Quadratic Polynomial Model Research Articles

Machine Learning, Analytical, and Numerical Techniques for Vibration Analysis of Submerged Porous Functional Gradient Piezoelectric Microbeams with Movable Supports

This research numerically and analytically examines the dynamics of underwater movable porous functional gradient (FG) microsize beams integrated with a piezoelectric layer. Also, the efficiency and accuracy of support vector machine (SVM) techniques in the vibration prediction of the microbeam are assessed. The dynamical simulation is conducted by considering the assumptions of Rayleigh beam theory, different porosity distribution models, nonlinear and linear stress–temperature relationships, and modified couple stress theory (MCST). The eigenvalues of the system, critical temperature increment, and critical speed of the microbeam are computed. Comparative studies are carried out, frequency analyses are performed, and stability diagrams are drawn. The impacts of microbeam geometry, fluid mass ratio, piezoelectric voltage, and axial force on stability behavior in variable complex environmental conditions are parametrically inspected. The outcomes revealed that the smaller the contribution of voids on the outer surface of the microbeam, the better the microbeam stability. It is understood that among the utilized regression-based SVMs, the quadratic polynomial and medium Gaussian kernel models have the highest performance and speed, respectively. These research outcomes will be advantageous for designing the next generation of targeted drug delivery devices.

Beyond bits and bytes: Examining the dynamic influence of digital economy on ecological footprint in OECD economies

This study explores the effect of digital economy on ecological footprint in 37 Organization for Economic Co-operation and Development (OECD) economies between 2007 and 2022. We employed different econometric models and techniques, such as the panel regression model, the polynomial quadratic model, the modified structural equation model, and the Sobel test. Our study results reveal that digital development directly reduces ecological footprint through improved energy-efficient data centers, optimized production processes, and real-time resource management. Additionally, the relationship between digital development and ecological footprint shows an inverted U-shaped pattern. This implies that the growth of digital economy initially increases the ecological footprint due to the resource-intensive nature of setting up digital infrastructure, including data centers and communication networks. However, as digital development matures, efficiency gains from technological advancements lead to a reduction in the ecological footprint. The mediation analysis reveals that economic growth, green technology adoption, and industrial structure transformation significantly mediate the nexus between digital economy and ecological footprint at a proportion of 85.2%, 31%, and 65.6%, respectively. From the findings of our study, significant policy implications are proposed to enhance environmental quality.

Physicochemical components, antioxidant activity, and predictive models for quality of soursop tea (Annona muricata L.) during heat pump drying

Abstract The peel and pulp of soursop are ideal for creating a new tea product, offering a unique flavor compared to traditional leaf tea. This study develops mathematical models to describe the drying process, decomposition of bioactive components, and antioxidant activity of soursop slices. The slices were dried at four temperatures (20–50°C) using industrial-scale heat pump drying. Changes in moisture ratio (MR) were calculated and compared with 30 previous models. Additionally, two and four mathematical models were used to analyze data on total flavonoid content (TFC) and antioxidant activity. The model fits were evaluated based on statistical parameters (R 2, root mean square error, χ 2). The results indicated that the drying process at 20°C involved two mechanisms following the Aghbashlo model (R 2 > 0.993). At higher temperatures, the moisture removal process followed a single mechanism. Zero order, first order, and polynomial quadratic models were suitable for describing TFC decomposition and antioxidant activity, depending on the temperature. The activation energy of MR (29.89 kJ/mol) was lower than that of 2,2′–azino-bis–3–ethylbenzothiazoline–6–sulfonic acid (37.02 kJ/mol) and 2,2–diphenyl–1-1-picrylhydrazyl (32.12 kJ/mol), indicating drying efficiency and retention of bioactive components. The study’s findings are expected to enhance quality, improve economic efficiency, and expand the market for soursop tea.

Margin of safety for needle puncture of a radial artery in children: Recommendation for ultrasound-guided cannulation.

The radial artery is commonly selected for arterial puncture and cannulation, but radial nerve palsy may occur. To minimize possible damage to the nerve, needle puncture should be made within the margin of safety (between the wrist to the distal end of the radial artery and the radial nerve running in parallel). In adults, the margin of safety for radial artery puncture is approximately 6.8cm from the wrist in men and approximately 5.4cm in women, but the margin of safety is not known in children of different age groups. Using an ultrasound device, we measured the margin of safety in 100 anesthetized patients aged 0months to 15yr. Polynomial quadratic regression models were made, and the lower limit of the prediction interval was regarded as the margin of safety. These results were then compared with the results obtained in adults. The margin of safety became wider as a child grows older, and the height, weight, and age were all suitable explanatory variables to predict the margin of safety, providing fairly a constant predicted margin of safety from a few millimeters in neonates to approximately 4cm in adolescents (much narrower than in adults). In children and adolescents, the margin of safety for radial artery puncture is much narrower than in adults, and these findings support the recommendation to use ultrasound guidance during radial artery puncture in children and adolescents, to minimize the risk of associated complications. jRCT1032230243.

Optimization of process parameters for polishing aero-engine blade with abrasive cloth wheel considering spindle vibration and polished roughness

The vibration of machine tool spindle is very important for machining. Firstly, in order to explore the relationship between spindle vibration and process parameters, the spindle vibration acceleration when polishing aero-engine blade was measured, and the quadratic polynomial models between the spindle vibration acceleration in X, Y and Z direction and the process parameters were established. Secondly, a quadratic polynomial model for the influence of process parameters on polished surface roughness was also determined. Thirdly, through the Analysis of Variance (ANOVA) and main effect analysis, it can be seen that the spindle speed has the greatest impact on the vibration. Finally, a multi-objective optimization model was established with the optimization objective of minimizing spindle vibration acceleration and polished surface roughness, and the optimal process parameters were solved using genetic algorithm. The optimal process parameters were verified and the results show that the polished surface roughness with the optimal process parameters are all less than 0.4 μm, and the deviation rates between the theoretical optimization results of spindle vibration acceleration and the experimental results are all less than 10%, indicating that the optimization results are good.

Short communication: Estimation of the dietary standardized ileal digestible valine to lysine ratio required for 40 to 130 kg pigs during the finisher periods

BackgroundThree experiments were conducted separately to determine the optimum standardized ileal digestible (SID) valine (Val) to lysine (Lys) ratio for early finishing (Experiment 1, 40 to 75 kg bodyweight), finishing (Experiment 2, 75 to 100 kg bodyweight), and late finishing (Experiment 3, 100 to 130 kg bodyweight) pigs. Dietary SID Val: Lys ratios were designed at 0.61, 0.65, 0.69, 0.73, and 0.77. The optimal SID Val: Lys ratio was estimated by different regression models, including a quadratic polynomial model, a two-slope quadratic broken-line model, a curvilinear-plateau model, and a one-slope straight broken-line model.ResultsIn Exp.1, a total of 550 early finishing pigs (initially 40.3 kg bodyweight) were used in a 38-day growth trial. Pigs consuming 0.61 dietary SID Val: Lys ratio had lower final bodyweight compared to those fed 0.69 in diets. Using regression models, the optimal dietary SID Val: Lys requirement for average daily gain (ADG) was between 0.63 and 0.68, and for feed to gain ratio (F: G) was between 0.62 and 0.68, respectively. In Exp.2, 525 finishing pigs (initially 76.4 kg) were used in a 26-day trial. Based on regression models, estimate of the required SID Val: Lys for ADG was between 0.65 and 0.71, and for F: G was between 0.64 and 0.70, respectively. In Exp.3, 640 late finishing pigs (102 kg bodyweight) were used in a 27-day trial. No significant improvement was found for performance parameters of pigs from 100 to 130 kg, while 0.73 SID Val: Lys ratio resulted in the highest ADG and the lowest F: G from a numerical point of view.ConclusionsThese findings indicated that the optimum SID Val: Lys requirement for pigs from 40 to 75 kg was between 0.62 and 0.68, and for pigs from 75 to 100 kg was estimated to be between 0.64 and 0.71, using different regression models.

Optimizing the content of Li2CO3, Na2SO4 and TEA in fly ash–cement system by response surface methodology

With an optimized dosage, hardening accelerators become a vital means of modifying fly ash-cement system (FAC). This study comprehensively investigated the mechanical properties of FAC modified by Li2CO3, Na2SO4, and triethanolamine (TEA) under different dosages, and optimized the dosage of accelerators through the response surface method (RSM). The synergistic effect of accelerators on the hydration of FAC was characterized by thermogravimetric differential scanning calorimetry (TG-DSC), X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS). The results demonstrated that the factors and response value followed a quadratic polynomial model. The regression coefficients R2 of the model were all greater than 0.9, indicating good agreement with the experimental data. The content of Li2CO3 and Na2SO4 had an extremely significant effect on the compressive strength of 1d and 3d, followed by TEA. The optimal mix ratio predicted by RSM was 0.12 % Li2CO3, 0.47 % Na2SO4, and 0.40 % TEA. Early hydration stages revealed that the combined action of these accelerators increased the formation of CH, CaCO3, and amorphous C-(A)-S-H gel. Microscopically, the surface of fly ash exhibited alkali-induced corrosion, thereby enhancing its pozzolanic reactivity.

Improving AGB estimations by integrating tree height and crown radius from multisource remote sensing.

Precise estimation of forest above ground biomass (AGB) is essential for assessing its ecological functions and determining forest carbon stocks. It is difficult to directly obtain diameter at breast height (DBH) based on remote sensing imagery. Therefore, it is crucial to accurately estimate the AGB with features extracted directly from RS. This paper demonstrates the feasibility of estimating AGB from crown radius (R) and tree height (H) features extracted from multi-source RS data. Accurate information on tree height (H), crown radius (R), and diameter at breast height (DBH) can be obtained through point clouds generated by airborne laser scanning (ALS) and terrestrial laser scanning (TLS), respectively. Nine allometric growth equations were used to fit coniferous forests (Larix principis-rupprechtii) and broadleaf forests (Fraxinus chinensis and Sophora japonica). The fitting performance of models constructed using only "H" or "R" was compared with that of models constructed using both combined. The results showed that the quadratic polynomial model constructed with "H+R" fitted the AGB estimation better in each vegetation type, especially in the scenario of mixed tall and short coniferous forests, in which the R2 and RMSE were 0.9282 and 25.30 kg (rRMSE 17.31%), respectively. Therefore, using high-resolution data to extract crown radius and tree height can achieve high-precision, global-scale estimation of forest above ground biomass.

OPTIMIZATION OF ENZYMATIC HYDROLYSIS CONDITIONS FOR ANTIBACTERIAL PEPTIDES PRODUCTION AGAINST PANTOEA SPP. CAUSING RICE LEAF BLIGHT

The Central Composite Design (CCD) within the Response Surface Methodology (RSM) was applied to optimize the enzymatic hydrolysis process. This process used Alcalase® to hydrolyze Bactronophorus thoracites protein with the goal of maximizing its antimicrobial effects. Four distinct parameters were identified as independent variables: pH (A: 8.5–10.5), temperature (B: 45–65 °C), hydrolysis time (C: 120–360 min), and enzyme-to-substrate ratio (D: 1.45%–2.65% w/v). Meanwhile, the antimicrobial activity was chosen as the response variable, specifically against Pantoea ananatis (Y1) and Pantoea stewartii (Y2). According to the findings, the constructed quadratic polynomial model showed a significant correlation with the experimental data, as evidenced by the coefficient of determination (R2) values for antimicrobial activity: Y1 being 0.9893 (p < 0.0001) and Y2 at 0.9848 (p < 0.0001). Optimal antimicrobial activity for Bactronophorus thoracites protein hydrolysates (BTPH) was recorded at 46.748% against P. ananatis and 40.768% against P. stewartii. This result was observed under the optimal conditions of pH 9.5, temperature 55ºC, hydrolysis duration of 240 minutes, and 2.05% w/v enzyme-to-substrate ratio. There was a notable alignment between the actual and predicted values from our models, with the Residual Standard Error (RSE) values falling under 5%. Furthermore, the established Minimum Inhibitory Concentration (MIC) was 250µg/mL, and the Minimum Bactericidal Concentration (MBC) was 500µg/mL for both P. ananatis and P. stewartii. In conclusion, the findings suggest that the refined BTPH has great promise as an effective bioactive component for agricultural use.

Application of Response Surface Methodology for concentration of fluorosilicic acid by extraction technique with benzyl alcohol as extractant

As a kind of alternative of natural fluorinated minerals and raw material for producing anhydrous hydrogen fluoride, fluorosilicic acid has attracted more and more attention. In order to raise its utilization rate, dilute fluorosilicic acid solution coming from chemical enterprises needs to be concentrated. The extraction technology with benzyl alcohol as extraction agent was used to concentrating fluorosilicic acid aqueous solution. In order to determine the optimizing operation conditions of the extracting process, single - factor experiments were carried out to confirm the significant affecting factors and their operating range. Then the Response Surface Methodology (RSM) was conducted to accomplish regression of a nonlinear quadratic polynomial model to the experimental data and statistical analysis. Based on these studies, the optimal technical parameters of extracting process are acquired by optimization of the model using the Design-Expert 13 software. The statistical analysis for the fitting response surface quadratic equation model indicated that the model was reliable and accurate with very low p-values (<0.0001), the predicted values with the model equation had remarkable consistency in experimental data. By a great number of optimizations carried out with the Design Expert 13 software based on the fitting model equation, the optimal extractive processing conditions for concentrating fluorosilicic acid aqueous solution were obtained: the phase ratio 7, the extraction time 120.11 min and the extraction temperature 39.70 °C. The optimal concentration of fluorosilicic acid is 26.68 %. In order to increase the concentration of fluorosilicic acid, three-stage cross-current extraction for dilute fluorosilicic acid solution was carried out at the optimizing extracting conditions, 17.43 wt% fluorosilicic acid solution can be concentrated up to 37.46 wt%. The extractant-benzyl alcohol can be recovered with vacuum distillation and recovery rate reached up to 98 %.

Bio-process optimization for developing a turmeric (Curcuma longa Linn.) beverage fermented with functional lactic acid starter cultures

Turmeric, scientifically known as Curcuma longa, is a herbaceous plant characterized by its rhizomatous nature with remarkable chemical composition and biologically active compounds. Lactic acid bacteria (LAB) have been observed to break down complex polyphenols into simpler, more bioactive compounds through fermentation. The success of the fermentation process relies on various factors to achieve the desired end product. This study's main goal was to assess the feasibility of using turmeric as a fermentable substrate for LAB, with the intention of creating a non-dairy fermented beverage. The investigation delved into the impact of several fermentation parameters, namely Fermentation Temperature, pH (Lemon juice concentration), Inoculum concentration, and Substrate concentration (Turmeric concentration), on the phytochemical and antioxidant properties of the lactic acid-fermented turmeric beverage (FTB). Statistical analysis revealed that a quadratic polynomial model could effectively illustrate how these fermentation parameters influenced the beverage's phytochemical and antioxidant qualities. Visualization through response surface plots revealed that these independent variables significantly influenced the beverage's total phenolic content, total flavonoid content, and antioxidant properties. Optimal fermentation conditions were identified to yield the highest levels of phenolic, flavonoid, and antioxidant content. These conditions included a Fermentation Temperature of 37.45 °C, a pH of 5.62, an Inoculum concentration of 5.12%v/v, and a Substrate (turmeric) concentration of 2.28%w/v. Under these precise conditions, experimental results closely aligned with predicted values for total phenolic content (57.46mg/100 ml), total flavonoid content (51.48mg/100 ml), and total antioxidant activity (72.24%). The overall acceptability of the fermented turmeric beverage reached a high 98.10%. Notably, the FTB exhibited significantly improved attributes such as astringency, flavor, taste, and overall acceptability when compared to the non-fermented turmeric beverage (NFTB), with statistical significance (P < 0.05).

Design of an experimental approach based on the contrast-to-noise ratio measurement for X-ray computed tomography parameters optimization applied to a carbon fiber-reinforced polymer materials scan

This paper proposes a systematic approach for the optimization of scan parameters for industrial X-ray computed tomography (XCT), as regard its specific application as diagnostic tool on carbon fiber-reinforced polymer materials (CFRP). This procedure allows the system operator to overcome suboptimal scan results due to a subjective choice of XCT parameters. In this work, XCT scan quality has been measured in terms of contrast-to-noise ratio (CNR) metric, by calculating it on collected XCT 2D projection images. A four-factor five-level central composite design (CCD) was implemented to perform experiments, and a quadratic polynomial model was chosen to describe the effects of XCT scanning parameters combination on CNR measurement and finally to predict optimal results. Analysis of variance was carried out to evaluate the significance of the model on the response, reporting a R2 of 97.1%, and response surface analyses were also performed for CNR optimization purposes. In order to validate the CCD results, different XCT parameters combinations, coming from the CCD analysis on projection images, were used to run different scans, and, as result, the optimal CNR predicted from the model was also reflected in an optimal CNR measured on the reconstructed XCT images.

Preparation, Characterization, and Testing of Compost Tea Derived from Seaweed and Fish Residues

Non-aerated compost tea (CT) was prepared from compost derived from rockweed (Ascophyllum nodosum) and fish (cod, common ling, haddock, saithe) residues that fermented in water. Electrical conductivity, pH, concentrations of dry matter, ash, C, macronutrients (N, P, K, Ca, and Mg), and micronutrients (Cu, Fe, Mn, Mo, and Zn) of CT prepared under different fermentation conditions were measured. The effects of process factors, i.e., water/compost mass ratio (4.2–9.8 g/g) and fermentation time (4.2–9.8 days = 100–236 h), on the physicochemical properties of CT were quantified using quadratic polynomial models. CT obtained at optimal levels of process factors (4.2 g/g and 5.6 days = 134 h) was tested for lettuce seed germination and seedling growth. Diluted CT (25% CT + 75% ultrapure water) improved seedling growth while achieving a high germination percentage (97%).

Leaching of Neodymium From Hard Disk Drive Magnet Waste Using Citric Acid‐ Design of Experiments and Optimization

AbstractNeodymium magnet waste recycling and precious metal recovery have drawn a lot of researchers’ attention because of their vital role in contemporary technology. In this work, the potential of citric acid for the leaching of neodymium from hard disk drive waste magnets has been examined using statistical approaches like full factorial design(FFD) and central composite design (CCD).The variables have been screened and conditions are optimized to obtain higher leaching. The polynomial quadratic Model proves effective to predict optimized conditions for neodymium leaching. Leachant concentration and temperature were screened as the most effective factors. Optimization conditions for the leaching process were achieved through central composite design, revealing that 2 mol/L citric acid and a temperature of 333 K provide the ideal conditions for the complete dissolution of neodymium. This extensive study contributes to sustainable materials management and resource conservation by illuminating the effective recovery of important metals from neodymium magnets.

Trimethoprim Removal from Aqueous Solutions via Volcanic Ash-Soil Adsorption: Process Modeling and Optimization

Antibiotic contamination of water sources is a significant environmental and public health concern. This contamination is classified among the most dangerous types of pollution currently because of their harmful effects. Therefore, it is essential to identify effective and environmentally friendly ways to deal with those dangerous compounds. Within this context, this work looked into whether soils made from volcanic ash could be used as cost-effective adsorbents to remove the antibiotic trimethoprim (TRM) from aqueous solutions. To examine the impacts of the main operating parameters on TRM removal, which are the initial antibiotic concentration (C), contact time (t), stirring speed (S), and solid-to-liquid ratio (R), a Central Composite Design (CCD) based on the Response Surface Methodology (RSM) was employed. Full quadratic polynomial models were used to correlate the experimental data, allowing for the estimation of each factor’s influence. With a predicted removal efficiency of 77.59%, the removal process optimization yielded the following set of optimal conditions: C = 4.5 mg/L, t = 45.5 min, S = 747 rpm, and R = 0.04 g/mL. Experiments conducted under predicted ideal conditions supported both the result and the previously developed model’s capacity for prediction. Additionally, the adsorption mechanism was also proposed based on the characterization of the adsorbent before and after the treatment. The study’s findings provide the possibility of using soils formed from volcanic ash as a cost-effective adsorbent material for the removal of TRM and likely other similar pollutants from contaminated waters.

Area extraction and growth monitoring of sugarcane from multi-source remote sensing images under a polarimetric SAR data compensation based on buildings

ABSTRACT Aiming at the issue of low accuracy in crop mapping and growth monitoring caused by imprecise calibration of radar time-series data, this paper proposed a Synthetic Aperture Radar (SAR) spatio-temporal error compensation method. By constructing a compensation reference image using the buildings with stable backscattering coefficients in the study area, the error correction of time-series SAR data was realized based on the compensation model. The compensated SAR data were used to establish the Sugarcane Growth Index (SGI) according to the growth curve of sugarcane. The sugarcane area was extracted after combining the compensated SGI and optical image, and the accuracy of F1 on sugarcane distribution extraction was 92.12%. There was an improvement of 4.11% compared with no compensation method. On this basis, the newly planted and ratoon sugarcane were further classified by the expectation maximization algorithm based on the compensated SAR image at the seedling stage. The newly planted sugarcane and the ratoon sugarcane could be accurately distinguished with area extraction accuracy of 82.06% and 80.59%, respectively. Moreover, the compensated SAR data of time series during the tillering to maturity stages were used to estimate the sugarcane height, yielding an R 2 value of 0.717 using a quadratic polynomial model. The Spatio-temporal error compensation method for distributed targets proposed in this study can reduce the loss of SAR data across various times and regions, and achieve accurate results of sugarcane distribution extraction and plant height estimation.

Adsorption of cationic dye onto Raphanus seeds: optimization, adsorption kinetics, thermodynamic studies

Dyes are one of the common contaminants in industrial wastewater. Adsorption is the most widely method which used to treat dye-contaminated water due to their easy use, cost-effectiveness, and their efficiency was high. The aim of this study is the investigating of the utilization of the activated carbon which prepared from Raphanus seeds solid residual (ACRS) as a low cost adsorbent for removing of cationic Methylene Blue dye (MB)from wastewater. measuring the surface area using BET methods and SEM. The FT‒IR and XRD was measured. Different variables (e.g.: initial concentration of the dye, pH, contact time, and dosage) have been studied. Process has been systematically investigated experimentally at (25 ± 1 °C). The % removal of MB reached 99.4% after 90-min MB adsorption (40 mg/L) was observed within 5 min of contact time for the Raphanus seeds solid residual (ACRS) dosage of 4 g/L. MB initial concentration (10 ppm) Raphanus seeds solid residual (ACRS) effectively adsorbed MB (> 99%) over a widely range of pH (from pH 2 to pH 8). However, a swift decline in removal was observed when the pH was set at 7. The results of the adsorption kinetics analysis indicate a strong correlation with the pseudo-second-order model, as evidenced by the high regression coefficients. However, the adsorption capacity diminished with a rise in temperature. Thermodynamic calculations of (MB) onto Raphanus seeds solid residual (ACRS) is an exothermic reaction. The results have been indicated that the effectiveness of MB removal by activated carbon prepared from Raphanus seeds solid residual is favorable under neutral conditions, Raphanus seeds solid residual (ACRS) can be considered an efficient, environmentally friendly, readily available, and economical adsorbent that could treat industrial wastewater contaminated with cationic textile dyes. The objective of the experiments was to investigate the impact of various factors on the response of a process or formulation. To accomplish this goal, response surface methodology (RSM) has employed as a statistical model. RSM is an efficient and effective method for optimizing processes through the use of a quadratic polynomial model. The utilization of RSM allows for a reduction in the number of experiments needed, thus minimizing the associated costs of extensive analysis. This method has been done using Box–Behnken Design (BBD) to optimize % removal of MB. The optimal conditions as obtained from the RSM is pH 7,contact time 120 min, initial concentration 10 ppm, ACRS dosage 1 g, adsorption temperature 45 °C.

Optimizing Ultrasonic‐Assisted Extraction for Enhanced Yield of Phenolic Compounds and Antioxidant Activity in Cold Brew Coffee

ABSTRACTThis study aimed to identify the best conditions for ultrasonic‐assisted extraction (UAE) of DPPH and phenolic compounds from cold brew coffee using Box‐Behnken Design (BBD) and Response Surface Methodology (RSM). It explored the effects of solid‐liquid ratio (5%–15%), extraction time (40–50 min), and ultrasonic power (70%–80%) on these compounds, finding that all factors significantly influenced the outcomes. Statistical analysis showed the data fit a quadratic polynomial model well, with R2 values of 0.9981 for phenolic compounds and 0.9799 for DPPH radicals. Using 3D surface and contour plots from these models, the optimal extraction conditions for these compounds from cold brew coffee were determined. The highest yields of total phenolic compounds and DPPH radical were obtained when samples were extracted at a 10% solid–liquid ratio, 45 min extraction time, and 75% ultrasonic power. Under these optimal conditions, total phenolic compounds and DPPH radical were 64.10 ± 0.31 gGAE/mL and 61.90 ± 0.14%, respectively, with a maximum caffeine content of 213.13 ± 0.23 mg/L. Gamma irradiation at kGy also reduced cold brew coffee's microbial content. This research may be a new alternative for producing cold brew coffee that will save time and help extend the shelf life.

Diffusion hysteresis in unsaturated porous media: A microfluidic study

In unsaturated flow studies, water saturation is commonly used as the sole descriptor for macroscale flow models. However, this approach often results in hydraulic hysteresis in capillary pressure and relative permeability during drainage and imbibition processes. Furthermore, the effects of these behaviors on solute diffusion remain unclear. To address this knowledge gap, we conducted microfluidic experiments to investigate these hysteresis relationships. We firstly implemented drainage and imbibition processes in the micromodel to establish pore-scale water configurations. Subsequently, we upscaled the capillary pressure and diffusion coefficients to the Representative-Elementary-Volume scale. Our results revealed that, at the same saturation levels, the unsaturated diffusion coefficients during drainage were at least 6.1 % higher than during imbibition, indicating the presence of diffusion hysteresis. We observed that this hysteresis was influenced by capillary number and residual water saturation. An increase in the capillary number reduced diffusion hysteresis, similar to the capillary pressure hysteresis. While a decrease in residual saturation rose diffusion hysteresis. We also proposed a quadratic polynomial model that effectively predicts the diffusion coefficient by incorporating both saturation and capillary pressure. This research emphasizes the importance of historical changes in unsaturated water flow, which hold significant implications for modeling solute transport processes.

Modeling and Optimization of Electrochemical Advanced Oxidation of Clopidogrel Using the Doehlert Experimental Design Combined with an Improved Grey Wolf Algorithm

In this research, the optimization of the electrochemical advanced oxidation treatment for the degradation of Clopidogrel was investigated. This study examined the influence of various experimental parameters including applied current, initial Clopidogrel concentration, and ferrous ion concentration by the use of the Doehlert design within a response surface methodology framework. The improved grey wolf optimizer was applied in order to define the optimum operating conditions. The monitoring of clopidogrel concentration during treatment revealed that complete disappearance of clopidogrel was achieved under an initial clopidogrel concentration of 0.02 mM, current intensity of 0.55 A, Fe2+concentration of 0.7 mM, and a reaction time of 20 min in a solution containing 50 mM Na2SO4 at pH 3. A quadratic polynomial model was developed, and its statistical significance was confirmed through the analysis of variance, demonstrating a high level of confidence in the model (R2 = 0.98 and p-value &lt; 0.05). Furthermore, following electrolysis treatment for 480 min, the synthetic clopidogrel solutions underwent mineralization, achieving a 70.4% removal rate of total organic carbon. Subsequently, the applicability of the optimized process was tested on real pharmaceutical wastewater, and mineralization was investigated under the identified optimal conditions, resulting in a total organic carbon removal rate of 87% after 480 min of electrolysis time. The energy consumption for this system was calculated to be 1.4 kWh·kg−1 of the total organic carbon removed. These findings underscore the effectiveness and potential applicability of the electrochemical advanced oxidation for industrial wastewater treatment.