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Nowadays, there are many preconditions and circumstances for conducting shadow schemes in the financial market. Therefore, the level of risk of participation of bank and non-bank financial intermediaries in such schemes is assessed as high. The lack of a practical methodology for assessing the development trajectory of financial intermediaries raises the question of the need for preventive control and quality modeling of their growth dynamics. The study aims to identify and formalize the patterns of development paths of banking and non-banking financial intermediaries based on the Harrington desirability function, which will be used to identify risk patterns as indicative patterns of financial intermediaries’ participation in shadow schemes. The sample includes 13 banking institutions, 3 credit unions, 3 pawnshops, 3 insurance companies, and 3 financial companies. The obtained results showed the relationship between the financial intermediary risk level in terms of its participation in shadow schemes and the phases of the economic cycle as a catalyst for the economic dynamics of the formal and informal economy. Thus, in 2012–2015, most financial intermediaries were in the zone of most significant risk, especially banks, characterized by economic, social, and political instability. Today, banks are in the group with a controlled level of risk of participation in scheme operations. Over the years analyzed, a stable neutral level of risk of participation in shadow schemes was inherent in most non-bank financial institutions. They were less sensitive than banks to the phases of the economic cycle. AcknowledgmentAlina Bukhtiarova and Yevgeniya Mordan gratefully acknowledge financial support from the Ministry of Education and Science of Ukraine (0120U100473, 0121U100469).

Plant-based materials are an important source of bioactive compounds (BC) with interesting industrial applications. Therefore, adequate experimental strategies for maximizing their recovery yield are required. Among all procedures for extracting BC (maceration, Soxhlet, hydro-distillation, pulsed-electric field, enzyme, microwave, high hydrostatic pressure, and supercritical fluids), the ultrasound-assisted extraction (UAE) highlighted as an advanced, cost-efficient, eco-friendly, and sustainable alternative for recovering BC (polyphenols, flavonoids, anthocyanins, and carotenoids) from plant sources with higher yields. However, the UAE efficiency is influenced by several factors, including operational variables and extraction process (frequency, amplitude, ultrasonic power, pulse cycle, type of solvent, extraction time, solvent-to-solid ratio, pH, particle size, and temperature) that exert an impact on the molecular structures of targeted molecules, leading to variations in their biological properties. In this context, a diverse design of experiments (DOEs), including full or fractional factorial, Plackett–Burman, Box-Behnken, Central composite, Taguchi, Mixture, D-optimal, and Doehlert have been investigated alone and in combination to optimize the UAE of BC from plant-based materials, using the response surface methodology and mathematical models in a simple or multi-factorial/multi-response approach. The present review summarizes the advantages and limitations of the most common DOEs investigated to optimize the UAE of bioactive compounds from plant-based materials.

The aim of the present study was to optimize a chromatographic method for the analysis of atorvastatin (acid and lactone forms), ortho- and para-hydroxyatorvastatin by using an experimental design approach. Optimization experiments were conducted through a process of screening and optimization. The purpose of a screening design is to identify the factors that have significant effects on the selected chromatographic responses, and for this purpose a full 23 factorial design was used. The location of the true optimum was established by applying Derringer’s desirability function, which provides simultaneously optimization of all seven responses. The ranges of the independent variables used for the optimization were content of acetonitrile in mobile phase (60–70%), temperature of column (30–40 °C) and flow rate (0.8–1.2 mL min−1). The influences of these independent variables were evaluated for the output responses: retention time of first peak (p-hydroxyatorvastatin) and of last peak (atorvastatin, lactone form), symmetries of all four peaks and relative retention time of p-hydroxyatorvastatin. The primary goal of this investigation was establishing a new simple and sensitive method that could be used in analysis of biological samples. The method was validated and successfully applied for determination of atorvastatin (acid and lactone forms) and its metabolites in plasma.

Milling AA6082T6 materials is a difficult venture because of their heterogeneity and a slew of problems, inclusive of surface roughness, that get up for the duration of the machining method and are connected to the material’s homes and slicing settings. The optimization of machining parameters is a crucial section inside the manufacturing method. This research introduces a unique approach for improving machining settings whilst milling aluminum alloy. A technique notorious as desirability function analysis (DFA) turned into worn to optimize machining parameters. DFA is a effective tool for optimizing multi-reaction problems. Milling research for aluminum alloy were completed using tungsten carbide end milling inserts in dry situations, based totally on Taguchi’s L9 orthogonal array. Multi-response issues, along with machining pressure and surface roughness, are used to optimize machining parameters including feed charge, spindle speed, and depth of reduce. person desirability values from the desirability characteristic analysis are used to create a composite desirability cost for the multi-responses. The most effective ranges of parameters had been discovered based at the composite desirability fee and substantial contribution of parameters has been determined the usage of analysis of variance.

In this study, a multi-objective optimization technique involving response surface methodology (RSM)-based desirability function approach is used in optimizing the process parameters for friction stir welding of AA6063-T6 pipes. Two process parameters, namely, tool rotational speed and weld speed, are optimized for achieving a weld joint having superior tensile properties, viz., maximum yield, and ultimate tensile strength and maximum % of elongation. A regression model, with a 95% confidence level, is developed using response surface methodology to predict the tensile strength of the weld joint. ANOVA technique is used to determine the adequacy of the developed model and identify the significant terms. The desirability function is used to analyze the responses and predict the optimal process parameters. It is found that tool rotational speed and weld speed have equal influence over the tensile strength of the pipe weld. Tool rotational speed 1986 rpm and weld speed 0.65 rpm have yielded a maximum ultimate tensile strength of 167 MPa, yield strength of 145 MPa, and % elongation of 8.3, under considered operating conditions. Microstructural attributes for superior weld properties are also discussed.

Studies investigating how biodiversity affects ecosystem functioning increasingly focus on multiple functions measured simultaneously (\"multifunctionality\"). However, few such studies assess the role of species interactions, particularly under alternative environmental scenarios, despite interactions being key to ecosystem functioning. Here we address five questions of central importance to ecosystem multifunctionality using a terrestrial animal system. (1) Does the contribution of individual species differ for different ecosystem functions? (2) Do inter-species interactions affect the delivery of single functions and multiple functions? (3) Does the community composition that maximizes individual functions also maximize multifunctionality? (4) Is the functional role of individual species, and the effect of interspecific interactions, modified by changing environmental conditions? (5) How do these roles and interactions change under varying scenarios where ecosystem services are weighted to reflect different societal preferences? We manipulated species' relative abundance in dung beetle communities and measured 16 functions contributing to dung decomposition, plant productivity, nutrient recycling, reduction of greenhouse gases, and microbial activity. Using the multivariate diversity–interactions framework, we assessed how changes in species identity, composition, and interspecific interactions affected these functions in combination with an environmental driver (increased precipitation). This allowed us to identify key species and interactions across multiple functions. We then developed a desirability function approach to examine how individual species and species mixtures contribute to a desired state of overall ecosystem functioning. Species contributed unequally to individual functions, and to multifunctionality, and individual functions were maximized by different community compositions. Moreover, the species and interactions important for maintaining overall multifunctionality depended on the weight given to individual functions. Optimal multifunctionality was context-dependent, and sensitive to the valuation of services. This combination of methodological approaches allowed us to resolve the interactions and indirect effects among species that drive ecosystem functioning, revealing how multiple aspects of biodiversity can simultaneously drive ecosystem functioning. Our results highlight the importance of a multifunctionality perspective for a complete assessment of species' functional contributions.

Various chitosan (CS)-based nanoparticles (CS-NPs) of ciprofloxacin hydrochloride (CHCl) have been investigated for therapeutic delivery and to enhance antimicrobial efficacy. However, the Box–Behnken design (BBD)-supported statistical optimization of NPs of CHCl has not been performed in the literature. As a result, the goal of this study was to look into the key interactions and quadratic impacts of formulation variables on the performance of CHCl-CS-NPs in a systematic way. To optimize CHCl-loaded CS-NPs generated by the ionic gelation process, the response surface methodology (RSM) was used. The BBD was used with three factors on three levels and three replicas at the central point. Tripolyphosphate, CS concentrations, and ultrasonication energy were chosen as independent variables after preliminary screening. Particle size (PS), polydispersity index (PDI), zeta potential (ZP), encapsulation efficiency (EE), and in vitro release were the dependent factors (responses). Prepared NPs were found in the PS range of 198–304 nm with a ZP of 27–42 mV. EE and drug release were in the range of 23–45% and 36–61%, respectively. All of the responses were optimized at the same time using a desirability function based on Design Expert® modeling and a desirability factor of 95%. The minimum inhibitory concentration (MIC) of the improved formula against two bacterial strains, Pseudomonas aeruginosa and Staphylococcus aureus, was determined. The MIC of the optimized NPs was found to be decreased 4-fold compared with pure CHCl. The predicted and observed values for the optimized formulation were nearly identical. The BBD aided in a better understanding of the intrinsic relationship between formulation variables and responses, as well as the optimization of CHCl-loaded CS-NPs in a time- and labor-efficient manner.

The development of novel antioxidant compounds with high efficacy and low toxicity is of utmost importance in the medicine and food industries. Moreover, with increasing concerns about the safety of synthetic components, scientists are beginning to search for natural sources of antioxidants, especially essential oils (EOs). The combination of EOs may produce a higher scavenging profile than a single oil due to better chemical diversity in the mixture. Therefore, this exploratory study aims to assess the antioxidant activity of three EOs extracted from Cymbopogon flexuosus , Carum carvi , and Acorus calamus in individual and combined forms using the augmented-simplex design methodology. The in vitro antioxidant assays were performed using DPPH and ABTS radical scavenging approaches. The results of the Chromatography Gas-Mass spectrometry (CG-MS) characterization showed that citral (29.62%) and niral (27.32%) are the main components for C. flexuosus , while d -carvone (62.09%) and d -limonene (29.58%) are the most dominant substances in C. carvi . By contrast, β-asarone (69.11%) was identified as the principal component of A. calamus (30.2%). The individual EO exhibits variable scavenging activities against ABTS and DPPH radicals. These effects were enhanced through the mixture of the three EOs. The optimal antioxidant formulation consisted of 20% C. flexuosus , 53% C. carvi , and 27% A. calamus for DPPHIC50. Whereas 17% C. flexuosus , 43% C. carvi , and 40% A. calamus is the best combination leading to the highest scavenging activity against ABTS radical. These findings suggest a new research avenue for EOs combinations to be developed as novel natural formulations useful in food and biopharmaceutical products.

Currently, statistical experimental design is employed as a quality control method to produce excellent products at the lowest possible cost in food processing, speeding up the process of developing new foods, cutting down costs associated with research, easing the process of moving food products from the research and development stage to the manufacturing stage, and troubleshooting manufacturing issues. In the extraction of bioactive compounds from food, the optimization procedure becomes more straightforward as the optimum conditions of the numerous evaluated responses converge to a similar section. However, the problem becomes more complicated when the optimum values for each response go further apart, making it harder to discover settings that satisfy all of them simultaneously. Using a mathematical function, multiple responses can be integrated into a single one in another manner. The generated response surface enables the calculation of optimum values for extraction parameter, which fulfills all responses whenever possible. Hence, this article reviewed multiple responses, desirability function, and graphical optimization solutions employed to extract food bioactive compounds in the last decade. These techniques’ benefits, drawbacks, potentials, and applications were discussed, including some of their uses in the extraction of bioactive compounds. This will help to address the actual mathematical and statistical issues that arise during the multiple response extraction of food bioactive compounds. Graphical Abstract

Fused deposition modeling (FDM) is the most economical additive manufacturing (AM) technology available for fabricating complex part geometries. However, the involvement of numerous control process parameters and dimensional instabilities are challenges of FDM. Therefore, this study investigated the effect of 3D printing parameters on dimensional deviations, including the length, width, height, and angle of polylactic acid (PLA) printed parts. The selected printing parameters include layer height, number of perimeters, infill density, infill angle, print speed, nozzle temperature, bed temperature, and print orientation. Three-level definitive screening design (DSD) was used to plan experimental runs. The results revealed that infill density is the most consequential parameter for length and width deviation, while layer height is significant for angle and height deviation. The regression models developed for the four responses are non-linear quadratic. The optimal results are obtained considering the integrated approach of desirability and weighted aggregated sum product assessment (WASPAS). The optimal results include a layer height of 0.1 mm, a total of six perimeters, an infill density of 20%, a fill angle of 90°, a print speed of 70 mm/s, a nozzle temperature of 220 °C, a bed temperature of 70 °C, and a print orientation of 90°. The current study provides a guideline to fabricate assistive devices, such as hand and foot orthoses, that require high dimensional accuracies.