Product Optimization Research Articles

Formulation and Optimization of Metronidazole and Lactobacillus spp. Layered Suppositories via a Three-Variable, Five-Level Central Composite Design for the Management of Bacterial Vaginosis.

Bacterial vaginosis, a polymicrobial clinical syndrome characterized by a shift in healthy vaginal microbiota due to bacterial colonization, is characterized by high recurrence rates after conventional treatment with an antimicrobial agent. This has necessitated the need to develop a formulation that has the potential to ensure Lactobacilli viability and bacterial clearance. This study seeks to develop and optimize a layered suppository using a five-level central composite design to ensure optimized metronidazole release and lactic acid viability. Layered suppositories were formulated using the fusion method using polyethylene glycol blend 1500/4000 and Ovucire® as suppository bases. Lactobacillus fermentum was incorporated in the molten mass before molding the solid body suppositories into the cavity of hollow-type suppositories and sealing the molten excipients. Artificial neural network model predictions for product optimization showed high predictive capacity, closely resembling experimental observations. The highest disintegration time recorded was 12.76 ± 0.37 min, with the optimized formulations showing lower times of 5.93 ± 0.98 min and an average weight of 1.17 ± 0.07 g. Histopathological observations determined high compatibility of suppositories with vaginal cells with no distortion or wearing of the vagina epithelium. This optimized formulation provides a safe and promising alternative to conventional suppositories in the treatment and prevention of the recurrence of bacterial vaginosis.

Influence of phosphorus-based flame retardants on polypropylene insulation for high-voltage power cable applications

For high voltage (HV) power cable applications, various studies have been performed to improve the mechanical and electrical properties of polypropylene (PP)-based insulation materials to replace crosslinked polyethylene. However, studies on the effect of additives to yield additional PP properties are still lacking. Herein, we prepared PP blends by melt-mixing widely used commercial flame retardants for PP with isotactic PP (iPP) and investigated their electrical breakdown, flame retardancy behaviors, and UV stability. Among the five kinds of flame retardants employed, aluminum hypophosphite (AHP), aluminum diethyl phosphinate, melamine pyrophosphate, ammonium polyphosphate (APP), and APP treated with silane, AHP was very effective in minimizing the decrease of the direct current breakdown strength of iPP at both 25 °C and 110 °C in the range of 5–20 phr. Particularly, only AHP afforded V-2 grade flame retardancy to iPP, and the flame retardancy was maintained even when the content was reduced to 3 phr. Furthermore, upon exposure to ultraviolet (UV) rays for 5 d, the tensile strength of pristine iPP decreased by approximately 44%, while that of a blend with 3 phr AHP decreased by only 10%. The study results will contribute to the optimization of power cable products through the use of appropriate flame retardants in the design of high-performance PP-based HV insulation materials.

Consumer Demand Behavior Mining and Product Recommendation Based on Online Product Review Mining and Fuzzy Sets

Consumer demand is the need for product characteristics expressed in their own words, which is the basis for producers to develop product recommendations. The extraction and analysis of consumer demands is the most critical input information in quality function deployment (QFD), which has a significant impact on the final prioritization of product technical features, product optimization, and subsequent configuration decisions in QFD, and is directly related to the success of product development. However, the traditional QFD approach to demand analysis lacks reliability and feasibility, and its application often requires time and labor costs that exceed the company’s actual capabilities. Therefore, this paper uses online reviews as the data source and constructs a latent Dirichlet allocation (LDA) topic model based on fuzzy sets to explore the consumer demand information reflected in user reviews. We also introduce the concept of word vector to improve the LDA topic model and compare it with the traditional topic model to verify the performance of the model, so as to explore the consumer demand behavior more accurately and efficiently.

Research on the Optimization of Fresh Agricultural Products Trade Distribution Path Based on Genetic Algorithm

This study, taking the R fresh agricultural products distribution center (R-FAPDC) as an example, constructs a multi-objective optimization model of a logistics distribution path with time window constraints, and uses a genetic algorithm to optimize the optimal trade distribution path of fresh agricultural products. By combining the genetic algorithm with the actual case to explore, this study aims to solve enterprises’ narrow distribution paths and promote the model’s application in similar enterprises with similar characteristics. The results reveal that: (1) The trade distribution path scheme optimized by the genetic algorithm can reduce the distribution cost of distribution centers and improve customer satisfaction. (2) The genetic algorithm can bring economic benefits and reduce transportation losses in trade for trade distribution centers with the same spatial and quality characteristics as R fresh agricultural products distribution centers. According to our study, fresh agricultural products distribution enterprises should emphasize the use of genetic algorithms in planning distribution paths, develop a highly adaptable planning system of trade distribution routes, strengthen organizational and operational management, and establish a standard system for high-quality logistics services to improve distribution efficiency and customer satisfaction.

Finely regulating methanol concentration to control the alkylation depth in methanol aromatization for optimizing product distribution

Uncontrollable alkylation in methanol to aromatics severely restricts the light aromatic selectivity and catalytic stability. Herein, we proposed a new strategy to control the alkylation depth by precisely regulating methanol concentration in alkylation environment. Firstly, the high Si/Al ratio ZSM-5 (HZ) was packed over Zn doped low Si/Al ratio ZSM-5 (Zn/LZ) to form dual bed to inhibit deep alkylation for high catalytic stability and BTX selectivity. Secondly, part of methanol was introduced into lower Zn/LZ bed to promote methyl-cyclopentene alkylation for aromatic production and product optimization. After such regulation, toluene selectivity in aromatics decreased from 27.9% to 20.8% accompanied by an increase in xylene selectivity from 37.1% to 44.0%. BTX selectivity in aromatics also improved to 66.7% with 97.5 h of catalyst lifetime, much higher than 50.0% and 20 h of the single Zn/LZ bed. This work realized stable light aromatic production from methanol by controlling the microscopic reaction routes.

A New Extension of the Cubic Bézier Curve

An extended cubic Bézier curve is constructed, which can realize <italic>FC</italic>³ continuity under the condition of <italic>C</italic>² continuity, and ensure that the shape of both single-segment curve and composite curve can be freely adjusted without changing the control points. For this reason, a new curve with the same structure as the cubic Bézier curve is constructed. Firstly, the preliminary expression of the blending function is given, including undetermined coefficients. Then, according to the preset properties of the curves during joining, the endpoint properties of the blending function are deduced in reverse, so as to establish the equations that the undetermined coefficients in the blending function should satisfy. By solving the equations, a set of quintic polynomial blending functions with four parameters is obtained, which can be reduced to quartic when special parameters are taken. At last, a new curve with four shape parameters determined by four control points is defined by linear combination of the blending function and the control points. It has the basic properties of Bézier curve, such as convex hull property, geometric invariance and affine invariance. Thanks to the introduction of multiple shape parameters, curves of different shapes can be defined by the same control polygon, and the change of each shape parameter will drive the points on the curve to move linearly along a fixed direction. When constructing composite curve, the <italic>FC</italic>³ continuity conditions between adjacent curve segments are the same as the <italic>C</italic>² continuity conditions, and the shape of composite curve can be adjusted freely on the premise of maintaining continuity, control points and parameter segmentation unchanged. The new method can expand the processing ability of CAD system to industrial products, improve the speed of product design, modification and optimization, and save the investment of manpower and material resources in design.

A study on the effect of user experience of fitness APP on product trust and purchase intention

Purpose - The purpose of this study is to take fitness APP users as the research object from the perspective of user experience to explore the influence of fitness APP user experience factors on product trust and purchase intention. Design/methodology/approach - The study collected data on 275 customers who had experience buying and using fitness apps. To test the hypothesis, SPSS 27.0 and AMOS 26.0 statistical packages were used based on the collected data. Findings - The results showed that the user experience factors (usefulness, ease to use, enjoyment, interaction) of fitness APP and the relationship between product trust had a positive effect, and product trust had a positive effect on purchase intention. In addition, exercise experience, showed a moderating effect in the relationship between the usefulness, easy to use of user experience and product trust. Research implications or Originality - This study provided research model among user experience factors of fitness APP, product trust and purchase intention. This study can help sports and fitness companies with product optimization and marketing decisions.

Optimization of a green tea beverage enriched with honey and bee pollen

Green tea (Camellia sinensis) has common production in many countries. This plant species has polyphenols with natural antioxidant properties which are very beneficial for human health. The aim of the study was to develop a product made with green tea, honey, and pollen, in order to increase the quantity of health benefit components. The ratio of honey to pollen and percentage of non-tea substances constitute 2 factors of design. The results were compared with untreated green tea after sensory analysis. The total phenolics content, antioxidant capacity, ascorbic acid determination, and sugar analysis were carried out. Optimization of the final product was carried out by considering the highest total phenolics content, total antioxidant, and sensory evaluation as overall acceptability. The optimum conditions were 4:1 honey to pollen ratio and 6% total concentration of non-tea substances with total phenolics content of 578.674 mg gallic acid equivalent/L and total antioxidant capacity of 94.463.

Optimization of sharia bank products for micro, small and medium enterprises (MSMEs) in Indonesia during COVID-19

This study aims to show that the empowerment of MSMEs by Islamic banks is the key to the revival of the national economy after the COVID-19 pandemic. The reality of Micro, Small and Medium Enterprises (MSMEs) in Indonesia actually has two implications for shari'a banks. MSMEs are both an opportunity and a challenge. On the one hand, the dominant number of MSMEs is a very promising and potential market share for shari'a banks that want to expand market share and make profits at the same time. That way, the failure of shari'a banks to pursue a 10% market share in 2020 due to the pandemic can be achieved in 2022. On the other hand, because MSMEs are high-risk and lack the requirements to be financed due to all of their faults and restrictions, sharia banks are faced with the challenging task of financing them. The profit that can be expected from MSMEs is not proportional to the risk taken. The results of the study concluded that through product engineering methods, Islamic banks as ummat financial institutions are able to optimize their products for micro, small and medium enterprises (MSMEs).

Metabolic profiles alteration of Southern Thailand traditional sweet pickled mango during the production process.

Sweet pickled mango named Ma-Muang Bao Chae-Im (MBC), a delicacy from the Southern part of Thailand, has a unique aroma and taste. The employed immersion processes (brining 1, brining 2, and immersion in a hypertonic sugar solution, sequentially) in the MBC production process bring changes to the unripe mango, which indicate the occurrence of metabolic profiles alteration during the production process. This occurrence was never been explored. Thus, this study investigated metabolic profile alteration during the MBC production process. The untargeted metabolomics profiling method was used to reveal the changes in volatile and non-volatile metabolites. Headspace solid-phase micro-extraction tandem with gas chromatography quadrupole time of flight (GC/QTOF) was employed for the volatile analysis, while metabolites derivatization for non-volatile analysis. In conclusion, a total of 82 volatile and 41 non-volatile metabolites were identified during the production process. Terpenes, terpenoids, several non-volatile organic acids, and sugars were the major mango metabolites that presented throughout the process. Gamma-aminobutyric acid (GABA) was only observed during the brining processes, which suggested the microorganism’s stress response mechanism to an acidic environment and high chloride ions in brine. Esters and alcohols were abundant during the last immersion process, which had an important role in MBC flavor characteristics. The knowledge of metabolites development during the MBC production process would be beneficial for product development and optimization.

Product Optimization and Antimicrobial Efficiency of Starch-Based Active Packaging Film Prepared Using Amira (Plumbago Zeylanica) Root Extract

This study aimed to develop food packaging from cornstarch combined with methanol extract of Plumbago zeylanica root as antimicrobial agents. The antimicrobial activity of the extract was tested against three bacterial strains, namely, Staphylococcus aureus, Salmonella typhi, and Escherichia coli and one fungal strain called Aspergilla niger. Microorganism growth inhibition was examined by employing a zone of inhibition check on solid media. Two hundred microliters of assorted concentrations (200 mg/ml, 100 mg/ml, 50 mg/ml, and 25 mg/ml) of plant extracts were added into an eight-millimeter hole diameter employing a micropipette. Hence, 200 µl of 200 mg/ml extract inhibited 13.5, 8.75, 10.5, and 27 mm diameter for S. typhi, E. coli, S. aureus, and A. niger, respectively. The minimum inhibitory concentrations 1.25 mg/ml, 2.5 mg/ml, 1.25 mg/ml, and 0.625 mg/ml of crude extract utterly suppressed the growth of S. aureus, E. coli, S. typhi, and A. niger, respectively. Later on, the antimicrobial agent films and the control media were prepared by the casting method. The prepared antimicrobial packaging films exhibited inhibitory zones (a wide clear zone on solid media) for S. typhi and A. niger growth inhibition; however, inhibitions for E. coli and S. aureus were not effective. Antimicrobial activity decreased while decreasing the solubility of the film and antimicrobial concentration with increasing cornstarch content in the solution. The tensile strength of the films increased with increasing antimicrobial content in the solution. Higher antimicrobial inhibition activity was found at a 1.5 glycerol/starch ratio, 1.5 gram content of P. zeylanica, and 0.5 mm film thickness. Generally, the plasticized cornstarch antimicrobial packaging film combined with P. zeylanica extract had a significant effect on the growth of each selected microorganism and the physical properties of the material ( P &lt; 0.05). A preprint of this research has previously been uploaded to the Addis Ababa University database (Yirdaw et al. 2018). In this section, only the summary and updated content of the research findings are presented.

Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry: A Strategy for Optimization, Characterization, and Quantification of Antioxidant Nitro Derivatives.

As an antioxidant, N-phenyl-β-naphthylamine (PBNA) inhibits the activity of oxidants, such as NOx, to prevent the degradation of energetic materials. In the presence of NOx, nitrated products can be generated in the process potentially. To characterize nitrated PBNA in a nontargeted analysis of complex samples as such, liquid chromatography tandem quadrupole time-of-flight (LC-QTOF), as an excellent analytic technique, is used due to its high resolution and sensitivity. However, a systematic approach of instrumentation optimization, data interpretation, and quantitative determination of products is needed. Through a step-by-step evaluation of the instrumental parameters used in the Q0, Q1, and Q2 compartments of LC-QTOF, optimal ion yields of precursor ions and high-resolution MS2 fragmentation spectra at low mass defects were obtained in both negative and positive electrospray ionization modes. Through rationalization of the fragmentation pathways and verification using theoretical masses, the mononitro derivative of PBNA was accurately identified as N-(4-nitrophenyl)-naphthalen-2-amine and further confirmed using a reference standard. Using strict criteria provided by the analytical guidelines (e.g., SANTE), limit of quantitation, limit of detection, and calibration were established for the quantitation of PBNA and nitrated PBNA. From optimization to characterization and subsequent quantification of the mononitro-PBNA derivative, for the first time, the applicability of this strategy is demonstrated in the aged energetic binders.

In situ carbon dioxide capture to co-produce 1,3-propanediol, biohydrogen and micro-nano calcium carbonate from crude glycerol by Clostridium butyricum

BackgroundClimate change caused by greenhouse gas emission has become a global hot topic. Although biotechnology is considered as an environmentally friendly method to produce chemicals, almost all biochemicals face carbon dioxide emission from inevitable respiration and energy metabolism of most microorganisms. To cater for the broad prospect of biochemicals, bioprocess optimization of diverse valuable products is becoming increasingly important for environmental sustainability and cleaner production. Based on Ca(OH)2 as a CO2 capture agent and pH regulator, a bioprocess was proposed for co-production of 1,3-propanediol (1,3-PDO), biohydrogen and micro-nano CaCO3 by Clostridium butyricum DL07.ResultsIn fed-batch fermentation, the maximum concentration of 1,3-PDO reached up to 88.6 g/L with an overall productivity of 5.54 g/L/h. This productivity is 31.9% higher than the highest value previously reports (4.20 g/L/h). In addition, the ratio of H2 to CO2 in exhaust gas showed a remarkable 152-fold increase in the 5 M Ca(OH)2 group compared to 5 M NaOH as the CO2 capture agent. Green hydrogen in exhaust gas ranged between 17.2% and 20.2%, with the remainder being N2 with negligible CO2 emissions. During CO2 capture in situ, micro-nano calcite particles of CaCO3 with sizes in the range of 300 nm to 20 µm were formed simultaneously. Moreover, when compared with 5M NaOH group, the concentrations of soluble salts and proteins in the fermentation broth of 5 M Ca(OH)2 group were notably reduced by 53.6% and 44.1%, respectively. The remarkable reduction of soluble salts and proteins would contribute to the separation of 1,3-PDO.ConclusionsCa(OH)2 was used as a CO2 capture agent and pH regulator in this study to promote the production of 1,3-PDO. Meanwhile, micro-nano CaCO3 and green H2 were co-produced. In addition, the soluble salts and proteins in the fermentation broth were significantly reduced.Graphical

Assessing hybrid heat pump performance in simulated field-trial using hardware in the loop

Low-carbon heat generators such as (hybrid) heat pumps are very sensitive to operating conditions. Insight into the real-world performance of such systems is essential for stakeholders in order to make informed decisions regarding product design, commissioning systems and predicting energy use. In this research an emulator facility was developed which allows the testing of physical water-based heating generators in a simulated environment whereby a climate chamber simulates outdoor temperature and humidity and a ’heat rejection rig’ couples the tested equipment hydronics to the virtual heat emitter system. The equipment is tested against a fully dynamic house and heating system model. As demonstration case studies for the facility, two hybrid heat pumps have been tested with models of a typical 1970s terraced Dutch house. Weather conditions were based on six representative heating season days. Relevant performance indicators for these tests are gas and electricity consumption, heat pump COP and how these vary across the range of reference days. The results suggest the product control strategy and installer settings have a significant effect on performance indicators. Space heating gas use can be reduced by >60% in some cases while maintaining reasonable heat pump COP. The results highlight the potential to improve product controls and provide guidance for how hybrids should be configured, and hence the facility’s value in product optimisation and knowledge generation.

Design Optimization of Complex Products Based on CAD Multi-Objective Genetic Algorithm

Computer-Aided Design and Applications is an international journal on the applications of CAD and CAM. It publishes papers in the general domain of CAD plus in emerging fields like bio-CAD, nano-CAD, soft-CAD, garment-CAD, PLM, PDM, CAD data mining, CAD and the internet, CAD education, genetic algorithms and CAD engines. The journal is aimed at all developers and users of CAD technology to ptovide CAD solutions for various stages of design and manufacturing. The journal publishes all about Computer-Aided Design and Computer-Aided technologies.

Desirability-based optimization of bakery products containing pea, hemp and insect flours using mixture design methodology

Simplex lattice design was used to design 15 sponge cakes formulations combining pea (PP), hemp (HP) and insect (IP) flours representing 15% of dough composition. Moisture, protein content, baking loss, specific volume, texture and cost of the 15 samples plus the control (0% added protein) were analysed. Results showed that the effect of PP, HP and IP on cake properties could be modelled with linear regressions (96.80% < R2 < 99.96%). Ternary diagrams showed the effect of the combination of the three proteins in each response. The desirability function was used to obtain a multi-response optimization of the samples with maximum protein, maximum specific volume and minimum incremental cost. Sensory results of the 5 optimised samples showed that by combining 3.75% pea, 3.75% hemp and 7.5% insect it was possible to obtain a dairy- and egg-free sponge cake without significant differences from the control with animal-derived proteins.

Holistic Approach for Artificial Intelligence Implementation in Pharmaceutical Products Lifecycle: A Meta-Analysis

Recent developments in Digital Medicine approaches concern pharmaceutical product optimization. Artificial Intelligence (AI) has multiple applications for pharmaceutical products’ lifecycle, increasing development speed, quality of the products, and efficiency of the therapy. Here, we systematically review the overall approach for AI implementation in pharmaceutical products’ lifecycle. The published studies in PubMed and IEEE Xplore were searched from inception to March 2022. The papers were screened for relevant outcomes, publication types, and data sufficiency, and a total of 73 (1.2%) out of 6131 studies were retrieved after the selection. We extracted the data according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. All Artificial Intelligence systems could be divided into multiple overlapping categories by implementation. For the 177 projects found, the most popular areas of AI implementation are clinical trials and pre-clinical tests (34%). In second place are novel small molecule design systems, with 33% of the total. The third most popular scope for AI implementation is target identification for novel medicines. More than 25% of the systems provide this functionality. It is interesting that most of the systems specialize in only one area (102 systems—57%). None of the systems provide functionality for full coverage of the lifecycle and function in all categories of the tasks. This meta-analysis demonstrated that Artificial Intelligence solutions in pharmaceutical products’ lifecycle could find numerous implementations, and none of the available market solutions covers them all.

Synthesis and biological activity of waltherione F‐derived diamide derivatives containing 4‐quinolone group

AbstractThe exploitation of new fungicides and the discovery of action targets are effective ways to solve the problem of resistance, and structural optimization of natural products has become an resultful method to discover lead compounds. In this work, in conjunction with the structures of the fungicidal lead compounds h‐I‐9, X‐I‐3, and X‐II‐5 found in our previous project, waltherione F‐derived diamide compounds were synthesized and characterized by 1H NMR, 13C NMR, and HRMS. The biological assays suggested that the target compounds exhibited weak to good fungicidal activity against the tested pathogens, while most of the target compounds displayed high cellular cytotoxicity against Hela cells. The investigation of accidentally discovered fluorescence characteristics revealed that the compound I‐1 exhibited the most vigorous fluorescence intensity at 350 nm, which was significantly higher than that of I‐3 at 225 nm and was further elucidated by density functional theory (DFT) calculations. Overall, the above results would provide theoretical guidance for the design of active target molecules and the development of fluorescent probes.

The Current Situation and Trend of Blockchain Technology in the Financial Field

In the Internet era, with the development and application of information technology, the financial environment is becoming more and more complex, and traditional financial business products and service models are gradually unable to meet people’s daily needs. In response to this problem, it is important to iteratively upgrade the traditional business products by rationally applying the existing information technology in the entire financial market and realize the adjustment of the organizational structure of financial institutions and the optimization of products and services. With the development of network technology, the research on the application of blockchain technology in the financial field is gradually carried out, and its advantages and characteristics are of great significance to the optimization and upgrading of the traditional financial system. The purpose of this paper is to analyze the research status and trends of blockchain technology in the financial field. Through CiteSpace to analyze all relevant researches on blockchain technology in the financial field, we can grasp the research status and trends of blockchain technology in the financial field as a whole, coping with financial issues in the new environment. This article explains the basic theory of blockchain technology and conducts an overall visual analysis of related research on blockchain technology in the financial field based on CiteSpace. The results showed that the research keywords of blockchain technology in the financial field at home and abroad are concentrated in “supply chain finance,” and China’s research on this keyword accounts for 59.5%. Foreign research on this keyword accounts for 26.5%. The difference is 33%, and the overall popularity is on the rise.

Data Analysis of Amazon Product Based on LSTM and GPR

&lt;p&gt;In this paper, we propose a method that combines models such as GPR with PSO optimization to predict the time series data. We use LSTM and TOPSIS with entropy weight method modification to process vari-ous types of data from various aspects, taking into account both tabular and textual data, and to mine valuable contents from them. Based on shopping data, we analyze the historical situation and predict the future sales of products. So that we can recommend the most suitable products for customers. At the same time, for merchants, this paper provides directions for product optimization and improvement of advertising and marketing strategies.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;