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Critical water crisis due to overpopulation, industrialization and urbanization has resulted to the shortfall of providing safe drinking water to one billion people in the world. This work intends to fabricate modified hydrophobic polyvinylidene fluoride (PVDF) membrane by hydrophilic chitosan extracted from waste fish scales for wastewater treatment. Chitosan was blended with PVDF in N-methyl-2-pyrrolidone solution by solution casting method. Three different concentrations of 1, 3 and 5 wt% of chitosan were taken. The morphological, spectral and thermal analysis of the produced films were elaborately studied. The contact angle decreased with the increase of chitosan content from 82.64° to 60.97°. The tensile strength decreases from 1.11 to 0.38 MPa and Young’s modulus decreased from 12.08 to 7.4 MPa with increase in chitosan content in the film from 1 to 3 %. The performance of microparticle embedded membrane was compared with the pristine PVDF membrane, and it was affirmed that the microsized-chitosan embedded PVDF membrane manifests a broad promising application perspective towards wastewater treatment owing to its excellent water flux (76 L m−2 h−1) as well as antibacterial properties. [ABSTRACT FROM AUTHOR]

To identify what are the dominant lactic acid bacteria (LAB) involved in the fermentation of salt-free sauerkraut, and optimize its industrial culture conditions, we isolated and identified a strain of LAB, which is referred to as Lactobacillus sp. DF_001, with the preservation number CCTCC NO: M20232593, from five different regions in Guizhou Province. Industrial culture conditions were optimized using Plackett-Burman and Central Composite design experiments, and the potential role of this LAB in salt-free sauerkraut fermentation was validated. Bioproduction was optimal with a culture time of 66 h, starch/water ratio of 1.7% and inoculum of 0.02%, which gave approximately three-fold higher yield than the basal culture medium DeMan-Rogosa-Sharpe medium (MRS). The LAB was used in small-scale industrial experiments. The Dafang LAB significantly enhanced the sensory score of the salt-free sauerkraut products by about 32% compared to the control group. The total acid content increased by about 32% and the sugar and nitrite contents were reduced by 67.27 and 69.58%, respectively. The total number of bacterial colonies decreased by 37.5%. All other indicators complied with the national standard, providing overall the basis to improve salt-free sauerkraut fermentation. [ABSTRACT FROM AUTHOR]

Current study is based on the synthesis and characterisation of MgSiO3 nanoparticles (MgSiO3 NPs) and its application for ultrasound-assisted solid-phase extraction (UASPE) of methylene blue (MB) dye from water samples using UV-Vis spectrophotometry. The prepared MgSiO3 NPs were fully identified and characterised by different techniques such as Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Scanning electron microscope (SEM) and Energy-dispersive X-ray spectroscopy (EDS). The prepared nano sorbent had spherical shape with size diameter of 20 nm. Central composite design (CCD) optimisation approach as versatile tool was used for investigation and optimisation of the effective parameters. Using CCD method, the optimised conditions were achieved to be pH of 7.0, sorbent dosage of 29.80 mg, ultrasonic time of 10.34 min, and temperature of 25°C at 500 µl of dimethylformamide eluent using Triton X-100 surfactant. Under the optimised conditions, the proposed method is applicable for wide linear range with detection limit of 0.084 mg L−1, limit of quantification of 0.28 mg L−1. The prepared MgSiO3 NPs have exceptional properties in terms of porous and sheets structure and also high adsorption capacity. In addition, the applied method showed satisfactory figure of merits in terms of pre-concentration factor of 10, which make candidate the applied method and nano sorbent as an operative and ideal candidate for pre-concentration and determination trace level of MB from water samples. [ABSTRACT FROM AUTHOR]

The study aimed at complete elimination of lead with minimum energy consumption using electrocoagulation process employing concentric electrodes made of aluminium. The process was optimized using RSM for chosen variables: current intensity, initial pH, initial lead concentration and time. Quadratic models were generated and assessed using four factorial CCD. A significant quadratic regression model was obtained and validated using ANOVA. Complete removal was attained for optimised conditions having 6 pH, 0.3A current intensity, 41 mg/L initial Lead concentration,13 minutes of applied time duration using energy of 0.77 watt-hour per gram removal of lead. Adsorption followed pseudo Ist order kinetics with a good fitting of the Langmuir isotherm model. Overall process was well optimised with quite low operational cost of 0.00092 US $. [ABSTRACT FROM AUTHOR]

Additive manufacturing of thermoplastic elastomers is challenging using fused deposition modeling due to their high melt viscosity, low column strength, and poor fusion among layers. Solvent‐cast 3D printing (SC‐3DP) is an efficient alternative to successfully 3D print such materials. However, selection of suitable 3D printing parameters is crucial to realize parts with optimum physicomechanical properties. In this work, statistical modeling and SC‐3DP parameter optimization for styrene–ethylene–butylene–styrene (SEBS) block copolymer were performed. The effect of 3D printing process parameters on shrinkage, relative density, and tensile strength was analyzed using response surface methodology. Experiments were planned as per central composite design and analysis of variance was performed to evaluate the significant parameters. SEBS content in the polymer solution significantly affected the shrinkage of SC‐3DP samples. Moreover, relative density and tensile strength were significantly affected by print speed and layer height. A significant interaction between print speed and layer height was also noticed for tensile strength and relative density of printed samples. Multi‐objective optimization using genetic algorithm was also performed to minimize shrinkage and maximize relative density and tensile strength. Finally, a case study was conducted comparing the physicomechanical properties of SC‐3DP samples printed at optimized process parameters and compression molded samples. Highlights: Statistical models were developed using response surface methodology.Genetic algorithm based multi‐objective optimization was performed.Optimum solvent‐cast 3D printing (SC‐3DP) process parameters were determined. [ABSTRACT FROM AUTHOR]

The response surface technique approach was used in this study to determine the best processing parameters for the three responses. For the friction stir welded dissimilar AA7075-T651 and AA1200- H19 aluminium alloys, the rotating and the welding speed, as well as the tool tilt angle, were used as input variables. Mechanical tests were performed on the weldment and the average hardness ranges from 64.26 to 99.72 HV, while the Ultimate Tensile Strength (UTS) ranges from 111.51 to 152.48 MPa. The impact energy was found to varry between 2.9 and 21.4 J. The results from the Signal to Noise (S/N) ratio revealed optimal welding parameters for hardness, UTS and impact energy as 1500 rpm speed of tool rotation, 30 mm/min transverse speed, and 2° tool tilt angle, while for UTS, it is a rotational speed of 1500 rpm, 90 mm/min transverse speed, tool tilt angle of 2° and finally for impact energy as 1500 rpm rotational speed, 30 mm/min transverse speed and 2° tool tilt angle. The results from the grey relational analysis gave optimal process parameters of 1500 rpm rotational speed, 60 mm/min transverse speed and 2° tool tilt angle. The results from the ANOVA revealed that tool rotational speed has the highest significant contribution of 41.79% to the hardness of the weldment followed by the rotational speed (34.46%) and then the transverse speed (19.44%). For UTS, tool rotational speed has the highest significant contribution (35.03%) followed by tool tilt angle (33.72%) and then transverse speed (30. 23%). Also, tool rotational speed has the highest significant effect on the impact energy of the weldment (37.45%) followed by transverse speed (32.00%) and then a tool tilt angle of (27.02%). Empirical models were developed using the Minitab 17 software with the central composite design (CCD) from which the UTS of 150.99 MPa, hardness of 99.102 HV and impact energy of 20.039 were obtained and were found to be close to the experimental values obtained. This study is significant as it gives insight into the optimum processing parameters of joining AA7075-T651 and AA1200- H19 aluminium alloys using the FSW and can be recommended for producing high quality welds with good joint integrity. [ABSTRACT FROM AUTHOR]

The two-phase fluid flow in the Heavy-duty diesel (HDD) engine water jacket coolant can greatly reduce the thermal load of the cylinder head. In this experimental work, the characteristic of two-phase fluid flow in a transparent Plexiglas channel using C2H6O2- H2O (50%–50%) is investigated. Gray cast iron surfaces were selected as the heated surfaces to simulate the material of the HDD-cylinder head. Operating conditions of the HDD- engine (i.e. Vinlet from 0.46 to 2.0 m/s, Psystem from 1 to 2 bar and Tinlet from 70 to 110°C) are optimized using Response Surface Method (RSM) within the framework of the Central Composite Design (CCD) model. The outputs indicate: the onset of nucleate boiling (ONB) temperature increases by about ≈ 11.92% when the pressure changes from 1 to 2bar. By reducing the inlet temperature (from 70 to 110℃), the effect of superheating disappears around the bubble, so to reach the non-linear (i.e. two-phase region) area, the heat flux must be increased between 10 to 15 kW/m² to observe the ONB point. The cooling system pressure at low velocities (i.e. < 1m/s) should be considered in such a way that the saturation temperature of the fluid is about 35 to 50℃ lower than the HDD-engine wall temperature. Instead, at high velocities (i.e > 1m/s) this temperature difference between the fluid saturation temperature and the wall temperature is about 55 to 85℃. [ABSTRACT FROM AUTHOR]

Proper modeling of the dynamic behavior of the soil significantly affects the accuracy of the soil–structure interaction analysis results. Using nonlinear constitutive models has the highest accuracy in modeling soil behavior under earthquake loading. However, it is not functional for practical engineering purposes because of the high cost and complexity. The equivalent linear method also has many limitations, such as filtering out the high-frequency components of the input excitation, underestimating surface ground motion over long periods, and considerable error in high soil strain levels. The current study aims to present an accurate, simple, and low-cost method to model the nonlinear behavior of clays. This method does not meet the limitations of the traditional methods and fully considers the effect of the influential parameters. The novel central composite design technique was adopted to evaluate the effect of influential variables on the nonlinear behavior of clay and formulate the proposed method. The introduced method is applicable to various building structures, power planets, etc. Numerical analyses performed on the proposed method and nonlinear modeling confirm the accuracy, efficiency, and generality of the proposed method. [ABSTRACT FROM AUTHOR]

This study presents the development of eco-friendly cementitious materials for soil stabilization, based on alkaline multi-industrial waste (AMIW), using steel slag (SS), blast furnace slag (BFS), carbide slag (CS), fly ash (FA) and flue gas desulfurization gypsum (FGDG) as the raw materials. The optimal AMIW-based cementitious material composition determined through orthogonal experiments was SS:CS:FGDG:BFS:FA = 15:10:15:44:16. Central composite design (CCD) in response surface methodology (RSM) was employed to optimize the curing process parameters. The maximum 7-day unconfined compressive strength (7d UCS) was achieved under the optimal conditions of 18.51% moisture content, 11.46% curing agent content and 26.48 min of mix-grinding time. The 7d UCS of the AMIW-stabilized soil showed a 24% improvement over ordinary Portland cement (OPC)-stabilized soil. Rietveld refinement results demonstrated that the main hydration products of the stabilized soil were C-S-H and ettringite. After curing for 7 days to 28 days, the C-S-H content increased from 3.31% to 5.76%, while the ettringite content increased from 1.41% to 3.54%. Mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM) analysis revealed that with the extension of curing time, the pores of the stabilized soil become smaller and the structure becomes denser, resulting in an improvement in compressive strength. [ABSTRACT FROM AUTHOR]

Robotic arms have received attention in manufacturing due to their high precision and productivity. As their demand rises, energy consumed by robotic arms in manufacturing applications has become a critical issue. Predicting energy usage of industrial robotic arms is therefore necessary to assess and reduce their energy consumption and costs. However, existing power estimation methods require too many mechanical inputs or focus on only one single robotic arm without considering operational perspectives such as interactions between robotic arms and machines. To tackle these issues, this study proposes a simplified power estimation model for robotic arms and provides energy simulation models in which machines and robotic arms work together. For more accurate results, power data are collected through experiments of central composite design (CCD) using a 7-axis robotic arm. Then, regression models are built to estimate power demand of the robotic arm as three simple inputs: starting point, ending point, and payload. The regression analyses of this study consistently show that the power demand estimation models are very accurate with high R2 values between 0.95 and 0.98. Then, a manufacturing system with milling machines supported by robotic arms is simulated. By applying the proposed method, the activities of robotic arms and machines are simulated with various operational factors, and the time series power is obtained. Further analyses suggest that energy performance of robotic arms can be improved at a maximum of 22% by optimizing two operational parameters: the base and idle positions of robotic arms. The proposed method facilitates energy modeling and simulation processes for robot-assisted manufacturing and enables practitioners and researchers to readily adjust operational parameters and evaluate energy performance for robot applications in manufacturing. [ABSTRACT FROM AUTHOR]

The aim of this study was to optimise ultrasound-assisted extraction (UAE) of the herb Sanguisorba officinalis L. in terms of the antioxidant activity (DPPH and FRAP method) and total polyphenol content (TPC). Optimisation was performed using the response surface methodology (RSM) with a third-degree (33) Central Composite Design (CCD) approach. The RSM was applied to obtain the optimal combination of (1) raw material content (2.25–7.5 g raw material/100 mL of solvent), (2) ethanol concentration (20–60% v/v), and (3) extraction time (1–15 min). The optimal conditions for the extraction of polyphenols and antioxidant potential were a raw material content of 7.5 g/100 mL of solvent (solid/solvent ratio 13.3 mL/g), an ethanol concentration of 47% v/v, and an extraction time of 10 min. At these optimal extraction parameters, the maximum extraction of polyphenols and antioxidant activity obtained experimentally was found to be very close to its predicted value and was 12.9 mmol Trolox/L (DPPH method), 19.4 mmol FeSO4/L (FRAP method), and 2.1 g GA/L (TPC). The mathematical model developed was found to fit with the experimental data on the antioxidant potential and polyphenol extraction. The n-octanol/water partition coefficient of the optimised extract was used to determine their lipophilicity. Our studies have shown that the optimised extract is highly hydrophilic (log P < 0). Optimal parameters can be used for the industrial extraction of the S. officinalis herb for the needs of, among others, the pharmaceutical or cosmetic industry. [ABSTRACT FROM AUTHOR]

Agro-residues, including banana peel, pineapple peel, mango peel, apple peel, and coconut husk, were utilized to produce extracellular polysaccharide (EPS) via solid state fermentation(SSF) by the fungus, Trichoderma hamatum. EPS production was highest in pineapple peel (84.2 ± 0.4 mg/g), followed by mango peel (70.3 ± 0.41 mg/g) (p<0.01). The SSF bioprocess was optimized via a two-level full factorial design and response surface methodology. The effects of five selected variables on EPS biosynthesis, namely, the concentrations of glucose (10 to 30%), ammonium sulphate (0.1 to 1%), yeast extract (0.5 to 2%), MgSO4 (0.01 to 0.1%), and medium pH (4.5 to 6.5), were analyzed via a full factorial design (FFD). The EPS production ranged widely from 15.3 to 576.2 mg/g substrate. Three significant variables affecting EPS production were assessed in central composite design (CCD) to optimize concentrations of MgSO4, and glucose, and the pH. The designed CCD model was fitted to the quadratic model and was significant (p<0.0001). For 50 μL of EPS, the scavenging ratio was 43.4 ± 4.1% at a concentration of 200 μL (78.5 ± 6.9 μL) (p<0.01). The extracted EPS exhibited an alpha-glucosidase inhibitory effect (p<0.001). Solid-state fermentation allows the utilization of low-cost biomass for EPS production and the application of T. hamatum EPS as a natural antioxidant and α-glucosidase inhibitor. [ABSTRACT FROM AUTHOR]

Istamycins (ISMs) are 2-deoxyfortamine-containing aminoglycoside antibiotics (AGAs) produced by Streptomyces tenjimariensis ATCC 31603 with broad-spectrum bactericidal activities against most of the clinically relevant pathogens. Therefore, this study aimed to statistically optimize the environmental conditions affecting ISMs production using the central composite design (CCD). Both the effect of culture media composition and incubation time and agitation rate were studied as one factor at the time (OFAT). The results showed that both the aminoglycoside production medium and the protoplast regeneration medium gave the highest specific productivity. Results also showed that 6 days incubation time and 200 rpm agitation were optimum for their production. A CCD quadratic model of 17 runs was employed to test three key variables: initial pH, incubation temperature, and concentration of calcium carbonate. A significant statistical model was obtained including, an initial pH of 6.38, incubation temperature of 30 ˚C, and 5.3% CaCO3 concentration. This model was verified experimentally in the lab and resulted in a 31-fold increase as compared to the unoptimized conditions and a threefold increase to that generated by using the optimized culture media. To our knowledge, this is the first report about studying environmental conditions affecting ISM production as OFAT and through CCD design of the response surface methodology (RSM) employed for statistical optimization. In conclusion, the CCD design is an effective tool for optimizing ISMs at the shake flask level. However, the optimized conditions generated using the CCD model in this study should be scaled up in a fermenter for industrial production of ISMs by S. tenjimariensis ATCC 31603 considering the studied environmental conditions that significantly influence the production proces. [ABSTRACT FROM AUTHOR]

The main reaction parameters examined were the amount of blast furnace slag, the hydration duration, ammonium acetate concentration, and temperature. The Response surface methodology was employed to quantify their impact on the sorbent's surface area. Using a central composite design, the surface area of the resulting sorbent corresponding to Brunauer-Emmett-Teller (BET) was investigated. The sorbents produced range in surface area from 49.89 to 155.33 m2/g. Additionally, the effectiveness and response prediction capacities of the Response Surface Methodology (RSM) and Artificial Neural Network (ANN) modeling methodologies were investigated. The models were assessed using various statistical metrics, including (MSE) mean squared error, (ARE) average relative errors, the (SSE) sum of squared errors, (HYBRID) Hybrid fractional error function, (SAE) Sum of the absolute errors, (R2)coefficient of determination, and Root means square. According to statistical evidence, the ANN approach surpassed the RSM-CCD model approach. The surface area of the sorbent was shown to be significantly influenced by interactions between variables in addition to all the individual variables examined. The sorbent was made from a material with substantial structural porosity based on SEM. The functional groups were identified using FTIR. The XRF determined the elemental composition of BFS-based sorbents. [ABSTRACT FROM AUTHOR]

This paper aimed to evaluate the effects of different preparation parameters, including agitation speed, agitation time, and chilling temperature, on the structural and mechanical properties of a novel gelatin/elastin/sodium hyaluronate tissue engineering scaffold, recently developed by our research group. Fabricated using a combination of foaming and freeze-drying techniques, the scaffolds were assessed to understand how these parameters influence their morphology, internal microstructure, porosity, mechanical properties, and degradation behavior. The fabrication process used in this study involved preparing a homogeneous aqueous solution containing 8% gelatin, 2% elastin, and 0.5% sodium hyaluronate (w/v), which was then subjected to mechanical agitation at speeds of 500, 1000, and 1500 rpm for durations of 5, 15, and 25 min. This mixture was subsequently frozen at −20 °C and −80 °C, followed by freeze-drying and cross-linking. Morphological analyses using laser microscopy and scanning electron microscopy (SEM) demonstrated that the scaffolds had pore sizes ranging from 100 to 300 µm, which are conducive to effective cell interaction and tissue regeneration. This confirmed the efficacy of the combined foaming and freeze-drying method in creating highly interconnected porous structures. Our findings indicated that chilling temperature slightly influenced pore size. In contrast, higher agitation speeds and longer duration times led to increased porosity and degradation rate but decreased modulus. Mathematical estimators were developed for the porosity and compressive modulus of the scaffolds by statistical analysis of the preparation parameters. The estimators were validated experimentally, with the error between estimated and experimental values being less than 6% for porosity and less than 21% for compressive modulus. [ABSTRACT FROM AUTHOR]

The major activity in research of metal cutting is to derive the mathematical models for surface roughness in turning. The present work aims at experimental investigation of hard turning of AISI 52100 bearing steel in order to determine the combined effects of tool geometry (nose radius and rake angle) and process parameters (speed, feed and depth of cut) on the performance characteristic surface roughness. Experiments were conducted using orthogonal array and central composite face centered (CCF) design. A mathematical prediction model for SR has been obtained in terms of factors mentioned. 3D response graphs were drawn to study the interaction effects of surface roughness. Prediction for orthogonal array is done through artificial neural network. Optimization of surface roughness was also carried out for CCF design using genetic algorithm. The efficacy of the CCF design over orthogonal array design is evaluated. Minimum surface roughness of 0.985 µm is obtained when A = 90m/min, B = 0.052mm/rev, C = 0.6mm, D = 4mm and E = − 12O after application of genetic algorithm. [ABSTRACT FROM AUTHOR]

Machine learning and response surface methods for predicting the compressive strength of high-strength concrete have not been adequately compared. Therefore, this research aimed to predict the compressive strength of high-strength concrete (HSC) using different methods. To achieve this purpose, neuro-fuzzy inference systems (ANFISs), artificial neural networks (ANNs), and response surface methodology (RSM) were used as ensemble methods. Using an ANN and ANFIS, high-strength concrete (HSC) output was modeled and optimized as a function of five independent variables. The RSM was designed with three input variables: cement, and fine and coarse aggregate. To facilitate data entry into Design Expert, the RSM model was divided into six groups, with p-values of responses 1 to 6 of 0.027, 0.010, 0.003, 0.023, 0.002, and 0.026. The following metrics were used to evaluate model compressive strength projection: R, R2, and MSE for ANN and ANFIS modeling; R2, Adj. R2, and Pred. R2 for RSM modeling. Based on the data, it can be concluded that the ANN model (R = 0.999, R2 = 0.998, and MSE = 0.417), RSM model (R = 0.981 and R2 = 0.963), and ANFIS model (R = 0.962, R2 = 0.926, and MSE = 0.655) have a good chance of accurately predicting the compressive strength of high-strength concrete (HSC). Furthermore, there is a strong correlation between the ANN, RSM, and ANFIS models and the experimental data. Nevertheless, the artificial neural network model demonstrates exceptional accuracy. The sensitivity analysis of the ANN model shows that cement and fine aggregate have the most significant effect on predicting compressive strength (45.29% and 35.87%, respectively), while superplasticizer has the least effect (0.227%). RSME values for cement and fine aggregate in the ANFIS model were 0.313 and 0.453 during the test process and 0.733 and 0.563 during the training process. Thus, it was found that both ANN and RSM models presented better results with higher accuracy and can be used for predicting the compressive strength of construction materials. [ABSTRACT FROM AUTHOR]

Uricase is potential therapeutic and diagnostic enzyme having wide applications in pharmaceutical sector, but production yield and cost of production are challenging. Hence, isolation of potent uricase-producing sources and optimizing its production are essential for industrial-scale uricase production. In this study, a novel extracellular uricase-producing bacterium was isolated using uric acid plate assay. The strain was identified by 16S rRNA sequencing and it was found to be Pseudomonas mosselii with similarity of 99%. Further, multi-level statistical optimizations were conducted to enhance the uricase production. Firstly, Plackett-Burman design (PBD) was adapted for screening of different medium components and found that uric acid, peptone, and sucrose are highly significant medium components which affect the uricase production. Further, central composite design (CCD) and artificial neural network (ANN) combined genetic algorithm (GA) were used to optimize the uricase production. The use of CCD prior to ANN improved the predictive capability of ANN and GA model. Under the optimum conditions obtained using ANN-GA, the uricase production was enhanced and found to be 59.91 U/mL ± 0.32 which is 2.02 folds higher compared to unoptimized medium. The results of the current study enunciate that the newly isolated Pseudomonas mosselii is a potential bacterium for enhanced production of uricase and optimization using multilevel optimization approaches gave better prediction of optimum process conditions for enhanced uricase production. [ABSTRACT FROM AUTHOR]

Antibiotics have several negative effects on aquatic ecosystems and are difficult to degrade using traditional water/wastewater treatment methods. As a result, new treatment techniques must be employed to eliminate these contaminants from aquatic environments. Research on the relationship between the decomposing process of antibiotics and different factors by new technologies is scarce. This research focuses on the capability of ozone micro-nano bubbles (OzMNBs) to eliminate the antibiotics ciprofloxacin (CIPR) and levofloxacin (LEVO) in aqueous solutions. We studied the CIPR and LEVO decomposition to different variables through the central composite design method. The main variables included pH, ozonation time, and initial antibiotic concentration. The correlation coefficients of the quadratic model obtained by using the software, Design Expert version 13.0.1. Analysis of variances proved the significance of models and main factors. Verification tests also confirmed that the final optimum conditions of the antibiotics decomposition were: pH 9, ozonation for 40 min and, initial antibiotic concentration of 5 mg/L. In optimum conditions, removal rate of about 97% and 100% was obtained for CIPR and LEVO, respectively. The order of influence of various factors on CIPR and LEVO decomposition were obtained and the interactions between the main factors were also investigated. At the last stage of the research, the efficiency of OzMNBs in the removal of total organic carbon and mineralization of the solutions containing CIPR and LEVO under optimum conditions was examined. [ABSTRACT FROM AUTHOR]

AbstractMicrowave-Assisted Alkali (MAA) pretreatment of corncob biomass was optimized for maximum fermentable sugar yield using dilute sulfuric acid hydrolysis. A Central Composite Design (CCD) investigated the effects of microwave power (450–9000 W), NaOH concentration (1.5 to 4.5% wt./v), and irradiation time (10–20 min) on lignin removal. The optimal MAA pretreatment conditions were found to be 691.73 W, 3.4% NaOH, and 15.5 min, resulting in the selective removal of 73.36% lignin with high retention of cellulose (71.69%) and hemicellulose (22.14%). Characterization techniques (FTIR, SEM, XRD, TGA) confirmed substantial changes in surface morphology, functional groups, crystallinity, and thermal stability of the pretreated corncobs. Dilute sulfuric acid hydrolysis (0.5–2.5%, 110130 °C, 3060 min) of the optimized sample yielded a maximum reducing sugar output of 537.42 mg/g, achieved at 0.534% H2SO4, 122.3 °C, for 58 min. Optimizing Microwave-Assisted Alkali pretreatment process for corncobs could boost biofuel production efficiency, sustainably utilize agricultural waste, and advance a more sustainable energy landscape. [ABSTRACT FROM AUTHOR]

The optimization of floating bifacial solar panels (FBS PV) in tropical freshwater systems is explored by employing response surface methodology (RSM) and central composite design (CCD). Previous studies have yet to explore the long-term durability, environmental impact, economic viability, and performance of FBS PV systems under various climatic conditions. This study addresses this gap by focusing on panel height, water depth, and tilt angle to improve performance. The quadratic model reveals significant non-linear relationships impacting FBS PV power generation with freshwater cooling. Our models demonstrate high explanatory power, with R-squared values of 0.9831 for output power and 0.9900 for Bi-Facial gain. Experimental validation using conventional white surface (CWS) and proposed freshwater surface (PFS) indicates notable improvements in power generation, achieving a 4.34 to 4.86% gain in bifacial efficiency across various irradiation levels. Under 950 W/m2 irradiation, freshwater cooling achieves a 3.19% higher bifacial gain compared to CWS cooling. Panel temperature analysis shows consistent reductions with freshwater cooling, ranging from 1.43 to 2.72 °C, enhancing overall efficiency and longevity. This research highlights the potential of freshwater cooling in optimizing bifacial solar systems, offering actionable insights for sustainable energy solutions in tropical regions. [ABSTRACT FROM AUTHOR]

In this research, graphene oxide (GO) as an adsorbent was used to remove norfloxacin and ceftriaxone antibiotics from aqueous solutions. All environmental factors affecting removal (e.g., pH, adsorbent mass, contact time, and concentration) were optimized in a discontinuous system. The design of experiments and the optimization of variables were carried out using the response surface method (RSM). The results of the analysis of variance (ANOVA) and the regression coefficients of the quadratic terms indicated that the responses were significantly affected by all the studied variables (P < 0.05). Also, the quadratic polynomial model results corresponded to empirical data with a high coefficient of determination (i.e., R² > 0.99 for both antibiotics). Besides, the adjusted R² (R²-adj >0.98 for both antibiotics) was close to R² values, indicating a good and acceptable statistical model. According to the results, the optimal removal of antibiotics by GO occurs in conditions of pH of 8, 0.034 g of the adsorbent mass, a sonication time of 20 min, and a concentration of 25 mg L-1. In these conditions, the maximum removal efficiencies of ceftriaxone and norfloxacin were equal to 95.87% and 98.64%, respectively. GO was recovered in five adsorption/desorption processes, and the removal efficiency declined very slightly after using the adsorbent for five cycles. Therefore, it is concluded that GO is an efficient and acceptable adsorbent for removing ceftriaxone and norfloxacin from aqueous environments. [ABSTRACT FROM AUTHOR]

Despite the large number of works on the synthesis of polylactide-co-glycolide (PLGA) nanoparticles (NP) loaded with antituberculosis drugs, the data on the influence of various factors on the final characteristics of the complexes are quite contradictory. In the present study, a comprehensive analysis of the effect of multiple factors, including the molecular weight of PLGA, on the size and stability of nanoparticles, as well as the loading efficiency and release of the antituberculosis drug rifampicin (RIF), was carried out. Emulsification was carried out using different surfactants (polyvinyl alcohol, Tween 80 and Pluronic F127), different aqueous-to-organic phase ratios, and different solvents (dichloromethane, dimethyl sulfoxide, ethyl acetate). In this research, the PLGA nanoemulsion formation process was accompanied by ultrasonic dispersion, at different frequencies and durations of homogenization. The use of the central composite design method made it possible to select optimal conditions for the preparation of PLGA-RIF NPs (particle size 223 ± 2 nm, loading efficiency 67 ± 1%, nanoparticles yield 47 ± 2%). The release of rifampicin from PLGA NPs was studied for the first time using the flow cell method and vertical diffusion method on Franz cells at different pH levels, simulating the gastrointestinal tract. For the purpose of the possible inhalation administration of rifampicin immobilized in PLGA NPs, their mucoadhesion to mucin was studied, and a high degree of adhesion of polymeric nanoparticles to the mucosa was shown (more than 40% within 4 h). In the example of strain H37Rv in vitro, the sensitivity of Mycobacterium tuberculosis to PLGA-RIF NPs was proven by the complete inhibition of their growth. [ABSTRACT FROM AUTHOR]

The objective of this study was to prepare a co-amorphous blend of BCS class II drug, glipizide (GPZ), using arginine (ARG) as co former. The co-amorphous GPZ-ARG mixtures (molar ratios 1:1, 1:2 and 2:1) were prepared by mechanical activation (ball milling) with different milling times. The obtained mixtures were characterized with respect to their thermal properties, possible molecular interactions, dissolution properties and physical stability and compared to the behaviour of pure crystalline form. Solid-state characterization of mixture revealed amorphization of GPZ after 90 min. of ball milling. GPZ-ARG co amorphous mixture (1:2) upon ball milling for 90 min. exhibited maximum solubility (3876.8 µg/ml) compared to pure drug (300.89 µg/ml). The resulting best co amorphous blend was incorporated into pellets which were prepared by extrusion spheronisation technique. The parameters related to process of pelletisation and product related parameters were optimized by using 4-factor, 5-level Central Composite Design. The pellets containing co amorphous blend, prepared by using optimal parameter settings, showed 95.67% Drug Release in 120 min. (F23). The co-amorphous mixture and the optimized formulation were found to be stable when subjected to stability study as per ICH guideline. It was concluded that co amorphous is a promising approach to overcome the solubility constraint of Glipizide which would be helpful in better management of the disease. [ABSTRACT FROM AUTHOR]

Repackaging of expired medicines has become common in developed countries and can cause serious health problems. Therefore, the identification of these products is of considerable importance. This study investigated the applicability of an analytical method based on Fourier Transform Infrared spectroscopy combined with chemometrics for separating two types of expired and non-expired tablets. The study focuses on vildagliptin, collagen, and vitamin tablets and represents a preliminary study for different types of tablets. Instrumental conditions were determined by central composite design. As a result of the the variance analysis, it was found that the pressure parameter was significant, while the number of scans and resolution were insignificant. The optimum instrumental conditions were determined as attenuated total reflection module pressure 57, scan number 20, and spectral resolution 4 cm−1. Derivatizing spectra were used to find major peaks that make a significant difference. As a result of principal component analysis, PC1 in the 92-96.9% and PC2 in the range of 6.6-3% range explained the total variance. In the results obtained, significant discrimination and clustering between the species were seen, and for all three species, expired and non-expired drug samples with different storage conditions could be separated. Fourier Transform Infrared spectroscopy can be helpful in screening for counterfeit drugs as it is easy to use and requires little sample preparation. It is also thought that this approach may be helpful for the initial evaluation of repackaged tablets. [ABSTRACT FROM AUTHOR]

Physical or chemical processes can enrich surface functional groups of activated carbon. EDTA grafting was applied to the carbon surface using a chemical treatment in this study. In this way, while there was no significant change in the surface area of the carbon, the Golden Yellow (GY) removal performance increased. The changes caused by EDTA grafting on the carbon surface have been revealed using various methods. Environmental conditions affecting the adsorption process were statistically investigated using Central Composite Design (CCD). Different equations were used to determine the stability, capacity, and mechanism of the GY removal with activated carbon and EDTA grafted carbon. [ABSTRACT FROM AUTHOR]

Metakaolin-based geopolymers (MKGP) were optimised by varying the operating conditions using the central composite design (CCD) and the response surface method (RSM) to optimise the operating variables affecting MKGP formation and their adsorption efficiency. The MKGP was characterised and tested for the removal of methylene blue (MB) from an aqueous environment. Results show that the MKGP5 with the most organised structure exhibits the highest MB removal efficiency. Parameters like the adsorbent dose, the pH, the contact time, the initial dye concentration, and the temperature were optimised to improve the adsorption efficiency of MB. The results also demonstrated the accuracy and feasibility of CCD simulation to develop a well-converted geopolymer adsorbent for water treatment. [ABSTRACT FROM AUTHOR]

This work reports the degradation of cellulosic material, i.e., paper, under different environmental conditions (soil and hydrolytic). Models were developed using central composite design (CCD) within the framework of response surface methodology (RSM) and artificial neural network (ANN) techniques. It is done as part of a solid waste management system to eliminate the waste produced by excessive paper usage and obtain optimized degradation conditions of paper. In view of the real environments where paper-based solid wastes are usually exposed, soil degradation and hydrolytic degradation of paper were investigated. The factors pH (4–10), compost ratio (2–5), CaCl2 (5–15 ppm), and time (7–20 days) were independent factors that varied for the study, and degradation conversion was measured as the dependent variable for soil degradation of paper. The factors pH (4–10), CaCl2 (2–5 ppm), tripotassium phosphate (TPP, 2–5 ppm), and time (6–16 days) were independent variables that varied for the study, and degradation conversion was the dependent variable for hydrolytic degradation of paper. The optimal conditions for soil degradation were determined to be a pH of 4, a compost ratio of 5, a salt (CaCl2) addition of 5 ppm, and a duration of 20 days, resulting in the highest observed conversion rate. The coefficient of regression (R2) for CCD is 87.24%, whereas it is 94.82% for ANN. The optimal conditions for achieving maximum conversion in hydrolytic degradation include a pH of 10, a CaCl2 salt concentration of 5 ppm, a TPP salt concentration of 2 ppm, and a duration of 16 days. The coefficient of regression for CCD is 75.15%, while the coefficient of regression for ANN is 93.91%. In both deterioration scenarios, the data exhibited a higher degree of fit when modeled using ANN compared to CCD (RSM). [ABSTRACT FROM AUTHOR]

α-tocopherol (α-T), β-sitosterol (β-S), canolol (CA), and sinapic acid (SA) are the four main endogenous lipid phytochemicals (LP) found in Brassica napus L. seed oil, which possess the bioactivity to prevent the risk of several chronic diseases via antioxidant-associated mechanisms. Discovering the enhancer effects or synergies between LP is valuable for resisting oxidative stress and improving health benefits. The objectives of this study were to identify a potentially efficacious LP combination by central composite design (CCD) and cellular antioxidant activity (CAA) and to investigate its protective effect and potential mechanisms against H2O2-induced oxidative damage in HepG2 cells. Our results indicated that the optimal concentration of LP combination was α-T 10 μM, β-S 20 μM, SA 125 μM, and CA 125 μM, respectively, and its CAA value at the optimal condition was 10.782 μmol QE/100 g. At this concentration, LP combination exerted a greater amelioration effect on H2O2-induced HepG2 cell injury than either antioxidant (tea polyphenols or magnolol) alone. LP combination could reduce the cell apoptosis rate induced by H2O2, lowered to 10.06%, and could alleviate the degree of oxidative damage to cells (ROS↓), lipids (MDA↓), proteins (PC↓), and DNA (8-OHdG↓). Additionally, LP combination enhanced the antioxidant enzyme activities (SOD, CAT, GPX, and HO-1), as well as the T-AOC, and increased the GSH level in HepG2 cells. Furthermore, LP combination markedly upregulated the expression of Nrf2 and its associated antioxidant proteins. It also increased the expression levels of Nrf2 downstream antioxidant target gene (HO-1, SOD-1, MnSOD, CAT, GPX-1, and GPX-4) and downregulated the mRNA expression levels of Keap1. The oxidative-stress-induced formation of the Keap1/Nrf2 complex in the cytoplasm was significantly blocked by LP treatment. These results indicate that LP combination protected HepG2 cells from oxidative stress through a mechanism involving the activation of the Keap1/Nrf2/ARE signaling pathways. [ABSTRACT FROM AUTHOR]

Composite materials are utilized in various industries due to their advantageous properties. Drilling is a crucial process for joining these materials to construct the structures. During the drilling of composite materials, several types of defect can occur, with delamination being the most prevalent. Delamination adversely effects the properties of the drilled hole and diminishes the quality of the final structure. Thrust force is a key parameter used to monitor the drilling process; a higher thrust force increases the likelihood of defects, particularly delamination, in the drilled area. In this article, a central composite design is applied to the drilling process of carbon fiber-reinforced polymer (CFRP) composites, focusing on parameters such as rotational speed, feed rate, and the angle between the composite layer sequences. The objective is to minimize delamination factors and thrust force. The effect of drilling parameters on the responses is analyzed independently. The results indicate that the derived models can predict the thrust force and delamination factors in the drilling of CFRP composites. [ABSTRACT FROM AUTHOR]

In this study, the optimum hydrothermal conditions of sugar beet pulp were investigated by Response Surface Methodology (RSM) based on Central Composite Design (CCD). The hydrochar obtained from sugar beet pulp (SBP) was optimized for maximum yield and carbon content. Process conditions were chosen with reaction temperatures of 200–240 °C, residence time 60–150 min, and biomass to water ratio of 1:3–1:10. The yield and carbon content of the hydrochar varied with the process parameters. In order to obtain hydrochar with the highest yield and carbon content in optimization, the reaction temperature should be 220.74 °C, the biomass to water ratio should be 1:3, and the residence time should be 95.58 min. High heating value, energy and mass yield, and energy densification ratio of sugar beet pulp and hydrochar were also investigated. The products were characterized using FT-IR, SEM, and ultimate analysis techniques. The Coats-Redfern method was used to estimate the kinetic parameters of the combustion processes. The activation energy values of SBP and SBP-HC products were calculated as 13.88 and 11.46 kJ/mol, respectively. The kinetic data were used to determine the thermodynamic parameters (ΔH, ΔG, and ΔS). As a result, the properties of hydrochar produced from sugar beet pulp under optimum conditions have been extensively investigated and the results have shown that hydrochar has potential for use in different areas. [ABSTRACT FROM AUTHOR]

High polyhydroxyalkanoate (PHA) yield from selected substrates associated with minimal accumulation of residual biomass can improve the process economy. In this study, different carbon (glucose, sucrose, glycerol, and acetic acid) and nitrogen (NH4Cl and urea) sources were screened for PHA production by Cupriavidus necator. The effects of incubation time, nitrogen, and phosphate concentration on biomass growth and PHA production were co-optimized through response surface methodology (RSM) and genetic algorithm-optimized artificial neural network (GA-ANN). Sucrose and urea were found to offer significantly better (p <0.001) biomass (1.468 ± 0.007 g l-1) and PHA (0.924 ± 0.02 g l-1) yield when compared with other carbon and nitrogen sources. Though the performance of both the models remains similar for biomass (R2 = 0.97–0.98), GA-ANN (with six neurones in a hidden layer) seems exceptionally better in predicting PHA yield (R2 = 0.97) when compared to the polynomial model (R2 = 0.92). The maximum PHA concentration of 2.69 g l-1 was predicted by the ANN model at an incubation time of 62.80 h with 2.0 g l-1 of nitrogen and 4.0 g l-1 of phosphate concentration. The multi-composite desirability using the GA-ANN model projected a better polymer-to-biomass ratio compared to the polynomial model. The inclusion of a cost-benefit analysis framework may be warranted before recommending the optimal conditions obtained through multivariate regression and GA-ANN models. [ABSTRACT FROM AUTHOR]

The co-precipitation approach is used in the current study to create an environmentally friendly Ag/Fe/ZnO nanocomposites utilizing an aqueous leaf extract of Embelia schimperia. The synthesized nanocomposite was characterized using Fourier-transform infrared, UV, X-ray, UV–vis, DLS, TGA, and SEM to determine its functional group, structure, bandgap energy, size distribution, a mass of loss, and energy gain or loss, and morphological structure, respectively. The bioactive components of Embelia schimperia, synthesized Ag/Fe/ZnO NCs and degradation of Amoxicillin via photocatalyst were assessed. The response surface methodology of central composite design (CCD) was used to examine and optimize the effects of three independent variables on the degradation of Amoxicillin under visible light. According to the experimental findings, the maximum photocatalytic degradation efficiency was achieved at green synthesized Ag/Fe/ZnO NCs dosage of 100 mg, a concentration of Amoxicillin of 30 mg/L and a radiation time of 180 min. Their findings show that Embelia schimperia extract-derived Ag/Fe/ZnO nanocomposites is a promising alternative for degradation of pharmaceuticals contamination of wastewater via photocatalytic under the given conditions. [ABSTRACT FROM AUTHOR]

This study aims to synthesize and characterize silver nanoparticles (AgNPs) from Leucaena leucocephala leaf extract and evaluate their effectiveness in photo-catalytically degrading indigo carmine (IC) dye in an aqueous solution. The synthesized AgNPs were characterized using UV-visible spectrophotometry (UV-Vis), diffuse reflectance spectroscopy (DRS), Fourier transform infrared spectroscopy (FTIR), energy dispersive X-ray spectroscopy (EDX), transmission electron microscopy (TEM), and X-ray diffraction (XRD) techniques. Response surface methodology (RSM) based on central composite design (CCD) was employed to optimize the conditions for the photocatalytic degradation of IC dye under solar light. The results show that 97.52% of the maximum photodegradation of IC dye was achieved using a dye concentration, catalyst volume, and reaction time of 19.7 mgL-1, 4.47 mL, and 97 min, respectively. RSM results revealed optimal conditions for IC dye degradation under solar irradiation. Moreover, the kinetics study of IC dye showed a good correlation with the pseudo-first order kinetic model. [ABSTRACT FROM AUTHOR]

This study focuses on numerically optimizing key process parameters related to the liquid–liquid extraction batch process (LLEBP) technique for carrying out batch runs to remove methyl red effectively (MR) from dye effluent. LLEBP, a suitable industrial process for treating dye effluents, depends on the number of reaction parameters such as feed concentration, extraction time, and dye ratio (solution/solvent). The current research utilized a central composite design (CCD) of experiments along with numerical optimization techniques to optimize process parameters over a range of dye concentrations: (20–100) ppm, extraction time range 10–30 min, and dye ratio 1–3 mL/mL (solution/solvent). The batch runs performed at room temperature and a constant pH of 3, according to the experimental design criteria, suggest that maximum dye removal efficiency and distribution coefficient value could be achieved within the feed concentration range of (20–30) ppm, 20–30 min of extraction time, and 1–3 mL/mL of dye ratio (solution/solvent). Solvent capacity increases significantly within the (60–100) ppm feed concentration range. Numerical optimization with desirability function criteria identified optimal conditions: 20 ppm dye concentration, 30 min extraction time, and 3 mL/mL dye ratio ensuring maximum LLEBP yield. The current investigation achieved a 4% higher dye removal (%) of 85.682 compared to the previous study. The distribution coefficient and solvent capacity attained were 5.287 and 4.504 mg/L, respectively. The research enhances understanding of the optimization process for LLEBP in MR dye removal from textile effluent, surpassing previous findings within the same input range. The manuscript aims to maximize process optimization using CCD, promoting sustainable industry progress in line with UN sustainable development goals. [ABSTRACT FROM AUTHOR]

Aim: This study focuses on biotinylated nanocarriers designed to encapsulate amphiphilic molecules with self-biodegradable properties for enhanced drug delivery. Methods: Biotin-zein conjugated nanoparticles were synthesized and tested in C6 cell lines to evaluate their viability and cellular uptake. Optimization was achieved using a a central composite design. The nanoparticles underwent thermogravimetric analysis, and their pharmacokinetics and biodistribution were also studied. Results: The optimized nanoparticles displayed 96.31% drug encapsulation efficiency, a particle size of 95.29 nm and a zeta potential of -17.7 mV. These nanoparticles showed increased cytotoxicity and improved cellular uptake compared with free drugs. Thermogravimetric analysis revealed that the drug-loaded nanocarriers provided better protection against drug degradation. Pharmacokinetic and biodistribution studies indicated that the formulation had an extended brain residence time, highlighting its effectiveness. Conclusion: The biotin-zein conjugated nanoparticles developed in this study offer a promising nano-vehicle for in vivo biodistribution and pharmacokinetic applications. Their high drug encapsulation efficiency, stability and extended brain residence time suggest they are effective for targeted drug delivery and therapeutic uses. Graphical Abstract Article highlights A stable biotin and zein conjugate were formed via ethyl carbodiimide and N-hydroxy succinimide coupling to enhance site-directed delivery. Prepared polymeric conjugates were evaluated for its extent of conjugation, and secondary structural alteration revealed stability of conjugate. The biotin-zein conjugate exhibited a flexible backbone, and better encapsulation of hydrophilic molecules with a sustained release profile. Biotin-zein conjugation improved the loading capacity, and amphiphilic nature and aided the cytotoxic potential of the drug. The conjugated nanocarriers revealed the sustained release profile with higher cytotoxic potential compared with free drug along with enhanced cellular entrapment. The prepared nanoformulation revealed its safety via the nasal mucociliary canal. The formulation suggests higher residence time is observed via the intranasal route of administration compared with intraperitoneal administration. Ex vivo studies revealed presence of fluorescence intensity in the brain at 24 h (intranasal route), whereas in the intraperitoneal administered group signal intensity was reduced. [ABSTRACT FROM AUTHOR]

Aim: To investigate eutectic liquid-based emulsion-like dispersions for intratympanic injections to augment cinnarizine permeability across round window membrane in a healthy rabbit inner ear model. Methods: Two-tier systematic optimization was used to get the injection formula. The drug concentrations in perilymph and plasma were analyzed via. Ultra-performance liquid chromatography-tandem mass spectrometry method after 30-, 60-, 90- and 120-min post intratympanic injection time points in rabbits. Results: A shear-thinning behavior, immediate drug release (∼98.80%, 10 min) and higher cell viability (>97.86%, 24 h) were observed in dispersions. The cinnarizine level of 8168.57 ± 1236.79 ng/ml was observed in perilymph at 30 min post intratympanic injection in rabbits. Conclusion: The emulsion-like dispersions can augment drug permeability through round window membrane. Article highlights Intratympanic injections containing cinnarizine-loaded emulsion-like dispersions was prepared using camphor-menthol (1:0.97 molar ratio) eutectic liquid. The formula for preparing cinnarizine-loaded emulsion-like dispersions was obtained by applying linear (response surface methodology) and non-linear (artificial neural network) models. The optimized cinnarizine-loaded emulsion-like dispersions was prepared as per the formula suggested by the non-linear model. The MPS, PDI, ZP and drug amount in whole dispersions values of drug-loaded emulsion-like dispersions were 175.40 ± 5.20 nm, 0.245 ± 0.018, 43.20 ± 3.30 mV and 72.37 ± 5.67% w/v, respectively. The DEE, pH and osmolality values of drug-loaded emulsion-like dispersions prepared using the optimized formula were 96.50 ± 0.44%, 7.40 ± 0.07 and 299 ± 42.29 mOsm/kg H2O, respectively. The emulsion-like dispersions were found to be shear thinning (0.1 to 100 s-1 shear rate) and was not affected by coalescence and Ostwald ripening till 90 days at 25°C. The MTT test results performed in L-929 cells displayed cell viability values of more than 97.86% for all tested concentrations of drug-loaded emulsion-like dispersions. The presence of cinnarizine in perilymph and plasma of healthy rabbit inner ear model after intratympanic administration of drug-loaded emulsion-like dispersions was checked using a UPLC-MS/MS bioanalytical method. The intratympanic administration of drug-loaded emulsion-like dispersions displayed cinnarizine concentrations of 470.10 to 8168.57 ng/ml in perilymph for 30–120 min. [ABSTRACT FROM AUTHOR]

Abstract Anaerobic digestion of abundant feedstock from biomaterials is a good innovative fossil fuel alternative approach for the synthesis of green fuel (biogas). Rotatable central composite design (CCD) and machine learning (ML) via Python coding were successfully used to design, optimize, and predict the rate of biogas production from stew‐rice and eggs digestate with Udara seeds in an anaerobic unit. Two‐input parameters, such as inoculation ratio (S/I) and hydraulic reaction time (HRT) were considered, resulting in 13 experimental setups under mesophilic surroundings of 25–34°C. Mixture ratios of substrate/inoculum (S/I) of 0.98:1, 1.5:1, 2.75:1, 2.75:1, 4:1, 1.5: 1, and 4.52:1 were used against 30, 20, 44.14, 15.86, 40, 40, and 30 days HRT as modeled by CCD rotatable to optimize biogas production from crushed Udara seeds with spoilt stew‐rice and eggs digestate. From the results, it was observed that the coefficient of determination (R2) of 0.9573 was generated via CCD rotatable whereas, the R2 of 1 was generated from the multivariate regression of ML approach. Also, the data and graphs derived via ML were superior to the ones derived from CCD rotatable. However, the maximum output of 4.84 L at 4 mixing ratio and 40 days HRT from CCD rotatable is close to the ML value of 4.89 L under the same input factors, yet ML yielded more. Thus, it is clear that the Python‐based ML algorithm approach has the potential to predict biogas output better than CCD rotatable. However, the Gas Chromatography Mass Spectrometry analysis of the highest output produced generated 63.29% biomethane and 26.71% CO2 by volume and produced a flashpoint of −167°C which is flammable. Thus, the generated biogas via an anaerobic unit can be transmitted into large‐scale commercial applications for the betterment of mankind.

Abstract The insulators of overhead power lines play a crucial role in maintaining the reliability of transmission and distribution networks. Because they are exposed to harsh and dynamic environmental conditions, it is essential to investigate the impact of environmental parameters such as pollution, inclined angle with the cross arm, and temperature on the dielectric performance of the insulators of overhead lines. Conventionally, the effect of such parameters can be investigated through experimental measurements of the insulator flashover voltage. However, this approach is costly and time-consuming and calls for the isolation of the lines to conduct the test, causing interruption to the entire grid. As such, there is an essential need to develop a new methodology to quantify the flashover voltage of overhead insulators operating under various environmental conditions, which is the main aim of this paper. The Central Composite Design is employed to develop a mathematical correlation between the insulator flash over voltage as a dependent variable and three environmental parameters: pollution level, inclined angle, and temperature as independent variables. The robustness of the developed equation is validated through extensive experimental measurements of the insulator’s flash overvoltage under various conditions. Results reveal a good agreement between the actual and predicted flashover voltage using the developed correlation, as the absolute error for all investigated samples is less than 6%.

Agro-residues, including banana peel, pineapple peel, mango peel, apple peel, and coconut husk, were utilized to produce extracellular polysaccharide (EPS) via solid state fermentation(SSF) by the fungus, Trichoderma hamatum. EPS production was highest in pineapple peel (84.2 ± 0.4 mg/g), followed by mango peel (70.3 ± 0.41 mg/g) (p

This study aims to serve as a performance indicator for the workability and strength of concrete when coarse aggregate, sand, cement, and water are partially substituted with waste plastic bottle caps. The significance of these alternative plastic water bottle caps is to reduce plastic trash that is difficult to lapse and to prevent waste that can be transformed to something that may be employed in the advancement of technology in the future. The principle of "Reduce, Reuse, and Recycle" is used, which not only lowers environmental pollution but also reduces costs. In the building industry, concrete is the most often utilized material. In order to preserve natural resources and minimize the number of materials that end up in landfills, green construction is becoming a more significant worldwide issue. Empty cans and bottle tops from drinking water bottle produce a lot of garbage. The difficulty of biodegrading plastic trash and the need for techniques for recycling or reuse make this a problem for the environment. Such problems are being investigated in this study in order to determine whether it could be possible to partially replace coarse aggregate with 0, 6 and 12% in the manufacturing of concrete using discarded bottle caps. To evaluate the compressive strength, split tensile, and flexural strength test characteristics in a laboratory setting; waste bottle caps were used as replacements for coarse aggregate at different percentages. The highest compressive strength was determined to be 28.80 MPa with 12% replacement of used plastic bottle caps with a water cement ratio of 0.55. Advanced statistical methods, including RSM-CCD (Response Surface Method-Central Composite Design) and machine learning models ANN-LM (Artificial Neural Network- Levenberg Marquardt), were applied in this study to predict concrete performances based on mix design variations. It was found that ANN-LM model displayed more accurate prediction relative to RSM-CCD method. [ABSTRACT FROM AUTHOR]

Investigations have shown the traces of antibiotics in surface water, groundwater, wastewater treatment plants, and drinking water. However, conventional wastewater treatment is not entirely effective for vancomycin degradation. Advanced oxidation is one of the most widespread methods of antibiotic degradation in aqueous media. Vancomycin was quantified by high-performance liquid chromatography. The Response Surface Methodology (RSM) based on Central Composite Design (CCD) was used to explore and optimise the effect of the independent variables on vancomycin degradation. Independent variables were as follows: pH (3–11), vancomycin concentration (15–75 mg/L), TiO2–clinoptilolite (25–125 mg in 250 mL reactor volume), the temperature (25–45°C), and the reaction time (15–75 min). The validity and adequacy of the model were confirmed by the corresponding statistics (F–value = 111.5, correlation coefficient R2 = 0.98, adjusted R2 = 0.97, and prediction R2 = 0.95). The vancomycin degradation efficiency was 97% under optimal conditions (pH = 5, vancomycin concentration = 30 mg/L, TiO2-clinoptilolite content = 50.2 mg in a 250 mL reactor volume, temperature = 32.24°C, and reaction time = 50.9 min). This process followed the zero-order reaction kinetics model (R2 = 0.98), and the removal rate of Total Organic Carbon (TOC) under optimal conditions was 56%. The results indicated that supporting TiO2 on clinoptilolite particles could increase the photocatalytic properties. [ABSTRACT FROM AUTHOR]

An agro-waste corncob was used to prepare activated carbon and loaded with ZnO nanoparticles by using the impregnation method. The FTIR band at 492 cm−1 of zinc oxide nanoparticle-loaded corncob activated carbon (ZnO@CCAc-7) shows the spreading vibrational modes of ZnO. The crystallinity and crystal structure of different prepared materials were analysed using X-ray diffraction (XRD). The specific surface area of ZnO@CCAc-7 was observed to be 148.3 m2/g, which was nearly two times larger than that of efficient corncob activated carbon. The fundamental peaks of carbon, oxygen and ZnO nanoparticle with their atomic percent of C 66.66, O 27.10 and ZnO 6.24 were observed in the SEM-EDX spectrum. The thermal stability of the prepared adsorbent was also analysed using thermogravimetric analysis (TGA). The maximum COD reduction using ZnO@CCAc-7 adsorbent was obtained to be 76.4% at the peak values of pH 6, dose 1.50 g/50 mL, time 160 minutes and temperature 30 ͦC. The various adsorption models Hill, Khan, Redlich–Peterson, Toth, Koble–Corrigan and Freundlich were found close-fitted to the adsorption process. It was observed that the COD removal adsorption technique ensued to a pseudo-first-order rate of kinetics. The negative value of Gibb's free ΔG0 and positive values of the enthalpy change (∆H° = 25.64 kJmol-1) indicates that the process of COD removal using ZnO@CCAc-7 adsorbent was spontaneous and endothermic in nature. Furthermore, response surface methodology with a subset of Central composite design was also studied in detail to optimise the COD removal efficiency. [ABSTRACT FROM AUTHOR]

In this study, zirconia-modified alumina support (S) was used to investigate Ga-promoted Ni catalysts for dry reforming of methane (DRM). The catalysts (Ni + (0–3) wt% Ga/S) were prepared using the wet impregnation method and calcined at 700 °C for 3 h. The inclusion of Ga enhanced the surface area, basicity, and metal-support interaction of the Ni-Ga/S catalysts. Smaller Ni particles containing Ga were seen in the TEM. The most active and stable catalyst was Ni + 2.0 Ga/S, having a conversion of 35% CO2 and 28% CH4 at 600 °C and displaying less (17%) carbon deposition. Furthermore, the DRM process was optimized by a mathematical model. The model determined the optimal conditions as follows: temperature (800 °C), gas flow rate (GHSV—30,000 ml h−1gcat−1), and methane to carbon dioxide ratio (1:1). The model predicts CH4 and CO2 conversions of 76.76% and 82.0%, respectively, and an H2/CO ratio of 1.02, compared to experimental results showing CH4 conversion at 74.56%, CO2 conversion at 83.25%, and an H2/CO ratio of 1.01. The model demonstrates excellent agreement with the experimental observations, exhibiting less than 3% error. [ABSTRACT FROM AUTHOR]

In this study, the treatability of olive mill wastewater by iron-activated persulphate (PS) oxidation was investigated. Central Composite Design (CCD) was applied to optimise the process parameters and establish a mathematical model for total phenol, chemical oxygen demand (COD), and colour removal from olive mill wastewater. The effect of process variables (PS dose, Fe2+ dose, initial pH, and reaction time) on pollutant removal efficiency was evaluated. The correlation coefficients of the quadratic polynomial equations were high for COD, total phenol, and colour removal by PS oxidation, and the model was found to be applicable. Optimum conditions determined by the developed model for maximum COD removal were pH 5, PS dose 206.7 mM, Fe2+ dose 70 mM, and reaction time 95 min. The COD, total phenol, and colour removal efficiencies estimated by the applied model were 46.74%, 94.62%, and 96.04%, respectively. The removal efficiencies obtained under optimum conditions as a result of the validation experiments were 45.5%, 93.8%, and 95.5% for COD, total phenol, and colour removal, respectively. The results of the study showed that PS oxidation in which Fe2+ is used as an activator is a suitable alternative for olive mill wastewater treatment. [ABSTRACT FROM AUTHOR]

The present investigation deals with the optimization of various parameters for extraction of oleoresins from Syzygium aromaticum (L.) Merr. and L.M. Perry buds (clove) using microwave assisted extraction (MAE) and ultrasound assisted extraction (UAE) by response surface methodology comparing the results with Soxhlet extraction (SE). The chemical composition of oleoresins was studied by GC-MS analysis. This was followed by testing their antibacterial potential against Escherichia coli, Yersinia enterocolitica, Staphylococcus aureus and Bacillus sp. and antioxidant potential. The maximum yield of clove oleoresin (COR) was obtained by UAE (42.00%) at 1:35 (solid to liquid ratio), 70°C for 12.50 min followed by SE (41.38%) and MAE (41.07%, 1:31 (solid to liquid ratio), 625 W for 60 s). The COR extracted by MAE showed the maximum percentage of various oxygenated terpenes (76.96%), followed by UAE (74.98%) and SE (44.92%). The major compound found in CORs extracted by MAE and UAE was eugenol acetate and for SE was 4,8,13-duvatriene-1,3-diol. The CORs extracted by MAE exhibited maximum antibacterial potential with minimum inhibitory concentration (MIC) which is the lowest COR concentration that inhibited the detectable growth of the test microorganisms in the range of 2.80–4.20 mg/ml followed by UAE (3.20–4.45 mg/ml) and SE (3.75–4.56 mg/ml). The COR extracted by MAE also exhibited maximum antioxidant activity against mustard oil degradation having the least increase in peroxide value, anisidine value, thiobarbituric acid value and total oxidation value after 28 days of storage. Hence, the maximum yield of COR was obtained by UAE but the maximum antibacterial and antioxidant potential was shown by COR extracted by MAE. Hence, COR extracted by MAE can be used as a natural food preservative as an alternative to synthetic food preservatives. [ABSTRACT FROM AUTHOR]

Background: Sumatriptan is one of the most essential drugs for treating migraine. However, dosage-related side effects are still a worry despite its 14 % oral bioavailability and recurrence of migraine-associated diseases. Methodology: The fundamental focus of the study is to develop the sumatriptan intra-nasal nano-ethsomal gel by film hydration technique with the aid of QbD principles that govern the varied compositions and blends of polymers like HPMC K100M and Phospolipon 90G to develop a sustained release dosage form. Results and discussion: The preliminary FT-IR and DSC studies revealed no interactions between the drug and their physical mixtures. The present study considered three observable responses: vesicle size, zeta potential, and percent drug release after 24 h, taken into consideration during the optimization of the ethosomal formulations utilizing 32 central composite designs (CCD). The vesicle size (122.23 nm), zeta potential (-40.2 mV), and drug release percentage (92.61 %) for all formulations were seen in the F12 batch after 24h. The p-XRD and SEM studies indicated that the nano-ethosomal gel was stable. The stability studies indicated the preparation of a more stable formulation for the parameters under the study protocol. Conclusion: Using a novel intra-nasal brain targeting approach by adapting the film hydration technique, the current issues might be addressed, and the drug's duration of residence at the absorption site uptake substantially increase. To efficiently modify the drug's residence through the intra-nasal route, this work focuses on developing a nano-ethosomal gel loaded with sumatriptan.

Discharge of pharmaceutical wastewater into surface and underground water has harmful effects on human health and living organisms, even in low concentrations. For this reason, pharmaceutical wastewater treatment is very important. In this research, wastewater treatment of Aria Pharmaceutical's Fluoxetine production unit was studied using γ-alumina catalysts. The catalyst was synthesized using the co-precipitation method and characterized by XRD, FTIR, FESEM, EDX, and BET methods. In the synthesis of γ-alumina catalyst, aluminum nitrate was used as a precursor, and sodium carbonate was used as the precipitating agent. The central composite design method was used to design experiments and to model and optimize the wastewater treatment using catalytic ozonation. In addition, the effect of the operating parameters on the catalytic ozonation process of Fluoxetine-containing wastewater, including the inlet ozone concentration, the amount of the catalyst, and reaction time, were investigated. Based on the obtained results, a significant agreement was observed between the experimental data of COD removal for wastewater and the values predicted by the CCD method. The results of the Pareto analysis showed that among the studied operational parameters, the reaction time, the amount of catalyst, and the initial concentration of ozone are the most effective parameters on the COD removal with percentages of 35.58%, 34.64% and 10.87%, respectively. Finally, by optimizing the process, the maximum value of COD removal of 92.13% was obtained experimentally for pharmaceutical wastewater using catalytic ozonation process in the reaction time of 30 min, the amount of catalyst of 1 g/L and the ozone concentration of 30 mg/L as optimal conditions.

Abstract The co-precipitation approach is used in the current study to create an environmentally friendly Ag/Fe/ZnO nanocomposites utilizing an aqueous leaf extract of Embelia schimperia. The synthesized nanocomposite was characterized using Fourier-transform infrared, UV, X-ray, UV–vis, DLS, TGA, and SEM to determine its functional group, structure, bandgap energy, size distribution, a mass of loss, and energy gain or loss, and morphological structure, respectively. The bioactive components of Embelia schimperia, synthesized Ag/Fe/ZnO NCs and degradation of Amoxicillin via photocatalyst were assessed. The response surface methodology of central composite design (CCD) was used to examine and optimize the effects of three independent variables on the degradation of Amoxicillin under visible light. According to the experimental findings, the maximum photocatalytic degradation efficiency was achieved at green synthesized Ag/Fe/ZnO NCs dosage of 100 mg, a concentration of Amoxicillin of 30 mg/L and a radiation time of 180 min. Their findings show that Embelia schimperia extract-derived Ag/Fe/ZnO nanocomposites is a promising alternative for degradation of pharmaceuticals contamination of wastewater via photocatalytic under the given conditions.