Second-order Polynomial Model Research Articles

Structure-function relationship and diagnostic value of macular ganglion cell complex measurement using Fourier-domain OCT in glaucoma.

To evaluate the relationship between visual function and macular ganglion cell complex (GCC) thickness measured by Fourier-domain optical coherence tomography (OCT) and evaluate the diagnostic value of GCC measurement compared to retinal nerve fiber layer (RNFL) thickness and macular thickness in detecting early, moderate, and severe glaucomas. Subjects underwent standard automated perimetry (SAP), OCT imaging with optic nerve head mode and GCC mode. The relationship between OCT parameters (mean GCC thickness, mean RNFL thickness, and macular thickness) and perimetry global indices (mean deviation [MD] and pattern standard deviation [PSD]) was evaluated by regression analysis. Diagnostic values of mean RNFL thickness, GCC parameters, and macular thickness were compared with the area under the receiver operating characteristic curves (AUC). A total of 84 eyes, 42 of each normal and primary open-angle glaucoma patients were included in the study. Compared with linear models, second-order polynomial models better described relationships between GCC thickness and MD ( P < 0.001), and between GCC thickness and PSD ( P = 0.00). RNFL parameter, inferior RNFL thickness had the highest AUC for detecting early glaucoma. The AUC of mean GCC thickness for early glaucoma was higher than that of mean RNFL; however, the difference was not significant ( P = 0.09), which was higher than that of macular thickness. The relationship between visual field (VF) sensitivity and GCC thickness is best expressed by the curvilinear function. Macular GCC thickness and RNFL thickness showed similar diagnostic values but were better than macular thickness for detecting early glaucoma but inferior to macular thickness and RNFL thickness for detecting moderate glaucoma.

Ultrasound-assisted extraction of bioactive pigments from Spirulina platensis in natural deep eutectic solvents

Spirulina platensis biopigments have been documented as a potential source of nutritional, physiological, and pharmacological purposes due to the presence of bioactive pigments, total phenolic content (TPC) and the consequent antioxidant activity that these compounds present. Bioextracts market has increased in the last decades and is a key option for replacing fossil-derived products and promote the transition for a bio-based economy. To take advantage of these compounds more effectively, optimized extraction processes must be researched and used in biomass sources. The present study focused on optimizing the ultrasound-assisted extraction (UAE) using response surface methodology. Three factor and three level Box–Behnken design was used to optimize the extraction of bioactive pigments, and to investigate the effects of three independent variables, x\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$x$$\\end{document}1: extraction temperature (40–60 °C), x\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$x$$\\end{document}2: extraction cycle time (20–40 min), and x\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$x$$\\end{document}3: solvent-to-biomass ratio (50–70 mL/mg) on total pigment yield, antioxidant assay, and TPC (dependent variables). A second-order polynomial model was used for predicting the responses. Statistically, the model was validated using an analysis of variance. Results revealed that ultrasound-assisted temperature, time, and solvent-to-biomass ratio had a significant (p < 0.05) influence on the total pigment yield, while temperature and solvent-to-biomass ratio had a significant influence in the antioxidant activity, and temperature significantly influenced the total pigment yield. For total pigment yield, antioxidant activity, and total phenol content, the R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${R}^{2}$$\\end{document} values of the models generated were 0.8627, 0.8460, and 0.9003, respectively, indicating that the models developed based on second-order polynomials were satisfactorily accurate for analyzing interactions between parameters. Desirability functions showed that the optimal extraction parameters were temperature: 60 °C, extraction cycle time: 20 min; and a solvent-to-biomass ratio of 70 mL/mg. Under optimal conditions, experimental values for total pigment yield, total phenol content expressed as gallic acid equivalent (GAE), and antioxidant activity expressed as Trolox equivalent (TRE) were: 165.19 ± 1.01 mg/g Dry Matter (DM), 36.50 ± 0.98 mg GAE/g DM, and 37.98 ± 0.58 mg TRE/g DM, respectively. The experimental values showed a good agreement with the predicted values with residual standard low 1% under optimum conditions. This optimized ultrasound-assisted method in natural eutectic solvents is effective and scalable to a green extraction of the bioactive pigments from Spirulina platensis with potential application to food, pharmaceutical, functional materials, and packaging.Graphical

Dietary L-Lysine Requirement of Coho Salmon (Oncorhynchus kisutch) Alevins

The suitable dietary L-lysine concentration for coho salmon (Oncorhynchus kisutch) alevins was assessed by a dose response feeding trial. Six experimental diets were made with graded L-lysine concentrations of 2.29%, 2.81%, 3.32%, 3.80%, 4.27%, and 4.78% of the dry matter, respectively, each of which was fed to triplicate groups of 100 alevins (initial body weight: 0.30 ± 0.01 g) in 18 plastic baskets (water volume 240 L). The alevins were cultured in a flowing freshwater system and fed manually to apparent satiation four times a day for 12 weeks. The survival rate of alevins did not differ significantly among the dietary groups. The specific growth rate (SGR), protein efficiency ratio (PER), and body protein deposition (BPD) increased significantly (p &lt; 0.05) with the increase in dietary lysine concentration up to 3.80% and then reduced as lysine level further increased. The feed conversion ratio (FCR) had an inverse trend to SGR. The whole-body crude protein content of the alevins increased significantly with increasing dietary lysine level, while crude lipid content showed the opposite trend. In comparison, the contents of morphological indices, whole-body moisture, and ash were not affected significantly (p &gt; 0.05) by the different dietary lysine concentrations. The highest contents of lysine, arginine, and total essential amino acids (EAAs) were observed in the group with 4.27% dietary lysine concentration, which did not differ significantly from those in the 3.32%, 3.80%, and 4.78% groups but was significantly higher than those in the 2.29% and 2.81% groups. Similarly, valine had the highest content in the group with 4.78%. The variations in dietary lysine had no significant impacts on other EAA and non-EAA contents except glycine, which increased with increasing dietary lysine level. Second-order polynomial model analyses based on SGR, PER, BPD, and FCR evaluated the optimum L-lysine requirements of coho salmon alevins as 3.74%, 3.73%, 3.91%, and 3.77% of the diet or 6.80%, 6.78%, 7.11%, and 6.85% of dietary proteins, respectively.

Melon seed oil epoxidation: Kinetics and neuro-fuzzy evaluation

Melon seed oil (MSO) is characterized by unsaturated triglycerides, making it a suitable candidate for epoxidation. This work explored the kinetic and Optimization of MSO epoxidation by the in-situ generation of peroxyacetic acid. The formation of the epoxide group was studied over the reaction time at various temperatures. With catalyst concentration, time, and temperature as the process variables and oxirane value as the response, Box Behnken design with Response Surface Methodology (RSM) was used to simulate and optimize the epoxidation process of MSO. The in situ epoxidation process obtained the highest oxirane of 3.4 and 3.45 % at 70 °C and 500 rpm with significantly less oxirane cleavage. The rate constants ranged from 0.0119 to 0.0341 lmol−1.s−1 for the temperature range of 50 to 90 °C. Thermodynamic parameters such as a change in enthalpy and entropy were calculated to be 22.21 KJ/mol and -32.744 cal.mol−1.K−1, respectively. The results of the ANOVA revealed a second-order polynomial model, with R2 values of 0.9996, Adj R2 (0.9992), and Pred R2(0.9944) of 0.9992 and 0.994, showing a high significance level between the experimental and predicted results. The 3D plots revealed that the process variables considerably impacted the oxirane value. The optimal oxirane value of 3.96348 % was obtained at a stirring speed of 597.821 rpm, a reaction time of 3.96348 h, reaction temperature of 71.7146 °C with a desirability of 1.000. Adaptive neuro-fuzzy inference system (ANFIS) optimum result with tri membership function gave an MSE of (1.99E-6), and the models demonstrated significant predictive behavior with R2 (0.9996) and (0.9653) for RSM and ANFIS, respectively. The FT-IR and physicochemical characterization of the MSO confirmed a high degree of unsaturated fatty triglycerides that were suitably epoxidized.; hence the novelty of this study dwells on the kinetics and ANFIS modeling of the MSO epoxidation process, which explains the reaction mechanism and non-linear behaviours of the epoxidation process.

Modelling the complementary role of inert slag aggregate and waste glass on concrete mechanical strengths using the response surface and design-of-experiment approach

Recycling steel slag (SS) and waste glass (WG) in concrete represents a sustainability measure to promote the production of cost-effective and eco-friendly concrete. This study assessed the weight replacement effects of steel slag (SS) with coarse aggregate (up to 100 %), those of waste glass (WG) with cement (up to 30 %), and the water-to-binder ratio on the workability, density, compressive strength, and splitting strength. Multiple blends of the binary binders were examined using the design of experiments (DoE) approach to evaluate the technical feasibility of SS and WG and their synergistic effects in enhancing the properties considered. The second-order polynomial model used was sufficiently accurate to yield high correlation levels between the responses and the studied variables with high determination coefficient up to 98 %. The inclusion of WG in concrete produced with a 100 % replacement level of SS effectively addressed the site rheological pumping problems with higher strength, 58 % more in compressive and 33 % more in splitting strengths.

Anomaly detection and multi-step estimation based remaining useful life prediction for rolling element bearings

The prediction of the Remaining Useful Life (RUL) of rotating machinery targets the avoidance of sudden machine failures and the optimization of the maintenance schedules as well as the management of repairs and replacements. A number of statistical model-based prognostics methodologies have been proposed in recent literature but a number of open challenges still exist, blocking their integration in the industry: (i) The extraction of a high-quality Health Indicator (HI) is critical for bearings’ prognostics but till now the trend of many classic HIs is often disturbed; deviating from a monotonical increase or decrease. (ii) The detection of the Start Prediction Time (SPT) on the HI is usually required in order to improve the accuracy of the RUL estimation but it can be incorrect especially when distinct random outliers occur. (iii) The widely applied RUL estimators, e.g. the Kalman filter (KF) and the Particle filter (PF), belong to the category of single-step estimation techniques that assume that the current step estimation depends only on the state of the previous step. However, the occurrence of bearings’ damage is usually not a sudden change but an accumulated process. Therefore a novel prognostic strategy for Rolling Element Bearings (REB) is proposed in this paper, which integrates a robust anomaly detection technique, the Support Vector Data Description (SVDD), with a multi-step estimation method, the Moving Horizon Estimation (MHE). Various advanced entropy and sparsity HIs are extracted by signals filtered at different frequency bands. By comparing all the extracted HIs based on a proposed criterion, a premium prognostic HI is chosen from a specific frequency band. Moreover, the SVDD, deployed and combined with several proposed constraints, can robustly detect the occurrence of a bearing fault and decide the proper SPT. Furthermore, the MHE is combined with two popular exponential statistical models and a second-order polynomial model for bearings’ prognostics. Experimental results from fifteen degraded bearings demonstrate that the MHE outperforms the classic Kalman filter and Particle filter. Moreover, the polynomial model achieves a better RUL estimation compared to the two classic exponential models in combination with the MHE.

Enhancing stability and antimicrobial activity of spearmint essential oil nanoemulsion through formulation optimization by mixture experimental design and in vitro drug release study

Spearmint essential oil (SEO) has been widely recognized for its therapeutic properties in treating gastrointestinal, respiratory, carminative, diuretic, antispasmodic, and sedative ailments. Moreover, it is commonly utilized as a flavoring agent in various food and beverage products. However, the effectiveness of SEO for medicinal purposes is hindered by its limited water solubility. Hence, the objective of this research was to determine the optimal conditions for producing a nanoemulsion of SEO by measuring turbidity through a mixture experimental design. The study aimed to investigate the impact of different formulation variables on turbidity as the response variable. These variables included PEG-40 hydrogenated castor oil (HCO) (1%–2% w/w), Tween 80 (1%–3% w/w), Tween 20 (1%–3% w/w), propylene glycol (PG) (5%–20% w/w), and polyethylene glycol 400 (5%–20% w/w). The results of the experimental design showed that the obtained data could be adequately fitted in a second-order polynomial model for the prediction of nanoemulsion turbidity with a multiple regression coefficient of 0.9704. The particle size value at the optimum condition was 81.28 nm, which was matched with the result of transmission electron microscopy (TEM). The thermodynamic and long-term stability of the prepared nanoemulsion were investigated. Furthermore, the developed nanoemulsion exhibited better antimicrobial activity against E. coli. In vitro release testing showed that the release of the optimized nanoemulsion was significantly increased. This study demonstrated that SEO is capable of forming stable nanoemulsions for use in delivery systems of flavoring agents in the food industry.

Optimization of extraction process for classic prescription Yihuang Decoction based on Box-Behnken design-response surface methodology, standard relation, and analytic hierarchy process combined with entropy weight method

Based on the concept of quality by design(QbD), the Box-Behnken design-response surface methodology combined with standard relation(SR) and analytic hierarchy process(AHP)-entropy weight method(EWM) was applied to optimize the extraction process of the classic prescription Yihuang Decoction. The content of geniposidic acid, phellodendrine hydrochloride, and berberine hydrochloride in Yihuang Decoction, the extract yield, and fingerprint similarity were used as the critical quality attributes(CQAs) of the extraction process. The extraction time, water addition, and extraction times were used as the critical process parameters(CPPs). After determining the levels of each factor and level through single-factor experiments, response surface experiments were designed according to the Box-Behnken principle, and the experimental results were analyzed. The SR between each sample and the reference sample under various evaluation indicators of different extraction parameters was calculated. The weights of the five evaluation indicators were determined using AHP-EWM, followed by comprehensive evaluation. A function model between CPPs and CQAs characterized by comprehensive scores was established to predict the optimal extraction process parameters. In the final comprehensive weight coefficients, the yield rate accounted for 43.1%, and the content of berberine hydrochloride, phellodendrine hydrochloride, and geniposidic acid accounted for 35.1%, 6.3%, and 15.5%, respectively. After comprehensive score analysis with SR, the established second-order polynomial model was statistically significant(P&lt;0.01, and the lack of fit was not significant). The predicted optimal extraction conditions for Yihuang Decoction were determined as follows: 8-fold volume of water, extraction time of 1.5 h, and extraction once. The mean comprehensive score of the validation experiment was 85.77, with an RSD of 0.99%, and it met the quality control stan-dards for the reference sample of Yihuang Decoction. The results indicate that the optimized extraction process for Yihuang Decoction is stable and reliable, and the water extract is close in quality attributes to the reference sample. This can serve as a foundation for the research and development of granules in the future. Box-Behnken design-response surface methodology combined with SR and AHP-EWM can provide references for the modern extraction process research of other classic prescriptions.

Optimization pilot scale study on ammonia nitrogen removal by bio filter

In order to obtain the optimal conditions for ammonia nitrogen (AN) wastewater treatment by bio filter (BF), the effects of ratio of carbon to nitrogen (C/N), pH, and hydraulic load (HL) on the AN degradation were studied by Response Surface Methodology (RSM). Central Composite Design (CCD) experiments were conducted, and the response of the AN removal rates were fitted to a second-order polynomial model. The analysis of variance showed that the model was accurate and reliable. Through model fitting, the optimal condition for AN removal was: C/N of 18.95, pH of 7.78, and HL of 1.04 d−1. The maximum AN removal rate predicted by the model was 91.90%, accorded with the experimental verification value of 91.37% under the optimal condition. The research provided valuable demonstration for optimizing process parameters on AN removal in BF.

Sustainable Recovery of Phenolic Compounds from Distilled Rosemary By-Product Using Green Extraction Methods: Optimization, Comparison, and Antioxidant Activity.

Rosemary solid distillation waste (SWR), a by-product of the essential oil industry, represents an important source of phenolic antioxidants. Green technologies such as ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE), and accelerated solvent extraction (ASE) of phenolic compounds from SWR were optimized as valorization routes to maximize yield, rosmarinic acid (RMA), carnosol (CARO) and carnosic acid (CARA) contents. Response surface methodology was used in this context, with ethanol concentration (X1), extraction temperature (X2), and time (X3) being the independent variables. A second-order polynomial model was fitted to the data, and multiple regression analysis and analysis of variance were used to determine model fitness and optimal conditions. Ethanol concentration was the most influential extraction parameter, affecting phenolic compounds, while the influence of other parameters was moderate. The optimized conditions were as follows: X1: 67.4, 80.0, and 59.0%, X2: 70, 51, and 125 °C, and X3: 15, 10, and 7 min for MAE, UAE, and ASE, respectively. A comparison of optimized MAE, UAE, and ASE with conventional Soxhlet extraction techniques indicated that ASE provided a higher extraction yield and content of phenolic compounds. However, UAE represented the best process from an environmental point of view, allowing an improved extraction of phenolics from SWR with high energy efficiency and low energy costs.

Extraction,modification and characterization of native litchi seed (Litchi chinesis Sonn.) starch.

Litchi seeds, owing to their high starch content, have the potential to serve as a valuable non-conventional source of starch with versatile applications. This study aimed to optimize the extraction of native litchi seed and its modification using citric acid. Response surface methodology was used to determine the optimal combination of independent variables; extraction temperature (30 - 60 ° C) and extraction time (4-20hours) for the attainment of maximum starch yield (%). Starch was then chemically modified with citric acid concentrations of 20 and 40% to investigate its effect on physicochemical, morphological, and functional properties. The second-order polynomial model effectively described the experimental data, demonstrating a satisfactory fit for the observed results. The optimized condition with the highest starch recovery (212.4 g Kg-1 ) was found to have an extraction temperature of 30° C and an extraction time of 11 hours. It was observed that with an increase in concentration of citric acid has resulted in a decrease in amylose content, swelling power, and solubility, while the water absorption capacity of modified starch increased. The SEM micrographs showed that citric acid modification resulted in surface irregularities, while the shape and size of granules remain unaffected. Not much difference has been observed in the XRD pattern of modified starch except for the decrease in intensities of peaks. An effect on the thermal properties of modified starch was also reported. Results obtained from the study reveal that extraction temperature and extraction time are critical factors, exerting a significant effect on the extraction yield of starch. Furthermore, modified starches with improved functional properties can serve as novel and versatile source of starch in various food and non-food sectors. This article is protected by copyright. All rights reserved.

Bathymetries of proglacial lakes: a new data set from the northern Tien Shan, Kazakhstan

Between 2009 and 2020, 74 bathymetric surveys of 57 glacial lakes were conducted in the northern Tien Shan using the ecosounding technique. The surveys provided data on lake depths and other parameters characterising the three-dimensional lake geometry, and bathymetrically derived lake volumes. The sample included 21 glacier-connected lakes, 27 lakes formed on the young moraines without glacier-connected with glacier tongue, eight lakes formed on the older moraines and one rock-dammed lake. The lakes’ volumes ranged between 0.029x105 and 53.89x105 m3 with the largest value of mean depth was 23 m. There is a statistically significant correlation between lake depth and width, length and area, best approximated by the power, linear, and polynomial models, with coefficients of determination ranging between 0.50 and 0.78 for the glacier-connected lakes. The power equations underestimated both depths and volumes of larger lakes but the second-order polynomial model provided a closer approximation in the study region. The obtained data were combined with the bathymetrically derived depth and volume data published in the literature extending the global data set of bathymetries of lakes with natural dams. The area-depth scaling equations derived from the combined data set showed a considerable improvement in correlation between area and depth in comparison with the earlier studies. The measured bathymetries of the glacier-connected lakes were compared with bathymetries of the same lakes simulated using GlabTOP2 model and published simulated ice thickness data. There is generally a good agreement between the measured and simulated bathymetries although GlabTOP2 tends to overestimate lake depths. The data from the bathymetric surveys and GlabTOP2 model are used by the practitioners to reduce and avoid risks associated with glacier lake outburst floods and are important instruments of the regional strategy of adaptation to climate change.

Vacuum-Packed Pork Sausages with Modified Casing Added with Orange Peel Extracts: Evaluating In Vitro Antioxidant Activity via Hyperspectral Imaging Coupled with Chemometrics

The antioxidant activities (in vitro) of vacuum-packaged dry-cured sausages stored for 1 year, which were treated with varying concentrations of extracts from orange peel (EFOP) in a modification solution, were evaluated using a central composite design. The individual variables: soy lecithin concentration, soy oil concentration, treated time, lactic acid addition, EFOP addition, and dependent variable [i.e., in vitro antioxidant activity] were analyzed by response surface methodology. Among the 32 treatment combinations, treatment 26 (central point) exhibited a higher 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity compared to the control group (natural hog casing without modification). Spectral pre-treatments were applied to enhance the robustness of the model, and a partial least squares regression model (PLSRM) was fitted. The results of the response surface methodology indicated that the interactive effects of a high [soy lecithin concentration] × a high [EFOP addition] yielded a DPPH assay result of over 35%. The determination coefficients (R2 value) of the second-order polynomial model for the simultaneous effects on in vitro antioxidant activity reached 65.28%. The PLSRM developed using average reflectance data after the first derivation pre-treatment demonstrated a higher R2 value in the calibration group compared to the untreated data. The first principal component accounted for 77.39% of the overall attributes and effectively differentiated the sausages’ antioxidant activity from 31.88%.

Three leaved yam starch physical / engineering properties evaluation using Response Surface Methodology and Artificial Neural Network network

This study evaluated some physical properties of three-leaved yam starch (TLYS). The angle of repose (AOR) (wood and glass), bulk density, true density, bulk volume, and surface area were analyzed with varying temperatures (60 °C, 67.5 °C, and 75 °C) at a constant air velocity (1.75 m/s), as temperature increased, the AOR glass decreased significantly. In contrast, the AOR metal increased, the highest bulk density (0.61 kg/m3) was observed at 75 °C, bulk volume and bulk density decreased significantly with an increase in temperature, and surface area increased with an increase in temperature. The effect of the operating parameters (time, temperature, and air velocity) on the responses (bulk density, true density, bulk volume, and surface area) was investigated, modeled, and optimized via Response Surface Methodology (RSM). The Analysis of Variance (ANOVA) showed a second-order polynomial model with bulk density (R2- 0.999, Adj R2-0.9997, Pred R2-0.9979), true density (R2- 0.999, Adj R2-0.9997, Pred R2-0.9977), bulk volume (R2- 0.9970, Adj R2-0.9932, Pred R2-0.9527) and surface area (R2- 0.9953, Adj R2-0.9892, Pred R2-0.9247) indicating a close relationship between the experimental and predicted responses. The 3D graphs showed a significant impact of the process factors on the response. The optimal bulk density (0.81 kg/m3), true density (0.55 kg/m3), bulk volume (25 m3), and surface area (684 m2) were obtained at a temperature (57.5 °C), time (3 h), and air velocity (2.25 m/s). Artificial Neural Network (ANN) technique with 3 backpropagation algorithm (B·P.) algorithm was employed to analyze TLYS engineering properties; each algorithm was evaluated with 3 neurons in the input layer, 10 neurons in the hidden layer, and an output layer with four neurons. Coefficient of determination (R2) and mean square error (M.S.E.) have been implemented and correlated to test the adequacy of the model. Results showed that the Bayesian regularization had the best prediction for all the algorithms with an MSE (2.5465E-9) and R2 (9.999E-1) for the responses. Scanning Electron Micrograph (SEM) and proximate analysis indicate that the TLYS contains starch. This information from this study can be effectively utilized in the design parameters of the TLYS post-harvest process/machinery. Hence the post-harvest process evaluates the nutritional quality, protects food safety, and reduces losses between harvest and consumption.

Optimization of exopolysaccharide produced by L. kefiranofaciens ZW3 using response surface Methodology

ABSTRACT The primary objective of this study was to optimize the production of exopolysaccharide (EPS) produced by L. kefiranofaciens ZW3 through the utilization of response surface methodology (RSM). Central Composite Design (CCD) was used along with three variables to study the response variable. The effects of lactose (0.16–1.84%), tryptophan (0.16–0.84%), and pH (5.06–7.24) on EPS production were studied. RSM analysis revealed that coefficient of determination (0.9907) was good for the second-order polynomial model. The optimum values of explanatory variables were 0.36% lactose, 0.23% tryptophan, and pH value of 5.19. Additional experiments were performed to confirm the adequacy of this model. The predicted value of EPS at optimized level was 1609 mg/L, while its experimental value at optimized level was 1602 ± 3 mg/L. This study could help to produce higher amount of EPS from L. kefiranofaciens ZW3, which has a lot of industrial applications.

Statistical Analysis and Forecasting of Indexes of Gender Asymmetry in the Labor Market of the Orenburg Region

All-Russian and regional labor markets operate in an unstable socio-economic situation, which can contribute to the emergence of gender disproportion. The study of gender asymmetry is considered the most popular direction during periods of “economic upheaval”, since this kind of instability increases the inequality of men and women in various spheres of life. The state of turbulence in which the labor market of Russia as a whole and each of its regions is located contributes to the adaptation of each of its segments to new forms of work. This study examines the results of an analysis of the structure and trends in the dynamics of indexes of employment and unemployment of the male and female population in the Orenburg region for 2016-2021. The choice of the time period is justified by the uneven development of both the world and the Russian economy. Modern economic realities, in which the labor market exists, develops both in the country as a whole, and in its regions, experiencing a number of shocks, determine the scientific novelty of the issues under consideration.Purpose of the study. The main idea of the paper done is the possibility of using the methods of economic and statistical analysis to study dynamic differences in gender structures according to various characteristics, development directions that determine gender asymmetry in the labor market of the Orenburg region, and predict its main indexes for the medium term.Materials and methods. The information base of the study was the statistical information of Orenburgstat, which characterizes gender asymmetry in the labor market of the Orenburg region. To achieve this goal, a set of methods of economic and statistical analysis was applied, including the calculation of indexes of the structure and structural differences, dynamics, identifying trends, forecasting, as well as presenting the results of the study using tables and figures.Results. According to the results of the study, an average portrait of a busy and carefree person by gender was compiled. The characteristics of the male and female population in the labor market of the Orenburg region in 2021 compared to 2016 are highlighted. The study of structural differences was carried out according to the criterion of V. Ryabtsev, during which it was noted that there were no significant changes in the structures of employed men and women. A significant level of differences characterizes the age structure of unemployed men and women in 2021 compared to 2016, as well as the structure of unemployed men by level of education. The study made it possible to assert that in the dynamics of indexes characterizing gender inequality in the labor market of the Orenburg region, unstable changes are observed. The study tested the hypothesis of the presence/absence of trends in the time series of indexes characterizing gender asymmetry in the labor market of the region. For this purpose, one of the modifications of the series criterion was used. The assumption that there is no trend in the dynamics series under consideration has not been confirmed, therefore, the trend exists. Taking into account this circumstance, trend models were created, among which, according to the best statistical characteristics, second-order polynomial models were selected. With the help of the selected polynomials of the second degree, it was determined that in the dynamics of employment and unemployment indexes of the male and female population, downward trends of change prevail. Further, their prospective indexes were calculated. Conclusion. The study made it possible to analyze the main vectors that are emerging in the field of employment and unemployment in the regional labor market by gender, and to predict their main indexes for the medium term. In the dynamics of the number of both male and female labor force in the Orenburg region, unstable trends will be observed in the future. The number of women employed in the region’s economy will grow; the number of unemployed women will decrease. In the forecast period, the number of employed men in the economy of the Orenburg region will change under the influence of a downtrend. The number of unemployed men in the period from 2023 to 2025 will tend to decrease.

Box-Behnken Design for Assessing the Efficiency of Aflatoxin M1 Detoxification in Milk Using Lactobacillus rhamnosus and Saccharomyces cerevisiae.

Milk contaminated with aflatoxin can lead to liver cancer. Aflatoxin B1 (AFB1), a serious animal feed contaminant, is transformed into Aflatoxin M1 (AFM1) and secreted in milk. In this study, a biological method using probiotic bacteria, Lactobacillus rhamnosus (L. rhamnosus) in combination with Saccharomyces cerevisiae (S. cerevisiae), was used to assess their antiaflatoxigenic effect in animal milk. A Box-Behnken design was used to establish the optimal ratio of L. rhamnosus and S. cerevisiae, incubation time, and temperature for efficient AFM1 detoxification from milk. To achieve this, the primary, interaction, and quadratic effects of the chosen factors were investigated. To investigate the quadratic response surfaces, a second-order polynomial model was built using a three-factor, three-level Box-Behnken design. The quantity of AFM1 was detected by the ELISA technique. The results of these experiments obtained an optimum condition in AFM1 detoxification of the three tested factors in order to maximize their effect on AFM1 detoxification in milk. The model was tested in three highly contaminated milk samples to assure the efficacy of the model. AFM1 detoxification was up to 98.4% in contaminated milk samples. These promising results provide a safe, low-cost, and low-time-consuming solution to get rid of the problem of milk contamination with AFM1.

Application of Box-Behnken Design in Production of Monoglyceride with Esterification of Glycerol and Oleic Acid.

Monoglyceride MG has a wide function in the food industry, in particular as a natural emulsifier, pharmaceuticals, cosmetics, antioxidant, and antibacterial. Therefore, the production of polyol ester from esterification of acid (OA) and glycerol was investigated. The process optimization was performed using a Box-Behnken design, examining the effects of temperature, molar ratio, and catalyst amount. For predicting the optimal point, a second-order polynomial model was fitted to correlate the relationship between independent variables and response (% MG). The effects of temperature (100, 150, and 200 °C); catalyst amount (4, 10, and 16% w/w); and glycerol/oleic acid ratio (1:1, 1:2, and 1:3) were investigated and found to deeply affect the reaction outcome. At the optimal reaction conditions: 200 °C, 0.2% w/w KSF, and a glycerol/oleic acid ratio (3:1), more than 71.8% monoglycerides with selectivity of 80% were obtained. Confirmation experiments were performed to demonstrate the effectiveness of this approach, and the characterization of monoglycerides was performed using high-performance liquid chromatography (HPLC).

Biochar and pyrolysis liquid production from durian peel by using slow pyrolysis process: Regression analysis, characterization, and economic assessment

This study examines the conversion of durian peel to biochar and pyrolysis liquid via slow pyrolysis. The central composite design was utilized to optimize the conditions of three independent variables, namely pyrolysis temperature, cooling temperature, and holding time. Analysis of variance revealed that only pyrolysis temperature had a significant effect on biochar and pyrolysis liquid yields. The biochar and pyrolysis liquid yields fit by a second-order polynomial model agreed well with experimental results. As the pyrolysis temperature increased, the solid product yield decreased, while the pyrolysis liquid yield increased. The highest biochar and pyrolysis liquid yields were 56.11% and 38.53% that derive at 300 and 600 °C of pyrolysis temperature, respectively. The validation of both prediction models showed over 96% agreement. Biochar of high heating value (26.55 MJ/kg) was obtained at 600 °C pyrolysis temperature and 30 min holding time. According to the Van Krevelen plot, the molar ratios of the H/C and O/C of the biochar obtained at 600 °C of pyrolysis temperatures were similar to coal material. The high-quality biochar was of carbon storage class 4 according to the IBI classification; and the characteristics of pyrolysis liquid met community product standards of Thailand. An economic analysis was performed to assess the feasibility of converting 60 tons/year of durian peel into biochar and pyrolysis liquid. An internal project rate of return (IRR) of 25.91% with a payback period of 1.58 years was estimated. The findings of this study indicate the economic viability of immediately deploying large-scale pyrolysis utilizing a waste stream from agriculture.

Statistical Analysis and Forecasting of Gender Asymmetry Indexes in the Labor Market of the Orenburg Region

The labor market in Russia and its regions operates in an unstable socio-economic situation, which can contribute to the emergence of gender disproportion. The study of gender asymmetry is considered the most popular direction during periods of “economic shocks”, since this kind of instability increases the inequality of men and women in various spheres of life. The state of turbulence in which the labor market of Russia as a whole and each of its regions is located contributes to the adaptation of each of its segments to new forms of work. This study examines the results of an analysis of the structure and trends in the dynamics of indexes of employment and unemployment of the male and female population in the Orenburg region for 2016-2021. The choice of the time frame is justified by the uneven development of both the world and the Russian economy. Modern economic realities, in which the labor market exists and develops as a country as a whole and its regions, experiencing a number of shocks, determine the scientific novelty of the issues under consideration.Purpose of the study. The main idea of the work done is the possibility of using the methods of economic and statistical analysis to study dynamic differences in gender structures according to various characteristics, development directions that determine gender asymmetry in the labor market of the Orenburg region, and predict its main indexes for the medium term.Materials and methods. The information base of the study was the statistical information of Orenburgstat, which characterizes gender asymmetry in the labor market of the Orenburg region. To achieve this goal, a set of methods of economic and statistical analysis was applied, including the calculation of indexes of the structure and structural differences, dynamics, identifying trends, forecasting, as well as presenting the results of the study using tables and figures.Results. According to the results of the study, an average portrait of a busy and carefree person by gender was compiled. The characteristics of the male and female population in the labor market of the Orenburg region in 2021 compared to 2016 are highlighted. The study of structural differences was carried out according to the criterion of V. Ryabtsev, during which it was noted that there were no significant changes in the structures of employed men and women. A significant level of differences characterizes the age structure of unemployed men and women in 2021 compared to 2016, as well as the structure of unemployed men by level of education.The study made it possible to assert that in the dynamics of indexes characterizing gender inequality in the labor market of the Orenburg region, unstable changes are observed. The study tested the hypothesis of the presence/absence of trends in the time series of indexes characterizing gender asymmetry in the labor market of the region. For this purpose, one of the modifications of the series criterion was used. The assumption that there is no trend in the dynamics series under consideration has not been confirmed, therefore, the trend exists. Taking into account this circumstance, trend models were constructed, among which, according to the best statistical characteristics, secondorder polynomial models were selected. With the help of the selected polynomials of the second degree, it was determined that in the dynamics of employment and unemployment indexes of the male and female population, downward trends of change prevail. Further, their prospective indexes were calculated.Conclusion. The study made it possible to analyze the main vectors that are emerging in the field of employment and unemployment in the regional labor market by gender, and to predict their main indexes for the medium term. In the dynamics of the number of both male and female labor force in the Orenburg region, unstable trends will be observed in the future. The number of women employed in the region’s economy will grow; the number of unemployed women will decrease. In the forecast period, the number of employed men in the economy of the Orenburg region will change under the influence of a downtrend. The number of unemployed men in the period from 2023 to 2025 will tend to decrease.