM AUTHOR]

This research aims to treat toxic methylene blue (MB) dye from contaminated water due to its harmful effects on human health and the environment. For this purpose, xanthan gum-based hydrogel was prepared by grafting acrylamide (AAm) and 2-acrylamido-2-methly propane sulfonic acid (AMPS) onto xanthan gum (XG) with methylene bis acrylamide (MBA) as a crosslinking agent. With the introduction of sulfonate and carboxylate groups, the XG molecules were rearranged with better regularity, and based on rheology analysis; higher mechanical stability was approved. The central composite design (CCD) experimental design was used to evaluate the main and interaction effects of the independent hydrogel composition parameters (AMPS, AAm, and MBA concentration) and to derive a model from predicting optimization of the hydrogel composition to remove methylene blue (MB) dye. Accordingly, the concentrations of AAm (6 wt%), AMPS (4.09 wt%), and MBA (0.12 wt%) was found to be the optimum amount for the prepared pH-sensitive adsorbent to remove 98.85% of MB from an aqueous solution using CCD-RSM optimization. The fabrication of hydrogel and its interaction with monomers was specified by FTIR, TGA, rheology, FESEM, and ESEM techniques. The high porosity of hydrogel when swelled was confirmed based on ESEM images. A pseudo-first-order model and Langmuir isotherms best described the adsorption kinetics and adsorption equilibrium, respectively. The maximum equilibrium adsorption capacity of MB was obtained at 384.62 mg/g. The thermodynamic parameters indicated that the adsorption is endothermic and a process that increases irregularity. The hydrogel was regenerated for up to five cycles without significant reduction. [Display omitted] • The cross-linked hydrogel of XG and poly(AMPS-co-AAm) were synthesized. • Xanthan-g-p(AMPS-co-AAm) was used for the adsorption of MB dye-contaminated water. • CCD-RSM approach was used to evaluate and optimize the main and interaction effects. • Hydrogel characterization was done using FTIR, TGA, rheology, and ESEM techniques. [ABSTRACT FROM AUTHOR]

Yifan Wang,1– 3 Si Chen,1– 3 Xin Yang,1– 3 Shuang Zhang,1– 3 Chunying Cui1– 3 1Department of Pharmaceutics, School of Pharmaceutical Sciences, Capital Medical University, Beijing, People’s Republic of China; 2Engineering Research Center of Endogenous Prophylactic of Ministry of Education of China, Beijing, People’s Republic of China; 3Beijing Area Major Laboratory of Peptide and Small Molecular Drugs, Beijing, People’s Republic of ChinaCorrespondence: Chunying Cui; Shuang ZhangDepartment of Pharmaceutics, School of Pharmaceutical Science, Capital Medical University, Number 10 Youanmenwai Street, Fengtai, Beijing, 100069, People’s Republic of ChinaTel +86-10-8391-1668; +86-10-8391-1673Fax +86-10-8391-1668; +86-10-8391-1673Email ccy@ccmu.edu.cn; zshuang@ccmu.edu.cnBackground: siRNA brings hope for cancer therapy. However, there are many obstacles for application of siRNA in clinical. Because of the excellent biocompatibility, non-toxicity and non-immunogenicity of bovine serum albumin (BSA), BSA-based nanoparticles have been widely designed as a drug carrier system.Methods: The optimal formula for BSA NPs preparation was investigated by central composite design response surface methodology (CCD-RSM), BSA-based survivin-siRNA delivery system (BSA NPs/siRNA) was characterized by dynamic light scattering, atomic force microscope, transmission electron microscope and Bradford method. The in vitro anti-tumor effect and mechanism of BSA NPs were investigated by confocal microscopic imaging, MTT assay, RT-qPCR and ELISA analysis. Moreover, the anti-tumor effect, distribution and biosafety of BSA NPs were studied in vivo.Results: The optimal formula for BSA NPs was settled to be 20 mg/mL for BSA concentration, 9 for pH value, 136% for crosslinking degree and 1.6 mL/min for speed of ethanol addition. BSA NPs/siRNA could remain stable at 4°C for 4 weeks and protect siRNA from degradation by RNase A. Besides, BSA NPs/siRNA could maintain a sustained release of siRNA and promote the uptake of siRNA significantly. The survivin-mRNA level and the survivin-protein level were decreased by 55% ± 1.6% and 54% ± 1.6% separately. The in vivo tumor inhibition results suggested that the tumor inhibition rate of BSA NPs/siRNA-treated group was 54% ± 12% and was similar with that of DOX-treated group (57% ± 9.2%, P > 0.05). The biosafety results confirmed that BSA NPs/siRNA could not induce significant damages to the main organs and blood in vivo.Conclusion: These results demonstrated that CCD-RSM was an effective tool for preparation analysis, and the BSA NPs/siRNA was a promising system for siRNA-based gene therapy.Keywords: bovine serum albumin, BSA, CCD-RSM, survivin-siRNA, nanoparticles, RNAi

The removal of Cd (II) ions by rice husk biochar as adsorbent was evaluated through batch study. Activated biochar was prepared using the physicochemical activation method. Preparation was consisting of pre-impregnation of NaOH and nitrogen (N2) pyrolysis. The Influence of preparation parameters which were chemical impregnation (NaOH: RH), pyrolysis temperature, and pyrolysis time on biochar yield, cadmium removal rate, and adsorption capacity on cadmium ions was investigated. A quadratic model for correlating biochar preparation variables with biochar production, cadmium removal rate, and adsorption capability was built according to central composite design (CCD). The experimental results revealed that pyrolysis temperature and heating time are important factors that affect the yield of biochar and positively affect Cadmium's removal rate and adsorption capacity. The impregnation ratio positively impacted Cadmium removal and adsorption capacity, and it did not affect biochar yield. The optimal biochar was obtained using 458 ◦C temperature, 120 min reaction time, and 3 NaOH impregnation ratio, resulting in 34.5% of biochar yield, 72% of cadmium removal, and 17.8 mg/g of adsorption capacity on Cadmium.

SARS-CoV-2 (or COVID-19) has become a global risk and scientists are attempting to investigate antiviral vaccine. Berberis are important plants due to the presence of bioactive phytochemicals, especially berberine from the protoberberine group of benzylisoquinoline and recent studies have shown its potential in treating COVID-19. B. lycium Royle growing in subtropical regions of Asia had wide applications in Indian system of medicine. Rapid determination and novel optimisation method for berberine extraction has been developed by Soxhlet extraction utilising central composite design-response surface methodology (CCD-RSM). Berberine was detected by high-performance liquid chromatography (HPLC), and the highest yield (13.39%) was obtained by maintaining optimal extraction conditions i.e., extraction time (7.28 hrs), ethyl alcohol (52.21%) and solvent to sample ratio (21.78 v/w). Investigation of two geographic regions (Ramnagar and Srinagar) showed high berberine content in lower altitude. This novel optimisation technique has placed berberine as a potential candidate for developing pharmaceutical products for human health care. [ABSTRACT FROM AUTHOR]

The first aim of this study was to synthesize and characterize reed-based-beads (BBR), an enhanced adsorbent from Tunisian reed. The second purpose was to evaluate and optimize the BBR efficiency for the simultaneous removal of oxytetracycline (OTC) and cadmium (Cd(II)), using central composite design under response surface methodology. The third goal was to elucidate the biosorption mechanisms taking place. It was shown that under optimum conditions (4.19 g L−1 of BBR, 165.54 μmol L−1 of OTC, 362.16 μmol L−1 of Cd(II), pH of 6, and 25.14-h contact time) the highest adsorption percentages (63.66% for OTC and 99.99% for Cd(II)) were obtained. It was revealed that OTC adsorption mechanism was better described by Brouers-Sotolongo fractal equation, with regression coefficient (R2) of 0.99876, and a Person's chi-square (χ2) of 0.01132. The Weibull kinetic equation better explained Cd(II) biosorption (R2 = 0.99959 and χ2 = 0.00194). FTIR and isotherm studies confirmed that the BBR surface was heterogeneous, and that adsorption mechanisms were better described by the Freundlich/Jovanovich equation (R2 = 0.99276 and χ2 = 0.04864) for OTC adsorption, and by the Brouers-Sotolongo model (R2 = 0.9851 and χ2 = 0.77547) for Cd(II) biosorption. Overall results indicate that, at last, the BBR lignocellulosic biocomposite beads could be considered as cost-effective and efficient adsorbent, which could be of socioeconomic and environmental relevance. [ABSTRACT FROM AUTHOR]

(1) Background: This study is designed to extract the bioactive compounds from beetroot peel for future use in the food industry. (2) Methods: Spectrophotometry techniques analyzed the effect of conventional solvent extraction on betalains and polyphenolic compounds from beetroot peels. Several treatments by varying for factors (ethanol and citric acid concentration, temperature, and time) were applied to the beetroot peel samples. A Central Composite Design (CCD) has been used to investigate the effect of the extraction parameters on the extraction steps and optimize the betalains and total polyphenols extraction from beetroot. A quadratic model was suggested for all the parameters analyzed and used. (3) Results: The maximum and minimum variables investigated in the experimental plan in the coded form are citric acid concentration (0.10-1.5%), ethanol concentration (10-50%), operating temperature (20-60 °C), and extraction time (15-50 min). The experimental design revealed variation in betalain content ranging from 0.29 to 1.44 mg/g DW, and the yield of polyphenolic varied from 1.64 to 2.74 mg/g DW. The optimized conditions for the maximum recovery of betalains and phenols were citric acid concentration 1.5%, ethanol concentration 50%, temperature 52.52 °C, and extraction time 49.9 min. (4) Conclusions: Overall, it can be noted that the extraction process can be improved by adjusting operating variables in order to maximize the model responses. [ABSTRACT FROM AUTHOR]

Antibiotic shock may potentially impact the performance of promising microalgae-nitrifying bacteria consortia (MNBC) processes. This study investigated physiological behaviors of MNBC under sulfamethoxazole (SMX) shock (mg/L level) and verified a light regulating strategy for improving process performance. Results showed that SMX shock did not affect ammonium removal but caused nitrite accumulation, resulting from combined effects of excessive reactive oxidative species (ROS) production, inhibited microalgal photosynthetic activity, upregulated expressions of amoA and hao , and downregulated expression of nxrA. Moreover, high ammonium concentration aggravated nitrite accumulation and reduced ammonium removal owing to significantly reduced dissolved oxygen (DO). Increasing light intensity enhanced microalgal photo-oxygenation and promoted expressions of all nitrification-related genes, thus improving ammonium removal and alleviating nitrite accumulation. A central composite design coupled with response surface methodology (CCD-RSM) further demonstrated the negative impacts of SMX shock and high ammonium on MNBC and the effectiveness of the light regulation in maintaining stable process performance. This study provides theoretical basis for physiological responses and regulatory strategy of the MNBC process facing short-term antibiotic shock. [Display omitted] • SMX shocking caused nitrite accumulation by downregulating nxrA expression. • High ammonium aggravated nitrite accumulation and impaired ammonium removal. • Increasing light intensity enhanced ammonium removal performance. • CCD-RSM verified that light regulatory strategy promoted MNBC performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • The BHP@Bi 2 O 3 anode was successfully synthesized using electrodeposition method. • The BHP@Bi 2 O 3 composite exhibited enhanced photoelectrocatalytic activity and stability. • The predominant reactive species for OG dye degradation was confirmed to be O 2 – radicals. • The mechanism was proposed based on the synergistic effect between Bi 2 O 3 and BHP. In this study, we synthesized a bilayer film consisting of BaHPO 4 (BHP) and Bi 2 O 3 through the electrodeposition technique. The produced anode was subjected to characterization using cyclic voltammetry to clarify the deposition reactions. Subsequent to this, structural and morphological analyses were conducted utilizing X-ray diffraction alongside scanning electron microscopy, coupled with energy-dispersive X-ray spectroscopy. Additionally, UV–vis diffuse reflectance spectroscopy was employed to determine the bandgap energies of both semiconductors. Following an electrochemical characterization using linear sweep voltammetry (LSV), electrochemical impedance spectroscopy (EIS), and Mott-Schottky (MS) measurements, the photoanode was employed for the electro-degradation of the anionic dye Orange G (OG), varying key degradation parameters such as current density, pollutant concentration, supporting electrolyte concentration, and pH using the CCD-RSM experimental design method. A degradation efficiency of 98% was achieved within a 20-minute timeframe. Photoelectrocatalytic tests under UV irradiation reduced the degradation time from 20 to 6 min, with a degradation rate of 99%. Additionally, under the same conditions, the BHP@Bi 2 O 3 photoanode exhibited good stability, enduring up to 11 cycles of use. [ABSTRACT FROM AUTHOR]

Polyaniline/polycarbonates (PANI/PC) nanofibers composite were synthesized chemically for the removal of Cr(VI) from an aqueous solution. The nanofibers were characterized using X-ray diffraction (XRD) and scanning electron microscopy (SEM). Central composite design with response surface methodology (CCD-RSM) was used for optimized some factors such as pH, the weight of PANI/PC, temperature, and contact time. The best removal (98.8%) occurred under pH 2, the weight of PANI/PC 0.05, temperature 25°C, and contact time 60 min. The high value of R² and minimized value of error functions (χ², χ² red, and G²) indicated that the Freundlich isotherm model was found to be the better model rather than Langmuir and Temkin models. According to the results of XRD and SEM, affected factors using CCD-RSM, isotherm model, and error functions were involved in the adsorption process. All the results indicated that PANI/PC nanofibers composite could be used as a promising surface for the removal of Cr(VI). [ABSTRACT FROM AUTHOR]

[Display omitted] • Study of Ce-doped mesoporous ZnO prepared materials proprieties. • 2% Ce–ZnO is the most optimal photocatalyst for the MO-photodegradation. • Optimization of MO-photodegradation yield using central composite design in RSM. • The catalyst weight is the most important parameter in photocatalytic reaction. This paper investigates a new modeling approach of central composite design (CCD) in Response Surface methodology (RSM) for the optimization of methyl orange (MO) photodegradation based to the prepared materials under UV–vis irradiation. Mesoporous zinc oxide (ZnO) have been synthesized at different cerium (Ce) contents (2, 5 and 7 wt%) through a single step sol gel method. Subsequently, cerium nanoparticles (CeNPs) have been impregnated on mesoporous ZnO. The physico-chemical characteristics of each catalyst are described through several approaches. The photocatalytic activity of the prepared catalysts shows that CeNPs enhance the photocatalytic performance of ZnO at 2 wt% Ce content. MO photodergadation processes of the optimal catalyst can be mathematically described as a function of pH-solution, catalyst dosage and MO concentration being modeled by a CCD-RSM. Based on a statistical modeling (quadratic regression) and an optimization process (ANOVA analysis), the optimum conditions were achieved for pH of solution of 5.58, MO concentration of 20.72 mg L−1and catalyst dosage of 0.63 g L−1 which allowed reaching 100% of photodegradation. Overall, the value of the adjusted coefficient of determination (R2 = 0.9901) indicates that the considered model was quite suitable and that the selected CCD-RSM was successful in optimizing the photodegradation conditions of MO. [ABSTRACT FROM AUTHOR]

Chitinase is responsible for the breaking down of chitin to N-acetyl-glucosamine units linked through (1–4)-glycosidic bond. The chitinases find several applications in waste management and pest control. The high yield with characteristics thermal stability of chitinase is the key to their industrial application. Therefore, the present work focuses on parameter optimization for chitinase production using fungus Thermomyces lanuginosus MTCC 9331. Three different optimization approaches, namely, response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) were used. The parameters under study were incubation time, pH and inoculum size. The central composite design with RSM was used for the optimization of the process parameters. Further, results were validated with GA and ANN. A multilayer feed-forward algorithm was performed for ANN, i.e., Levenberg–Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient. The ANN predicted values gave higher chitinase activity, i.e., 102.24 U/L as compared to RSM-predicted values, i.e., 88.38 U/L. The predicted chitinase activity was also closer to the observed data at these levels. The validation study suggested that the highest activity of chitinase as predicted by ANN is in line with experimental analysis. The comparison of three different statistical approaches suggested that ANN gives better optimization results compared to the GA and RSM study. [ABSTRACT FROM AUTHOR]

Budesonide is a glucocorticoid for the treatment of ulcerative colitis (UC). The current study aims to develop a thermosensitive in situ and adhesive gel for rectal delivery of budesonide. HPMC K4M was selected as the adhesive agent based on the adhesive force and the effect on gel performance. The formulation of gel was optimized by using the central composite design-response surface methodology (CCD-RSM); a mathematical model was successfully developed to predict desired formulations as well as to analyze relationships between the amount of Pluronic F-127, Pluronic F-68, and HPMC K4M and the performances of gel. Based on CCD-RSM, a thermosensitive in situ and adhesive gel consisting of 0.002% budesonide, 0.74% HPMC, 4.87% F-68, and 19.0% F-127 was developed. Furthermore, the in vivo behavior of gel was evaluated in Sprague-Dawley rats. In comparison with budesonide solution, rectal administration of budesonide gel at 0.1 mg/kg in rats showed relative bioavailability of 230% with significant increase in rectum uptake. [ABSTRACT FROM AUTHOR]

(1) Background: This study is designed to extract the bioactive compounds from beetroot peel for future use in the food industry. (2) Methods: Spectrophotometry techniques analyzed the effect of conventional solvent extraction on betalains and polyphenolic compounds from beetroot peels. Several treatments by varying for factors (ethanol and citric acid concentration, temperature, and time) were applied to the beetroot peel samples. A Central Composite Design (CCD) has been used to investigate the effect of the extraction parameters on the extraction steps and optimize the betalains and total polyphenols extraction from beetroot. A quadratic model was suggested for all the parameters analyzed and used. (3) Results: The maximum and minimum variables investigated in the experimental plan in the coded form are citric acid concentration (0.10–1.5%), ethanol concentration (10–50%), operating temperature (20–60 °C), and extraction time (15–50 min). The experimental design revealed variation in betalain content ranging from 0.29 to 1.44 mg/g DW, and the yield of polyphenolic varied from 1.64 to 2.74 mg/g DW. The optimized conditions for the maximum recovery of betalains and phenols were citric acid concentration 1.5%, ethanol concentration 50%, temperature 52.52 °C, and extraction time 49.9 min. (4) Conclusions: Overall, it can be noted that the extraction process can be improved by adjusting operating variables in order to maximize the model responses.

The L-lysine is one of the most important essential amino acid used in food and pharmaceutical industries. The present investigation was conducted to optimize the L-lysine production by Corynebacterium glutamicum (NCIM 2168). The production parameters such as the temperature, pH and glucose concentration (g/l) were optimised and evaluated by simulation method to develop a suitable model. The experimental design was done using central composite design (CCD). Total 20 set of experiments were performed according to the CCD. The factors and their responses were analysed by using the statistical tools: response surface methodology (RSM) and artificial neural network (ANN) linked with genetic algorithm (GA). The predicted optimum production of L-lysine was 19.003 g/l and 28.363 g/l by CCD-RSM and ANN-GA respectively. During validation by GA under optimized conditions, the L-lysine production was found to be 27.25 ± 1.15 g/l, which was significantly high than that obtained using CCD-RSM optimization method. The ANN coupled with GA was found to be a powerful tool for optimizing production parameters with high level of accuracy. This technique may be used for other fermentation products to optimize the important process parameters before scaling up the process to industrial level. [ABSTRACT FROM AUTHOR]

Abstract The white laccase was produced from Myrothecium verrucaria ITCC-8447 under submerged fermentation. The media components were optimized by response surface methodology (CCD-RSM). The nutritional components (glucose and peptone) and physical parameters (pH and temperature) were optimized by response surface methodology for enhanced laccase production by Myrothecium verrucaria ITCC-8447. The enzyme activity under optimum condition exhibited 1.45 fold increases in laccase activity. The white laccase was subjected to ion exchange chromatography with 6 fold purification. The molecular weight of white laccase was ~63–75 kDa as estimated by SDS-PAGE followed by the activity staining with ABTS where green bands confirmed the presence of laccase. The enzyme was stable over an alkaline pH range of 7–9 and the temperature range of 30–40 °C. The characterization of white laccase was done by CD spectra, UV–visible absorption, FTIR and XRD. The K m and V max values of the purified laccase were 2.5 mM and1818.2 μmol/min/L. The delignification capability of the white laccase was determined by reduction in Kappa number (58.8%) and Klason lignin (64.7%) of wheat straw after 12 h of incubation. Further the delignification was confirmed FTIR and XRD. Graphical abstract Unlabelled Image Highlights • The process optimization of white laccase using CCD-RSM from Myrothecium verrucaria ITCC-8447 • Purification of white laccase and its characterization by CD, UV-spectra, FTIR and XRD • First report on white laccase for the efficient delignification of agroresidues: a step towards "Green and Clean Environment" [ABSTRACT FROM AUTHOR]

This study focuses on the preparation of a novel photoanode by combining BAHPO 4 (BHP) and ZnO, aiming to harness their synergistic impact on degrading Rhodamine B dye (RhB). Characterization involved X-ray diffraction (XRD), SEM-EDX morphological analysis, FT-IR vibrational analysis, and UV-Vis DRS optical analysis. Both semiconductors exhibited band gaps in the UV region, with ZnO at 3.1 eV and BHP at 3.9 eV. Electrochemical analyses, including Mott-Schottky (MS), open circuit potential (OCP), photocurrent (PT), and linear sweep voltammetry (LSV), were conducted. The electrocatalytic investigation of BHP@ZnO was optimized using statistical CCD-RSM analysis, identifying key parameters for improved degradation efficiency: applied current density, pollutant concentration, supporting electrolyte concentration, and pH. Remarkably, degradation efficiency achieved 100% within 30 min. Furthermore, photoelectrocatalytic experiments under UV light reduced degradation time to 8 min. Examination of trap states at the n-n junction of BHP@ZnO unveiled insights into the degradation mechanism, pinpointing •O 2 - as the primary radicals accountable. The photoanode demonstrated sustained stability and repeatability, showcasing its potential as a dependable and effective tool for RhB degradation. this study presents a promising approach utilizing BHP and ZnO within a novel photoanode, highlighting their synergistic effect in degrading RhB and contributing to the field of advanced photocatalytic materials. [Display omitted] • The BHP@ZnO photoelectrode was successfully synthesized and characterized. • The BHP@ZnO composite exhibited enhanced electrocatalytic and photo-electrocatalytic activity and stability. • The predominant reactive species for RhB dye degradation was confirmed to be •O 2 -radicals. • The mechanism was proposed based on the synergistic effect between ZnO and BHP. [ABSTRACT FROM AUTHOR]

Abstract Triclosan (TCS) is a well-known emerging contaminant got wide use in daily use products of domestic purpose, which provides the way to enter the ecological cycle, and is preferably detected in sewage treatment plants. In this study, TCS degrading bacteria (TDB) was isolated and identified from a wastewater treatment plant at the National Institute of Technology-Karnataka, Surathkal (NITK), India. The isolate was reported as Pseudomonas s train by performing 16S RNA Sequencing using BLAST analysis. Bacterial growth depends upon several environmental factors. Hence its growth optimization was carried out by response surface method (RSM) based central composite design (CCD) and validated by the artificial neural network (ANN). The Parameters or inputs used for optimization are pH, time (days), agitation (rpm) and sorbent dosage (μg/L). Experiments were conducted in batch mode to achieve optimum growth of bacteria based on RSM trial runs. The RSM model predictions were in better agreement with the experimental results and it was confirmed by ANN. The deviation lies within ±10% with experimental results compared to ANN for maximum trials. Hence optimized parameters were established and arrived at pH - 7, time - 13 days, agitation - 150 rpm, dosage - 1.5 μg/L presented 69% removal of TCS. Minimum inhibitory assay of isolated strain was conducted to identify the degradation capacity of TCS and it was found out to be lesser than 0.025 mg of TCS. Later the strain was immobilized in two different matrices. One is biopolymer extracted from cellulose (Water Hyacinth) along with sodium alginate and second is free bacteria with sodium alginate and was made in the form of beads. The removal of TCS by TDB-cellulose-alginate (BCA) and TDB-Alginate (BA) beads were 58% and 30% respectively. Hence it was concluded that BCA beads showed effective removal compared to BA beads. Therefore, isolate can degrade TCS when the concentration ranges from 0.025 mg/L to 5.5 ng/L. Highlights • Pseudomonas Sp. was isolated and identified from the domestic wastewater. • An Optimized condition of identified strain's growth was carried out by CCD-RSM and ANN. • Isolate was immobilized into biopolymer; TDB-Alginate (BA) and TDB-cellulose-Alginate (BCA). • TCS degradation was obtained experimentally by batch mode for optimized condition. • Effective removal was observed by BCA for very low concentration of TCS. [ABSTRACT FROM AUTHOR]

Graphical abstract Abstract The objective of this present study was to develop and evaluate the triptolide-loaded nanostructured lipid carriers (TPL-NLCs) for transdermal drug delivery system (TDDS). TPL-NLCs was prepared with emulsification technique and optimized by central composite design of a response surface methodology (CCD-RSM). The optimized TPL-NLCs were spherical and physically stable with the average size of 139.6.0 ± 2.53 nm and Zeta potential of −36.03 ± 2.41 mV. The encapsulation efficiency and drug loading were 97.15% ± 9.46 and 10.35% ± 1.12, respectively. Moreover, the in vitro release study showed that TPL-NLCs had a sustained release profiles and the in vitro penetration study indicated that TPL-NLCs could effectively penetrate into skin. Besides, the methodology of skin-blood synchronous microdialysis was established to evaluate the pharmacokinetics of TPL-NLCs in vivo and the results displayed that the TPL concentration in skin was higher than that in blood. And TPL-NLCs presented a remarkable effect of decreasing knee edema, inhibiting inflammation by regulating the levels of TNF-α, IL-1β and IL-6, which indicated that TPL-NLCs was a promising topical administration in treatment of edema and inflammation associated with rheumatoid arthritis (RA). [ABSTRACT FROM AUTHOR]

Excessive phosphorus (P) and ammonia nitrogen (NH 3 –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 NH 3 –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 NH 3 –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 NH 3 –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. [Display omitted] • The optimal conditions of the Ce-bentonite adsorption process were predicted by CCD-RSM and GA-BPNN methods, respectively. • The optimization efficiency of GA-BPNN was better than that of CCD-RSM. • The GA-BPNN optimized conditions are useful as a guide for the study of the adsorption performance of Ce-bentonite. The GA-BPNN provides a new method for studying the adsorption performance under optimized optimal conditions. [ABSTRACT FROM AUTHOR]

Nowadays, Machine Learning (ML) techniques have become one of the most widely used engineering tools due to their numerous advantages, including their continuous improvement. This study proposes a smart soft sensor using various ML algorithms to control and predict the Coagulation and Flocculation Process (CFP). Optimizing and predicting the behaviour of a CFP is difficult due to its non-linear and complex behaviour. Therefore, ML computations is a proper method to overcome this challenge. However, one of the challenges of ML studies is the lack of sufficient data which we overcome by using an 8-year database of experiments. For prediction, this study compares different ML methods, including Random Tree, Random Forest (RF), Artificial Neural Networks (ANN), Quinlan's M5 algorithm with regression function (M5P), Linear Regression (LR), Simple LR, Gaussian method, Decision Stump method, Smola and Scholkopf's Sequential Minimal Optimization algorithm with LR (SMOreg), and the Adaptive Neuro-Fuzzy Inference System (ANFIS). Also, for optimization of the studied system, Central Composite Design designed the experimental data with the Response Surface Methodology (CCD-RSM). The most significant factors in turbidity removal are related to FeCl3 dosage, and slow mixing speed with < 0.0001 and 0.005 P-values. The present research findings show that the maximum removal efficiency of 92% is predicted using CCD-RSM under the optimal condition. In addition, ANFIS and RF models with R2 of 0.96 and 0.92, have shown the highest accuracy levels for removing water turbidity. Finally, a Petri-Net model establishes a Conceptual model to intelligently conduct managerial insights for water treatments. [Display omitted] [ABSTRACT FROM AUTHOR]

The removal of Cd (II) ions by rice husk biochar as adsorbent was evaluated through batch study. Activated biochar was prepared using the physicochemical activation method. Preparation was consisting of pre-impregnation of NaOH and nitrogen (N 2) pyrolysis. The Influence of preparation parameters which were chemical impregnation (NaOH: RH), pyrolysis temperature, and pyrolysis time on biochar yield, cadmium removal rate, and adsorption capacity on cadmium ions was investigated. A quadratic model for correlating biochar preparation variables with biochar production, cadmium removal rate, and adsorption capability was built according to central composite design (CCD). The experimental results revealed that pyrolysis temperature and heating time are important factors that affect the yield of biochar and positively affect Cadmium's removal rate and adsorption capacity. The impregnation ratio positively impacted Cadmium removal and adsorption capacity, and it did not affect biochar yield. The optimal biochar was obtained using 458 ◦C temperature, 120 min reaction time, and 3 NaOH impregnation ratio, resulting in 34.5% of biochar yield, 72% of cadmium removal, and 17.8 mg/g of adsorption capacity on Cadmium. [ABSTRACT FROM AUTHOR]

Pomelo peel-derived essential oils have been gaining popularity due to greater demand for stress relief therapy or hair care therapy. In this study, we first performed optimization of parameters in the pomelo essential oil extraction process on a pilot scale to gain better insights for application in larger scale production. Then extraction kinetics, activation energy, thermodynamics, and essential oil quality during the extraction process were investigated during the steam distillation process. Three experimental conditions including material mass, steam flow rate, and extraction time were taken into consideration in response surface methodology (RSM) optimization. The optimal conditions were found as follows: sample weight of 422 g for one distillation batch, steam flow rate of 2.16 mL/min and extraction time of 106 min with the coefficient of determination R2 of 0.9812. The nonlinear kinetics demonstrated the compatibility of the kinetic model with simultaneous washing and unhindered diffusion with a washing rate constant of 0.1515 min−1 and a diffusion rate constant of 0.0236 min−1. The activation energy of the washing and diffusion process was 167.43 kJ.mol−1 and 96.25 kJ.mol−1, respectively. The thermodynamic value obtained at the ΔG° value was −35.02 kJ.mol−1. The quality of pomelo peel essential oil obtained by steam distillation was characterized by its high limonene content (96.996%), determined by GC-MS. [ABSTRACT FROM AUTHOR]

Bioemulsifier and exopolysaccharides are industrially important biomolecules produced by microorganisms using green technology. They have applications in food, biomedical, pharmaceutical and cosmetic industries and hence high yield of both products becomes necessary. The current study showed that Brevibacillus borstelensis has a potential to produce bioemulsifier and exopolysaccharide simultaneously but yield of both products is limited. In this study, CCD-RSM has been used as experimental design to increase concentration of both products. Concentrations of glucose, monosodium glutamate, yeast extract and magnesium sulphate were process variables and concentrations of bioemulsifiers, exopolysaccharides and biomass were responses. 30 experimental runs were performed and the models from CCD were optimized by genetic algorithm and NSGA. The results from modelling and optimization techniques were compared along with validation of models. The predicted values from optimization techniques were better than experimental values. The study concluded that NSGA is most suitable to optimize multiple responses simultaneously when compared to RSM and genetic algorithm. The optimum conditions for production were 22 g/l glucose, 14 g/l monosodium glutamate, 6 g/l yeast extract and 0.6 g/l magnesium sulphate with maximum yield of 6.1, 17.6 and 2.8 g/l bioemulsifier, exopolysaccharide and biomass, respectively. Knowledge of optimum concentrations of carbon and nitrogen source will help to utilize industrial and agricultural wastes for production of both products. They have applications in environmental bioremediation by clearing oil spills. Bioemulsifiers also help in heavy metal removal from hazardous waste. Hence this will result in environmental bioremediation by utilization of wastes by employing products generated from wastes. • Green production of bioemulsifier and exopolysaccharide simultaneously. • RSM, genetic algorithm and NSGA were used as optimization tools. • Four process variables and four responses were studied to maximize production. • All techniques resulted in maximum yield of 6.1, 17.6 and 2.8 g/l bioemulsifier, exopolysaccharide and biomass, respectively. • NSGA was found to be the most suitable optimization tool. [ABSTRACT FROM AUTHOR]

Cadmium is one of the most hazardous metals in the environment, even when present at very low concentrations. This study reports the systematic development of Kenaf fiber biochar as an adsorbent for the removal of cadmium (Cd) (II) ions from water. The adsorbent development was aided by an optimization tool. Activated biochar was prepared using the physicochemical activation method, consisting of pre-impregnation with NaOH and nitrogen (N2) pyrolysis. The influence of the preparation parameters—namely, chemical impregnation (NaOH: KF), pyrolysis temperature, and pyrolysis time on biochar yield, removal rate, and the adsorption capacity of Cd (II) ions—was investigated. From the experimental data, some quadratic correlation models were developed according to the central composite design. All models demonstrated a good fit with the experimental data. The experimental results revealed that the pyrolysis temperature and heating time were the main factors that affected the yield of biochar and had a positive effect on the Cd (II) ions' removal rate and adsorption capacity. The impregnation ratio also showed a positive effect on the specific surface area of the biochar, removal rate, and adsorption capacity of cadmium, with a negligible effect on the biochar yield. The optimal biochar-based adsorbent was obtained under the following conditions: 550 °C of pyrolysis temperature, 180 min of heating time, and a 1:1 NaOH impregnation ratio. The optimum adsorbent showed 28.60% biochar yield, 69.82% Cd (II) ions removal, 23.48 mg/g of adsorption capacity, and 160.44 m2/g of biochar-specific area. [ABSTRACT FROM AUTHOR]

Oily-biological sludge (OBS) generated from petroleum refineries has high toxicity. Therefore, it needs an appropriate disposal method to reduce the negative impacts on the environment. The anaerobic co-digestion process is an effective method that manages and converts organic waste to energy. For effective anaerobic digestion, a co-substrate would be required to provide a suitable environment for anaerobic bacteria. In oily-biological sludge, the carbon/nitrogen (C/N) ratio and volatile solids (VS) content are very low. Therefore, it needs to be digested with organic waste that has a high C/N ratio and high VS content. This study investigates the use of sugarcane bagasse (SB) as an effective co-substrate due to its high C/N ratio and high VS content to improve the anaerobic co-digestion process with oily-biological sludge. The sugarcane bagasse also helps to delay the toxicity effect of the methane bacteria. Batch anaerobic co-digestion of oily-biological sludge was conducted with sugarcane bagasse as a co-substrate in twelve reactors with two-liter capacity, each under mesophilic conditions. The interaction effect of a C/N ratio of 20-30 and a VS co-substrate/VS inoculum ratio of 0.06-0.18 on the methane yield (mL CH4/g VSremoved) was investigated. Before the anaerobic digestion, thermochemical pre-treatment of the inoculum and co-substrate was conducted using sodium hydroxide to balance their acidic nature and provide a suitable pH environment for methane bacteria. Design and optimization for the mixing ratios were carried out by central composite design-response surface methodology (CCD-RSM). The highest predicted methane yield was found to be 63.52 mL CH4/g VSremoved, under optimum conditions (C/N ratio of 30 and co-substrate/inoculum ratio of 0.18). [ABSTRACT FROM AUTHOR]

Siamenoside I is a rare mogroside in Siraitia grosvenorii Swingle and has become one of the target ingredients in natural sweetener production. However, the complex structure of siamenoside I has hindered its production in various ways. Here, a yeast cell that produces a specific β-glucosidase for siamenoside I conversion from mogroside V was constructed, and the enzymes were coelectrospun with poly(vinyl alcohol) followed by phenylboronic acid cross-linking to provide potential usage in the batch production process of Siamenoside I. A central composite design (CCD)-response surface methodology (RSM) was used to find the optimum coelectrospinning parameters. The pH stability and sodium dodecyl sulfate tolerance increased for the entrapped enzymes, and positive correlations between the fiber diameter and enzymatic activity were confirmed. The batch process showed an average siamenoside I production rate of 118 ± 0.08 mg L -1 h -1 per gram of fiber. This is the first research article showing specific siamenoside I production on enzyme-loaded electrospun fibers.