Maximizing polyphenol yield: ultrasound-assisted extraction and antimicrobial potential of mango peel.

This study investigated the ultrasound-assisted extraction (UAE) techniques used to enhance the polyphenols and antioxidants of mango peel extract (MPE). Additionally, it explored the bacteriostatic activity of MPE against various microorganisms. The UAE method was optimized using response surface methodology (RSM) at different times, temperatures, and ratios, with optimal conditions found to be 35 minutes, 45 °C, and a 1:35 ratio. The optimized yield results for total polyphenol content (TPC) were 17.33 ± 1.57 mg GAE/g, total flavonoid content (TFC) was 12.14 ± 0.29 mg QE/g, and radical scavenging activity (RSA) was 72.11 ± 2.19%. These response models were extremely significant with p-values less than 0.05. MPE showed selective effectiveness against Bacillus cereus, Geobacillus stearothermophilus, and Escherichia coli (E. coli). The results highlight the potential of mango peel as a sustainable source of bioactive compounds, contributing to waste reduction in the food industry and the development of natural antimicrobial agents. This study contributes to further research on the application of MPE in processed foods.

Optimizing COP by RSM and MATLAB model of mini refrigerator based on thermoelectric units driven by solar photovoltaic.

Energy scarcity in the world and the pollutants resulting from excessive use of conventional energy aroused the need for sustainable alternatives that are environment friendly. A multi-use thermoelectric refrigerator powered by solar energy to obtain the lowest consumption with the highest efficiency. The designed refrigerator is based on the Peltier effect using Peltier units where a temperature difference is created between the junctions by applying a voltage difference across the junction. This study investigates the performance of a refrigerator cooling system powered by a photovoltaic (PV) system. The research aims to assess the efficiency, effectiveness, and feasibility of utilizing solar energy to drive refrigeration, particularly in off-grid or environmentally conscious applications. Through a comprehensive experimental setup and data analysis, the study examines energy consumption, cooling efficiency, and overall system performance under varying conditions. The findings contribute valuable insights into the potential of PV-powered refrigerators as sustainable cooling solutions. It relies on a control unit that measures the resulting temperature to determine the appropriate connection mode to give the highest cooling efficiency. The average solar radiation when operating for 8 h, for the different seasons of the year was 149.5, 67.5, 119.3, and 118.3 w/m2 in summer, winter, spring, and fall, respectively. The average cooling energy consumption was 107.25, 137.04, 107, and 138.08 w for temperatures (20 ± 1, 15 ± 1, 20 ± 2, and 15 ± 2) °C respectively that proof solar radiation is sufficient to produce energy for the summer of cooling temperatures up to 15 °C, while in the spring and fall it is sufficient to 20 °C. The Fast not Eco mode is the least energy consuming and the fastest cooling, it can be used for rapid cooling at a short time less than an hour. The best mode in the case of continuous operation is the case of as next Eco mode cooling temperature of 20 ± 0.1 °C. The MATLAB Simulink model was developed to reduce the design cycle and facilitate the integration of solar photovoltaic with the TEC. The optimal operating point is identified through simulation and validated through experimental analysis, the optimal COP was 71.089% by Response surface methodology (RSM).

Nanoporous Metatitanic acid on γ-Al2O3 aerogel for higher CO2 adsorption capacity and lower energy consumption.

Carbon dioxide capture has become an important issue in reducing atmospheric heat these days. In this study, adsorption of carbon dioxide by aerogel Gamma Alumina-Metatitanic Acid has been investigated and optimized. Morphological and structural analyses such as BET, FESEM, FT-IR, and XRD have also been conducted. In addition, Response surface methodology has been applied in order to achieve the optimal conditions, using a five-level Central composite design. The highest amount of adsorption, 12.874 (mmol/g), was recorded at a temperature of 20 (°C), pressure of 7 (bar), and 25 (%wt) of Metatitanic Acid. This was approximately 11.46% and 4.84% higher than those of mesoporous MgO and 4Azeolite, respectively. Regeneration of the adsorbent was also studied at different temperatures and process durations. Metatitanic acid, as a catalyst, reduces the temperature and regeneration time of the adsorbent by creating active sites and surface hydroxyl groups. It also lowers the required activation energy and enhances the thermal conductivity of the composite material. The optimal result was achieved at a temperature of 100 (°C) and a duration of 30 (min). Finally, isothermal and thermodynamic experiments were conducted to establish the most accurate predictive model and conditions, including Enthalpy, Entropy, and Gibbs free energy. The results indicate that the Freundlich model aligned well with the laboratory findings. Additionally, the negative values of Enthalpy, Entropy, and Gibbs free energy suggested that the adsorption process was physical, exothermic, and spontaneous.

Synthesis, characterization of hydroxyapatite from pomegranate fruit peel for Cr (VI) adsorption: Process modelling, kinetic and isotherm studies.

The present work focuses on preparation of hydroxyapatite from pomegranate peels by precipitation method. The hydroxyapatite derived from pomegranate fruit peels (HA-PP) was characterized by XRD, FT-IR, SEM-EDS and BET techniques. The HA-PP has mesoporous in structure and had an area of 99.021 m2/g. Further HA-PP was used as adsorbent for the removal of Cr (VI) ion particles from K2Cr2O7. The adsorption trials were executed and found the optimized solution using response surface methodology (RSM). The experiments included parameters like pH 2, initial chromium concentration 200 mg/L, adsorbent loading 0.8 g, and contact time 60 min, respectively. Cr (VI) removal was 89.4 % at the optimum combination of these process parameters. A mathematical and statistical optimizing technique response surface methodology (RSM) was applied to verify the interactive effects of various parameters on the adsorption capacity. The analysis of variance (ANOVA) was used to predict the adequacy of the model (F 82.16) shows developed model is valid with R2 value 0.987, and p-value (>0.1). In this the Langmuir adsorption isotherm and the pseudo-second-order kinetic model are well explained for Cr (VI) adsorption onto HA-PP. This reaction is spontaneous and endothermic, as indicated by the negative change in the standard free energy (ΔG0 = -0.1732) and ΔH0 (+4.71) value at the selected temperature. The ΔS0 (+15.89) further confirms that the randomness increased at the solid-solution interface during adsorption.

Optimization and prediction of paver block properties with ceramic waste as fine aggregate using response surface methodology.

The ceramic industry produces a significant volume of ceramic waste (CW), representing around 20-30% of its the entire output. The waste mostly comes from challenges noticed in the manufacturing process, overproduction, and damage to products. Considering the substantial worldwide production of ceramics, it is crucial to efficiently handle and recycle this waste to promote sustainability efforts. This study explores the conversion of ceramic waste into fine aggregates suitable for the production of paver blocks. Currently, a variety of assessments are being conducted to determine the effectiveness of these enhanced paver blocks. The evaluations involve aspects like compressive strength, water absorption (WA), dry density, flow table measurements, ultrasonic pulse velocity (UPV), and rebound hammer tests. The results indicate that replacing natural aggregates with up to 30% CW significantly improves compressive strength (CS) and Rebound results from tests. This study provides useful information into optimising the content of CW in paver blocks, contributing to the development of sustainable and economical construction materials. Furthermore, it focusses on minimising landfill waste and preserving natural resources.

Modeling of carbon dioxide absorption into aqueous alkanolamines using machine learning and response surface methodology.

This research focuses on modeling CO2 absorption into alkanolamine solvents using multilayer perceptron (MLP), radial basis function network (RBF), Support Vector Machine (SVM), networks, and response surface methodology (RSM). The parameters, including solvent density, mass fraction, temperature, liquid phase equilibrium constant, CO2 loading, and partial pressure of CO2, were used as input factors in the models. In addition, the value of CO2 mass flux was considered as output in the models. Trainlm, trainbr, and trainscg algorithms trained the networks. The results showed that the best number of neurons for MLP with one layer is 16; with two layers, 5 neurons in the first layer and 12 neurons in the second layer; and with three layers, 9 neurons in the first layer, 5 neurons in the second layer, and 1 neuron in the third layer. The best spread in RBF was found to be 2.202 for optimal network performance. Furthermore, statistical data analysis revealed that the trainlm function performs best. The coefficients of determination for RSM, MLP, RBF, and SVM for optimized structures are obtained at 0.9802, 0.9996, 0.9940, and 0.8946, respectively. The results demonstrate that MLP and RBF networks can model CO2 absorption using the trainlm, trainbr, and trainscg algorithms.

Box-Behnken design (BBD) for optimization and simulation of biolubricant production from biomass using aspen plus with techno-economic analysis.

The growing concern and limitations for existing lubricants have driven the need for biolubricants, extensively proposed as the most suitable and sustainable lubricating oils. Biolubricant refers to lubricants that quickly biodegrade and are non-toxic to humans and aquatic habitats. Over the last decade, there has been a significant increase in the production of biolubricants due to the rising demand for replacing petroleum-based lubricants with those derived from renewable sources like vegetable oils and lipase that are used in various applications. In this study biodiesel (FAME) produced from blending animal fats and waste cooking was used as a raw material with ethylene glycol for biolubricant production using a transesterification reaction in the presence of calcium oxide which considers the newest and novel part as there is no production of biolubricant from animal fats and waste cooking oil in previous researches. The reaction parameters of biolubricant production were optimized using response surface methodology (RSM) with the aid of Box Behnken Design (BBD) to study the effect of independent variables on the yield of biolubricant. These variables are temperature ranging from (100-150 °C), reaction time ranging from 1 to 4 h, and FAME (Fatty Acid Methyl Ester) to alcohol molar ratio ranging from (2:1) to (4:1). The highest biolubricant yield is 91.56% at a temperature of 141 °C, a FAME/alcohol molar ratio of 2:1, and 3.3 h. Various analyses were performed on the produced biolubricant at the optimum conditions. The results include a pour point of -9 °C, a flash point of 192 °C, a kinematic viscosity at 40 °C of 10.35 cSt, a viscosity index of 183.6, an ash content of 0.76 wt.%, and a carbon residue of 1.5 wt.%, comparing favorably with the ISO VG 10 standard. The production process of biolubricant was simulated with Aspen Plus version 11 using a Non-Random Two-Liquid (NRTL) fluid package. The simulation results indicated that the production process can be applied on an industrial scale. Economic analysis was performed on the biolubricants production plant. The total capital investment was $12.7 M with a payback period of 1.48 years and an internal rate of return (IRR) of 67.5% indicating the suitability and profitability of the biolubricant production.

Antibiotics pollutants in agricultural soil: Kinetic, sorption, and thermodynamic of ciprofloxacin.

The entry of antibiotics, as pollutants, into the environment has created great concerns. Environmental dynamics of antibiotics based on soil chemical properties need to be a better understanding of their chemical behavior. This research is focused on studying the adsorption behavior and kinetic mechanisms of ciprofloxacin (CIP) in an agricultural soil. For this purpose, a batch experiment was conducted at different times (5 min-24 h), and using initial concentrations of CIP (0-1 mmol L-1) in the soil. The adsorption processes as affected by pH and ionic strength were assessed based on the modeling with response surface methodology (RSM). According to the results, the sorption equilibrium was found within 240 min, and the pseudo second-order model was the best for describing the data. Increasing the initial CIP concentration increased CIP adsorption, but increases in ionic strength and pH had an inverse effect. Based on RSM modeling, the CIP adsorption was 7.31 and 7.03 (mg g-1) in the presence of NaCl and CaCl2 electrolytes, respectively, in the optimized conditions (pH 6.5 and ionic strength 0.01 mol L-1). The spontaneous nature of CIP adsorption was determined based on thermodynamic calculations (ΔG° = -10.8 to -12.4 kJ mol-1). The interaction of pH and ionic strength was described with the quadratic model. The obtained results contribute to understanding the CIP fate in the soil environment and facilitate decisions regarding entry and controlling soil contamination due to this antibiotic.

Integrated bioprocessing and genetic strategies to enhance soluble expression of anti-HER2 immunotoxin in E. Coli.

Immunotoxins are widely applied for cancer therapy. However, bacterial expression of immunotoxins usually leads to the formation of insoluble and non-functional recombinant proteins. This study was aimed to improve soluble expression of a novel anti-HER2 immunotoxin under the regulation of the trc promoter in Escherichia coli by optimization of the cultivation conditions using response surface methodology (RSM). To conduct RSM, four cultivation variables (i.e., inducer concentration, post-induction time, post-induction temperature, and medium recipe), were selected for statistical characterization and optimization using the Box-Behnken design and Design Expert software. Based on the developed model using the Box-Behnken design, the optimal cultivation conditions for soluble expression of anti-HER2 immunotoxin were determined to be 0.1 mM IPTG for induction in the LB medium at 33 °C for 18 h. The expressed immunotoxin was successfully purified using affinity chromatography with more than 90% purity and its bioactivity was confirmed using cell-based ELISA. Technical approach developed in this study can be generally applied to enhance the production yield and quality of recombinant proteins using E. coli as the gene expression system.

Sensitivity study on convective heat transfer in a driven cavity with star-shaped obstacle and hybrid nanofluid using response surface methodology.

Sensitivity analysis is significant for understanding and measuring the impact of various parameters and input variables on heat transfer phenomena. The main objective of the current work is to examine the sensitivity of a numerical analysis of mixed convection in a lid-driven square cavity with a magnetic field. The cavity also contains a heated, star-shaped obstacle and is filled with a hybrid nanofluid. The sensitivity analysis was conducted employing the statistical response surface methodology (RSM), while the numerical simulations used the Galerkin weighted residual finite element approach to solve the governing PDEs. The study investigates the impacts of four dimensionless factors: Ri, Re, Ha, and ϕ. The numerical observation was made that there exists an upward trend between the average heat transfer rate with Ri, Re, and ϕ, while there exists a downward trend with Ha. Furthermore, the average heat transfer rate increases by almost half (49.54 %) when ϕ increases from 1 % to 10 % and decreases by 5.97 % when the Ha increases from 0 to 60. Finally, the statistical investigation of the current model and testing techniques imply that R 2 values for the response function are high (98.72 %), suggesting that this model is appropriate for estimating Nu.

Small Regulatory RNAs of the Rsm Clan in Pseudomonas.

Bacteria of the genus Pseudomonas are ubiquitous on Earth due to their great metabolic versatility and adaptation to fluctuating environments and different hosts. Some groups are important animal/human and plant pathogens, whereas others are studied for their biotechnological applications, including bioremediation, biological control of phytopathogens and plant growth promotion. Notably, their adaptability is mediated by various signal transduction systems, with the post-transcriptional Gac-Rsm cascade playing a key role. This pervasive Pseudomonas pathway controls major transitions at the population level, such as motile/sessile lifestyle, primary/secondary metabolism or replicative/infective behaviour. A hallmark of the Gac-Rsm cascade is the participation of small, regulatory, non-coding RNAs of the Rsm clan. These RNAs are synthetised in response to cell-density-dependent autoinducer signals channelled through the GacS/GacA two-component system, and they counteract, by molecular mimicry, the translational control that RNA-binding proteins of the RsmA family exert over hundreds of mRNAs. Rsm RNAs have been investigated in a few Pseudomonas model species, evidencing the presence of a variable number and families of genes depending on the taxonomic clade. However, the global picture of the distribution of these riboregulators at the genus level was unknown until now. We have undertaken a comprehensive survey and annotation of the vast array of gene sequences encoding members of the Rsm RNA clan in 245 complete genomes that cover 28 phylogenomic clades across the entire genus. The properties of the different families of rsm genes, their phylogenetic radiation, as well as the features of their promoters and adjacent regions, are discussed. The novel insights presented in our manuscript will significantly boost research on the biology of these prevalent RNAs in understudied species of the genus Pseudomonas and closely related genera.

Optimization of double-cooking condition for low potassium potatoes using response surface methodology (RSM).

This study aimed to establish optimal double-cooking condition using response surface methodology that maintained hardness while maximizing potassium reduction rate. The experimental design was based on the first cooking time (4.5-5.5 min) and rinsing time (20-60 s) through central composite design. This study suggested an optimal double-cooking condition of 5.5 min for first cooking and 57.57 s for rinsing. The model corroborated that the double-cooking condition significantly influenced dependent variables, including potassium reduction rate, hardness, and color (b-value). As the first cooking time increased, the potassium reduction rate increased and the hardness and b-value decreased. SEM revealed that double-cooked potato had more organized and netted structure. This structure could be helpful to maintain hardness, but relatively large amount of potassium could be leached out. The established optimal double-cooking condition for potatoes holds promise for broadening the dietary options for chronic kidney disease patients.

"Enhancing polyamine enrichment from wheat germs: A study utilizing response surface methodology and liquid chromatography-mass spectrometry".

Wheat germ is one of the richest natural sources of polyamines, especially spermidine. Cell proliferation property of polyamines has given them inductive effects in the reduction of a variety of chronic diseases and fertility enhancement. Preparing a polyamine-rich extract powder from wheat germ for use in supplements is the aim of the present study. For the first time, the effects of three independent variables of clean-up replicate (A), extraction time (B), and solid-to-liquid ratio (C) on the response of total spermidine content (Y) were investigated using a central composite design optimizing polyamine enrichment. The optimal extraction conditions were 7 h, 3 clean-up replicates, and 1:4 solid to liquid ratio. This is the first production report of spermidine-enriched powder for encapsulation purposes. To obtain an acceptable rheological property, the polyamine-enriched extract was spray dried together with a selected group of excipients, among which glucose was evidenced as the best choice based on encapsulation properties.

Performance analysis of floating bifacial stand-alone photovoltaic module in tropical freshwater systems of Southern Asia: an experimental study.

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.

Photosystem modulation and extracellular silicification in green microalgae: Key strategies for lead tolerance and removal.

The escalating contamination caused by lead ions (Pb2⁺) and its harmful effects on all life forms has raised global concerns. Certain microalgae thrive in metal mining sites characterized by low pH and high concentrations of Pb2⁺, which are usually prohibitive for many microorganisms. Little is known about the mechanisms underlying the adaptation of such microalgae to these hostile conditions. In this study, we elucidated the adaptive strategies of the green microalga Micractinium belenophorum strain AUMW, isolated from a lead mining site, and its application for the removal of Pb+2. Results revealed that strain AUMW can efficiently tolerate up to 200 ppm of Pb+2 in an F/2 medium. Further experimental variables were optimized through response surface methodology (RSM), and 99.6 % removal of Pb2⁺ was achieved. Novel adaptive responses of strain AUMW to high levels of Pb2⁺ include: (i) activation of metal-protective response by modulation of quantum yield (F v /F m ) and non-photochemical quenching (NPQ) of photosystem II; (ii) extracellular silicification encapsulated cells of strain AUMW and altered cell morphology from oval to hexagonal; (iii) silicification prevented intracellular translocation of Pb+2; (iv) silicification boosted adsorption of Pb+2, thus enhanced its removal. This study offers new insights into the protective role of silicification in green microalgae and its potential for the removal of metals from metal-polluted sites, waste from energy storage battery industries, and spent batteries. It also provides a solid base to explore the genetic and metabolic pathways involved in the adaptation of strain AUMW to elevated levels of Pb+2.

Optimization of Rhizoclonium hieroglyphicum extract for enhanced synthesis of nickel oxide nanoparticles using response surface methodology and its potential exploration in biological application.

The study investigates the potential of Rhizoclonium hieroglyphicum as a novel source for synthesizing nickel oxide nanoparticles (RH-NiONPs) and evaluates its biological applications. Phytochemicals in the algal extract serve as capping, reducing and stabilizing agent for nickel oxide nanoparticles. The process variables were optimized using BBD based RSM to obtain maximum RH-NiONPs. Characterization of RH-NiONPs using UV-Vis and FT-IR spectroscopy reveals the plasmon resonance peak at 340 nm and the functional groups responsible for reduction and stabilization. XRD confirmed the crystalline nature while the stability and size of the RH-NiONPs were determined by DLS and zeta potential. Toxicity assessments demonstrated the effect of RH-NiONPs against Vigna radiata, Allium cepa and Artemia salina was low. RH-NiONPs revealed significant zone of inhibition against the selected bacteria and fungi. The results of larvicidal activity showed that RH-NiONPs are toxic to 4th instar larvae of Daphnis nerii. Also, RH-NiONPs efficiently decolorized Reactive Violet 13 (92%) under sunlight irradiation and the experimental data well fits to Langmuir isotherm along with pseudo second order kinetic model. The thermodynamic studies enunciate the exothermic and non-spontaneous photocatalytic decolorization of reactive violet 13. Thus, the current study assesses the eco-friendly and cost-effective nature of RH-NiONPs along with its biological applications.

Multi-objective optimization of an EDM process for Monel K-500 alloy using response surface methodology-multi-objective dragonfly algorithm.

Monel K-500 is a high-performance superalloy composed of nickel and copper, renowned for its exceptional strength, hardness, and resistance to corrosion. To machine this material more precisely and accurately, Electrical Discharge Machining (EDM) is one of the best choices. In EDM, material removal rate (MRR) and electrode wear rate (EWR) are crucial performance parameters that are often conflicting in nature. These parameters depend on several input variables, including peak current (Ip), pulse on time (Ton), duty cycle (Tau), and servo voltage (SV). Optimizing the EDM process is essential for enhancing performance. In this research, a set of experiments were conducted using EDM on Monel K500 alloy to determine the optimal process parameters. The Box-Behnken design was used to prepare the experimental design matrix. Utilizing the experimental data, a second-order mathematical model was developed using Response Surface Methodology (RSM). R2 value is found to be 99.40% and 96.60% for MRR and EWR RSM-based prediction model, respectively. High value of R2 is indicated is indicated good adequacy for prediction. The mathematical model further used in multi-objective dragonfly algorithm (MODA): a new meta-heuristic optimization technique to solve multi-objective optimization problem of EDM. The MODA is a very useful technique to achieve optimal solutions from the multi decision criteria. Utilizing this technique, a set of non-dominated solutions was obtained. Further, the TOPSIS method was used to determine the most desirable optimal solution, which was found to be 0.0135 mm3/min for EWR and 6.968 mm3/min for MRR. These results were obtained when the optimal process parameters were selected as Ip = 6 A, Ton = 200 µs, Tau = 12, and SV = 41.6 V. Operators can machine Monel K500 by selecting the above-mentioned optimal parameters to achieve the best performance.

RSM integrated GWO, Driving Training, and Election-Based Algorithms for optimising ethylic biodiesel from ternary oil of neem, animal fat, and jatropha.

The worldwide exploration of the ethanolysis protocol (EP) has decreased despite the multifaceted benefits of ethanol, such as lower toxicity, higher oxygen content, higher renewability, and fewer emission tail compared to methanol, and the enhanced fuel properties with improved engine characteristics of multiple-oily feedstocks (MOFs) compared to single-oily feedstocks. The study first proposed a strategy for the optimisation of ethylic biodiesel synthesis from MOFs: neem, animal fat, and jatropha oil (NFJO) on a batch reactor. The project's goals were to ensure environmental benignity and encourage the use of totally biobased products. This was made possible by the introduction of novel population based algorithms such as Driving Training-Based Optimization (DTBO) and Election-Based Optimization (EBOA), which were compared with the widely used Grey Wolf Optimizer (GWO) combined with Response Surface Methodology (RSM). The yield of NFJO ethyl ester (NFJOEE) was predicted using the RSM technique, and the ideal transesterification conditions were determined using the DTBO, EBOA, and GWO algorithms. Reaction time showed a strong linear relationship with ethylic biodiesel yield, while ethanol-to-NFJO molar ratio, catalyst dosage, and reaction temperature showed nonlinear effects. Reaction time was the most significant contributor to NFJOEE yield.The important fundamental characteristics of the fuel categories were investigated using the ASTM test procedures. The maximum NFJOEE yield (86.3%) was obtained at an ethanol/NFJO molar ratio of 5.99, KOH content of 0.915 wt.%, ethylic duration of 67.43 min, and reaction temperature of 61.55 °C. EBOA outperforms DTBO and GWO regarding iteration and computation time, converging towards a global fitness value equal to 7 for 4 s, 20 for 5 s and 985 for 34 s. The key fuel properties conformed to the standards outlined by ASTMD6751 and EN 14,214 specifications. The NFJOEE fuel processing cost is 0.9328 USD, and is comparatively lesser than that of conventional diesel. The new postulated population based algorithm models can be a prospective approach for enhancing biodiesel production from numerous MOFs and ensuring a balanced ecosystem and fulfilling enviromental benignity when adopted.

Investigating the potential of waste glass in paver block production using RSM.

The global surge in glass waste generation, exceeding 130 million tons annually, presents a pressing environmental issue, compounded by inadequate recycling practices, it is concerning that the global recycling rate for glass waste is below 50%. This research investigates the utilization of WG as a FA substitute in paver block to mitigate the ecological footprint of conventional paver block while enhancing its mechanical properties. WG's unique characteristics, such as high silica content and impermeability, make it a promising alternative. A comprehensive experimental approach, including tests like water absorption, dry density, workability, compressive strength, ultrasonic pulse velocity, and rebound hammer, demonstrated WG's potential to improve concrete's durability and performance. For instance, a 40% WGA replacement reduced the absorption rate 12%, while 20% WGA incorporation-maintained strength properties close to the control mix, with compressive strengths up to 30.80 MPa at 28 days. Employing RSM as predictive models, the study showed R2 values of 0.9513, 0.9983, 0.9156, 0.9925, and 0.9895 for water absorption, dry density, compressive strength, ultrasonic pulse velocity, and rebound hammer, respectively. This study offers supporting global research efforts to advance sustainable and affordable construction materials, leading to a significant reduction in landfill waste and the conservation of precious natural resources worldwide.

Organic acid-fractionated lignin silver nanoparticles: Antimicrobial, anticancer, and antioxidant characteristics.

Bioactive substances are utilized to treat a variety of diseases. Green lignin-mediated silver nanoparticles (L-Ag-NPs) have significant promise as a building block in the production of bio-renovation materials. The work optimized organic acid extraction to remove lignin from residual fermented hybrid Napier grass byproducts. We subsequently produced L-Ag-NPs. FTIR, XRD, DLS, and STEM characterized the sample. L-Ag-NPs were tested for antioxidant activity with the DPPH, DMPD, FRAP, and ABTS assays, as well as antibacterial activities. Antimicrobial activity was evaluated using four pathogenic bacteria (Klebsiella pneumonia, Pseudomonas aeruginosa, Staphylococcus aureus, and Escherichia coli). In contrast, cytotoxicity and ROS production assays were carried out using the HeLa cell line. The findings showed that L-Ag-NPs had high antioxidant efficiency. For each bacteria isolate, the antimicrobial activity showed favorable growth inhibition, with significant variations in L-Ag-NPs. L-Ag-NPs were reported to have an IC50 of 43.61 g/mL in the cytotoxicity test, and a significant increase in ROS generation was seen. In conclusion, L-Ag NPs have an excellent prospect in the pharmaceutical and biomedical industries and can be a dependable and environmentally safe material for their potential use.