Design Of Experiments Framework Research Articles

Design Optimization of a Novel Catalytic Approach for Transglucosylated Isomaltooligosaccharides into Dietary Polyols Structures by Leuconostoc mesenteroides Dextransucrase.

Polyols, or sugar alcohols, are widely used in the industry as sweeteners and food formulation ingredients, aiming to combat the incidence of diet-related Non-Communicable Diseases. Given the attractive use of Generally Regarded As Safe (GRAS) enzymes in both academia and industry, this study reports on an optimized process to achieve polyols transglucosylation using a dextransucrase enzyme derived from Leuconostoc mesenteroides. These enzyme modifications could lead to the creation of a new generation of glucosylated polyols with isomalto-oligosaccharides (IMOS) structures, potentially offering added functionalities such as prebiotic effects. These reactions were guided by a design of experiment framework, aimed at maximizing the yields of potential new sweeteners. Under the optimized conditions, dextransucrase first cleared the glycosidic bond of sucrose, releasing fructose with the formation of an enzyme-glucosyl covalent intermediate complex. Then, the acceptor substrate (i.e., polyols) is bound to the enzyme-glucosyl intermediate, resulting in the transfer of glucosyl unit to the tested polyols. Structural insights into the reaction products were obtained through nuclear maneic resonance (NMR) and matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) analyses, which revealed the presence of linear α(1 → 6) glycosidic linkages attached to the polyols, yielding oligosaccharide structures containing from 4 to 10 glucose residues. These new polyols-based oligosaccharides hold promise as innovative prebiotic sweeteners, potentially offering valuable health benefits.

Plant-Derived, Nodule-Specific Cysteine-Rich Peptides as a Novel Source of Biopesticides for Controlling Citrus Greening Disease.

Nodule-specific cysteine-rich (NCR) peptides, encoded in the genome of the Mediterranean legume Medicago truncatula (barrelclover), are known to regulate plant-microbe interactions. A subset of computationally derived 20-mer peptide fragments from 182 NCR peptides was synthesized to identify those with activity against the unculturable vascular pathogen associated with citrus greening disease, 'Candidatus Liberibacter asiaticus' (CLas). Grounded in a design of experiments framework, we evaluated the peptides in a screening pipeline involving three distinct assays: a bacterial culture assay with Liberibacter crescens, a CLas-infected excised citrus leaf assay, and an assay to evaluate effects on bacterial acquisition by the nymphal stage of hemipteran vector Diaphorina citri. A subset of the 20-mer NCR peptide fragments inhibits both CLas growth in citrus leaves and CLas acquisition by D. citri. Two peptides induced higher levels of D. citri mortality. These findings reveal 20-mer NCR peptides as a new class of plant-derived biopesticide molecules to control citrus greening disease.

Improving an rRNA depletion protocol with statistical design of experiments

<h2>Abstract</h2> In prokaryotic RNA-seq library preparation, rRNA depletion is required to remove highly abundant rRNA transcripts from total RNA. rRNA is so abundant that small improvements in depletion efficiency lead to large increases in mRNA sequencing coverage. The current gold-standard method for rRNA depletion makes rRNA depletion the most expensive step in prokaryotic RNA-seq library preparation. A variety of commercial and home-made methods exist to lower the cost or increase the efficiency of rRNA removal. Many of these techniques are suboptimal when applied to new species of bacteria or when the protocol or reagents need to be changed. Re-optimizing a protocol by trial-and-error is an expensive and laborious process. Systematic frameworks like the statistical design of experiments (DOE) can efficiently improve processes by exploring the quantitative relationship between multiple factors. DOE allows experimenters to find factor interactions that may not be apparent when factors are studied in isolation. We used DOE to optimize an rRNA depletion protocol by updating reagents and identifying factors that maximize rRNA removal and minimize cost. The optimized protocol more efficiently removes rRNA, uses fewer reagents, and is less expensive than the original protocol. Our optimization required only 36 experiments and identified two significant interactions among three protocol factors. Overall, our approach demonstrates the utility of a rational, DOE framework for improving complex molecular biology protocols.

Component blending for bitumen production for Indian refineries

This investigation pertains to the bitumen production using component blending. During the manufacture of blended bitumen, the proportion of the constituents, the temperature during blending, and the duration of blending are selected to meet the penetration at 25°C and the absolute viscosity at 60°C as per the Indian specifications. The choices of the blend parameters become challenging when the constituents from multiple crudes are blended to produce different paving grades. Two constituent and three constituent blends for four different grades of bitumen were prepared in a laboratory blending facility from four different crude sources. A design of experiments framework was used to develop prediction models for penetration and viscosity. Simulations were carried out to suggest blending schemes to manufacture all the viscosity grades from different crude sources. Correspondence between the viscosity grade and high-temperature performance grade was observed for blend parameters for the crude sources investigated in this study.

Aggregate planning with Flexibility Requirements Profile

Demand uncertainty can cause frequent changes in production plans, which create nervousness in manufacturing companies. Traditional methods used for stabilizing production plans do not provide the adequate flexibility in production plans to handle the random demand. Flexibility Requirements Profile (FRP) is an alternative stabilizing approach, where flexible bounds are enforced on production plans in order to maintain a desired degree of flexibility. In this study, we incorporate FRP into conventional aggregate planning, which is formulated as a mixed-integer linear program with additional constraints to reflect the FRP requirements. To ascertain the effectiveness of the proposed method, several structural results are presented along with a comprehensive numerical study using a design of experiments framework with examples from automotive and textile industries. Based on production costs and production plan stability, the effectiveness of FRP-based aggregate planning is compared to traditional aggregate planning without FRP as well as to FRP planning without optimization. The results show that aggregate planning with FRP can consistently identify more stable production plans without significantly sacrificing the cost objective.

Double Dutch: A Tool for Designing Combinatorial Libraries of Biological Systems.

Recently, semirational approaches that rely on combinatorial assembly of characterized DNA components have been used to engineer biosynthetic pathways. In practice, however, it is not practical to assemble and test millions of pathway variants in order to elucidate how different DNA components affect the behavior of a pathway. To address this challenge, we apply a rigorous mathematical approach known as design of experiments (DOE) that can be used to construct empirical models of system behavior without testing all variants. To support this approach, we have developed a tool named Double Dutch, which uses a formal grammar and heuristic algorithms to automate the process of DOE library design. Compared to designing by hand, Double Dutch enables users to more efficiently and scalably design libraries of pathway variants that can be used in a DOE framework and uniquely provides a means to flexibly balance design considerations of statistical analysis, construction cost, and risk of homologous recombination, thereby demonstrating the utility of automating decision making when faced with complex design trade-offs.

On Optimization of Surface Roughness of Selective Laser Melted Stainless Steel Parts: A Statistical Study

In this work, the effects of re-melting parameters for postprocessing the surface texture of Additively Manufactured parts using a statistical approach are investigated. This paper focuses on improving the final surface texture of stainless steel (316L) parts, built using a Renishaw SLM 125 machine. This machine employs a fiber laser to fuse fine powder on a layer-by-layer basis to generate three-dimensional parts. The samples were produced using varying angles of inclination in order to generate range of surface roughness between 8 and 20 µm. Laser re-melting (LR) as post-processing was performed in order to investigate surface roughness through optimization of parameters. The re-melting process was carried out using a custom-made hybrid laser re-cladding machine, which uses a 200 W fiber laser. Optimized processing parameters were based on statistical analysis within a Design of Experiment framework, from which a model was then constructed. The results indicate that the best obtainable final surface roughness is about 1.4 µm ± 10%. This figure was obtained when laser power of about 180 W was used, to give energy density between 2200 and 2700 J/cm2 for the re-melting process. Overall, the obtained results indicate LR as a post-build process has the capacity to improve surface finishing of SLM components up to 80%, compared with the initial manufactured surface.

Effect of resistance spot welding parameters on weld pool properties in a DP600 dual-phase steel: A parametric study using thermomechanically-coupled finite element analysis

The objective of this research is to quantify the effects of resistance spot welding (RSW) parameters on different weld properties of a dual-phase steel. A finite element based model was used which accounted for the following required physical interactions: the interaction between (1) the electro-kinetics and heat transfer via the Joule effect, (2) the heat transfer and phase transformations through latent heat, and (3) the heat transfer, electro-kinetics, and mechanical behavior via the contact conditions. The effects of the RSW parameters on weld properties were investigated within a design of experiments framework by altering (1) the electrical current intensity, (2) the welding time, (3) the sheet thickness, (3) the electrode face radius, and (5) the squeeze force at multiple levels. The simulation results were analyzed using the analysis of variance (ANOVA) technique to show the effects of these parameters and their potential interactions, along with their significance. The current intensity was the most influential factor and resulted in an increased size of molten zone and the heat affected zone. The sheet thickness and welding time also showed significant contributions in changing the weld properties. The effects of the other parameters were less significant. The importance of this study is that finding the optimal process window for RSW parameters can help to engineer the desired weld properties.

Design of Experiment Framework Based on Warship Equipment Maintenance Support Simulation Experiment and Exploratory Analysis

The warship equipment maintenance support system is a complex system, which has uncertainty. Aimed at uncertain support scheme, the equipment maintenance support simulation experiment (EMSSE) is a method based on exploratory analysis (EA) and simulation. According to the characters of EA and the demand of EMSSE planning, an experiment framework (EF) based on EMSSE was put forward a experiment framework (EF) which makes the problem solved more flexibly because of being independent of the simulation model,, and the content was analyzed in detail. Finally, an example of warship maintenance support is introduced to explain application of EF and validate it feasible.

The impact of ENSO and macrocirculation patterns on precipitation under climate change

The possible impact of El Nino-Southern Oscillation (ENSO) and macrocirculation patterns (CPs) on local precipitation are examined and analyzed here under climate change conditions. First the relationship between the input and output variables under present conditions is established using two models, a fuzzy rule-based model (FRBM) and a multivariate linear regression model (MLRM), then this historical relationship is extended under climate change conditions. The input variables for these models consist of lagged ENSO-data (represented by the Southern Oscillation Index, SOI) and 500 hPa height data clustered into macrocirculation patterns over the western United States, while the output is an estimate of monthly local precipitation at selected Arizona stations. To overcome the lack of SOI data under climate change, several scenarios are constructed by perturbing the historical SOI data in a design of experiments framework. The results of the experimental design show that, in general, the precipitation amount seems to decrease under climate change. While the stations and months have differences, as expected, the perturbed scenarios do not show significant differences.

Optimizing liquefied natural gas terminal design for effective supply-chain operations

Liquefied natural gas (LNG) supply-chain management has become more critical due to the increased gas demand and the need for imported LNG. One of the major issues is the design of LNG terminals for efficient gas flow. This paper provides a framework for analyzing the key design parameters for LNG terminals that impact profitability. Design considerations such as storage capacity, vessel docking capacity and throughput are taken into account and connected to the LNG sourcing using a mixed integer programming model. An application is provided for the Cove Point LNG Terminal in Maryland using a design of experiments framework.

Experimentation on the Residual Stresses Generated by Endmilling

Residual stress measurements from endmilling of annealed AISI 4340 have been made at multiple points within the cut geometry to investigate the effects of location on the machining-induced residual stresses from endmilling. In the same experiments the effects of axial depth of cut and feed on the residual stresses induced in the machined surface have been investigated in a design of experiments framework. The experimentation demonstrates that location, feed and axial depth of cut have strong influences on the machining-induced residual stresses from end-milling when expressed in a workpiece coordinate frame. In addition, expression of the residual stresses in a coordinate frame fixed in the tool demonstrates a simplification in the residual stresses from endmilling in that the stresses at multiple locations within the cut geometry show strong similarities when expressed in this coordinate frame.