In silico cell factory design driven by comprehensive genome‑scale metabolic models:development and challenges

Genome-scale metabolic models(GEMs)have been widely used to design cell factories in silico.However,initial flux balance analysis only considers stoichiometry and reaction direction constraints,so it cannot accurately describe the distribution of metabolic flux under the control of various regulatory mechanisms.In the recent years,by introducing enzymology,thermodynamics,and other multiomics-based constraints into GEMs,the metabolic state of cells under different conditions was more accurately simulated and a series of algorithms have been presented for microbial phenotypic analysis.Herein,the development of multiconstrained GEMs was reviewed by taking the constraints of enzyme kinetics,thermodynamics,and transcriptional regulatory mechanisms as examples.This review focused on introducing and summarizing GEMs application tools and cases in cell factory design.The challenges and prospects of GEMs development were also discussed.

From Factory Floor to Design Headquarters

AN iPhone made by a Chinese OEM (original equipment manufacturer) sells for US$499 in the US market, while the commissioned Chinese manufacturer of the phone gets a recompense of only US $4.

Factorial Experimental Design to Study the Effects of Layers and Fiber Content on Concrete Flexural Behavior

Experimentation has come a long in helping researchers achieve breakthroughs in their different scientific areas and engineering happens to be one of those areas with the most impact from experimental advancement. The need for valid experimental results free from biases and confounding conclusions has prompted the development of new experimental techniques that takes consideration of all applicable factor and combinations in providing answers on a research topic, and the Factorial Experimental design credited to Sir Ronald Fisher is one technique yielding highly valid results. This paper uses the factorial design of experiments to research the flexural impact of polyvinyl acetate fiber and layered concrete in construction. The experiment considered two levels of fiber contents and two levels of layers, and prepared samples with all combinations of the variable factors. The samples were tested after 7 days from casting for flexural strength and an advance statistical analysis was performed on the flexural responses of the samples using R-program. The results from the analyses revealed the significance of the variables to the flexural strength of the samples, as well as their interactions. The experiment concluded that based on the number of layers and fiber content used for the experiment, casting concrete in layers does have a significant negative effect on the flexural strength of concrete, and the failure pattern of concrete members under flexural load in evidently influenced by the material composition of the concrete, and that it can be evidently influenced by casting the concrete in layers.

Construction of Split-Plot Designs with General Minimum Lower Order Confounding

Fractional factorial split-plot design has been widely used in many fields due to its advantage of saving experimental cost. The general minimum lower order confounding criterion is usually used as one of the attractive design criterion for selecting fractional factorial split-plot design. In this paper, we are interested in the theoretical construction methods of the optimal fractional factorial split-plot designs under the general minimum lower order confounding criterion. We present the theoretical construction methods of optimal fractional factorial split-plot designs under general minimum lower order confounding criterion under several conditions.

Design and Robust Performance Evaluation of a Fractional Order PID Controller Applied to a DC Motor

This paper proposes a methodology for the quantitative robustness evaluation of PID controllers employed in a DC motor. The robustness analysis is performed employing a 2~3 factorial experimental design for a fractional order proportional integral and derivative controller(FOPID), integer order proportional integral and derivative controller(IOPID)and the Skogestad internal model control controller(SIMC). The factors assumed in experiment are the presence of random noise,external disturbances in the system input and variable load. As output variables, the experimental design employs the system step response and the controller action. Practical implementation of FOPID and IOPID controllers uses the MATLAB stateflow toolbox and a NI data acquisition system. Results of the robustness analysis show that the FOPID controller has a better performance and robust stability against the experiment factors.

CONSTRUCTION OF OPTIMAL BLOCKING SCHEMES FOR ROBUST PARAMETER DESIGNS

Robust parameter design （RPD） is an important issue in experimental designs. If all experimental runs cannot be performed under homogeneous conditions, blocking the units is effective. In this paper, we obtain the correspondence relation between fractional factorial RPDs and the blocking schemes for full factorial RPDs. In addition, we provide a construction of optimal blocking schemes that make all main effects and control-by-noise two-factor interactions estimable.

Optimization of hydrothermal synthesis of H-ZSM-5 zeolite for dehydration of methanol to dimethyl ether using full factorial design

H-ZSM-5 zeolite was synthesized by hydrothermal method. The effects of different synthesis parameters, such as hydrothermal crystallization temperature （170-190 ℃） and Si/A1 molar ratio （100-150）, on the catalytic performance of the dehydration of methanol to dimethyl ether （DME） over the synthesized H-ZSM-5 zeolite were studied. The catalysts were characterized by N2 adsorption-desorption, XRD, NH3-TPD, TGA/DTA, and SEM techniques. The full factorial design of experiments was applied to the synthesis of H-ZSM-5 zeolite and the effects of synthesis conditions and their interaction on the yield of DME as the response variable were determined. Analysis of variance showed that two variables and their interaction significantly affected the response. According to the experimental results, the optimized catalyst prepared at 170℃ with the Si/A1 molar ratio of 100 showed the best catalytic performance among the tested H-ZSM-5 zeolite.

Artificial Neural Network and Full Factorial Design Assisted AT-MRAM on Fe Oxides, Organic Materials, and Fe/Mn Oxides in Surficial Sediments

Artificial neural network（ANN） and full factorial design assisted atrazine（AT） multiple regression adsorption model（AT-MRAM） were developed to analyze the adsorption capability of the main components in the surficial sediments（SSs）. Artificial neural network was used to build a model（the determination coefficient square r2 is 0.9977） to describe the process of atrazine adsorption onto SSs, and then to predict responses of the full factorial design. Based on the results of the full factorial design, the interactions of the main components in SSs on AT adsorption were investigated through the analysis of variance（ANOVA）, F-test and t-test. The adsorption capability of the main components in SSs for AT was calculated via a multiple regression adsorption model（MRAM）. The results show that the greatest contribution to the adsorption of AT on a molar basis was attributed to Fe/Mn（–1.993 μmol/mol）. Organic materials（OMs） and Fe oxides in SSs are the important adsorption sites for AT, and the adsorption capabilities are 1.944 and 0.418 μmol/mol, respectively. The interaction among the non-residual components（Fe, Mn oxides and OMs） in SSs interferes in the adsorption of AT that shouldn’t be neglected, revealing the significant contribution of the interaction among non-residual components to controlling the behavior of AT in aquatic environments.

Methodology of factorial design deriving guidelines for simulation of growth curve and production of sugars by Spirulina (Arthrospira) maxima

It is practical, economic and sometimes essential to derive rules or conclusions by performing lesser runs of experiments. In this part, a methodology based on 2 f factorial design was brought up to derive guidelines to simulate growth curve and production of sugars by Spirulina (Arthrospira) maxima . The growth curve or accumulation process of sugars was idealized by sets of straight lines limited by phase transfers of growth or accumulation of sugars. Normal analyses of the critical values of the transfers were used to derive their linear relationships with the initial conditions of the experimental factors. These linear functions were called guidelines and were used to simulate the growth curve or accumulation of sugars. Generalization of the guideline technique was determined by the kinetic limitation of nutrient nitrogen or sulfur that was dependent upon their stoichiometric deficiency directly derived from their initial values in the medium. This method uses the initial conditions of culture and does not need measurements of concentrations of nitrate, sulfate and pigments during cultivation. It is a practical and useful alternative way to trace and predict approximately the growth curve and production of sugars by S. maxima .

Abrasive resistance of metastable V–Cr–Mn–Ni spheroidal carbide cast irons using the factorial design method

Full factorial design was used to evaluate the two-body abrasive resistance of 3wt%C–4wt%Mn–1.5wt%Ni spheroidal carbide cast irons with varying vanadium（5.0wt%–10.0wt%） and chromium（up to 9.0wt%） contents. The alloys were quenched at 920℃. The regression equation of wear rate as a function of V and Cr contents was proposed. This regression equation shows that the wear rate decreases with increasing V content because of the growth of spheroidal VC carbide amount. Cr influences the overall response in a complex manner both by reducing the wear rate owing to eutectic carbides（M7C3） and by increasing the wear rate though stabilizing austenite to deformation-induced martensite transformation. This transformation is recognized as an important factor in increasing the abrasive response of the alloys. By analyzing the regression equation, the optimal content ranges are found to be 7.5wt%–10.0wt% for V and 2.5wt%–4.5wt% for Cr, which corresponds to the alloys containing 9vol%–15vol% spheroidal VC carbides, 8vol%–16vol% M7C3, and a metastable austenite/martensite matrix. The wear resistance is 1.9–2.3 times that of the traditional 12wt% V–13wt% Mn spheroidal carbide cast iron.

Modeling Experimental Design for Photo-Fenton Degradation of Methomyl

Modeling experimental design was used to study the main effects and the interaction effects between operational parameters in the photocatalytic degradation of pesticide methomyl. The important parameters which affect the removal efficiency of methomyl such as concentration of Fe(NO3)3, concentration of H2O2, initial concentration of the pesticide and pH. The parameters were coded as x1, x2, x3 and x4, consecutively, and were investigated at two levels (–1 and +1). The effects of individual variables and their interaction effects for dependent variables, namely, photocatalytic degradation efficiency (%) were determined. From the statistical analysis, the most effective parameters in the photocatalytic degradation efficiency were initial concentrations of the methomyl and Fe(NO3)3. The interaction between initial concentration of the pesticide and Fe(NO3)3 was the most influencing interaction. The optimum conditions that were obtained for the photocatalytic degradation of methomyl were: minimum quantity of contaminant: 6 × 10–5 mol.L–1, maximum quantity of Fe(NO3)3: 5 × 10–4 mol.L-1, initial pH of the solution: 3 and maximum quantity H2O2: 10–2 mol.L–1.

Influence of parental sample sizes on the estimating genetic parameters in cultured clam Meretrix meretrix based on factorial mating designs

The precise and accurate knowledge of genetic parameters is a prerequisite for making efficient selection strategies in breeding programs.A number of estimators of heritability about important economic traits in many marine mollusks are available in the literature,however very few research have evaluated about the accuracy of genetic parameters estimated with different family structures.Thus,in the present study,the effect of parent sample size for estimating the precision of genetic parameters of four growth traits in clam M.meretrix by factorial designs were analyzed through restricted maximum likelihood（REML） and Bayesian.The results showed that the average estimated heritabilities of growth traits obtained from REML were 0.23-0.32 for 9 and 16 full-sib families and 0.19-0.22 for 25 full-sib families.When using Bayesian inference,the average estimated heritabilities were0.11-0.12 for 9 and 16 full-sib families and 0.13-0.16 for 25 full-sib families.Compared with REML,Bayesian got lower heritabilities,but still remained at a medium level.When the number of parents increased from 6 to 10,the estimated heritabilities were more closed to 0.20 in REML and 0.12 in Bayesian inference.Genetic correlations among traits were positive and high and had no significant difference between different sizes of designs.The accuracies of estimated breeding values from the 9 and 16 families were less precise than those from 25 families.Our results provide a basic genetic evaluation for growth traits and should be useful for the design and operation of a practical selective breeding program in the clam M.meretrix.

Modeling of biodiesel production: Performance comparison of Box–Behnken, face central composite and full factorial design

The performances of the response surface methodology(RSM)in connection with the Box–Behnken,face central composite or full factorial design(BBD,FCCD or FFD,respectively)were compared for the use in modeling of the NaOH-catalyzed sunflower oil ethanolysis.The influence of temperature,catalyst loading,and ethanol-to-oil molar ratio(EOMR)on fatty acid ethyl esters(FAEE)content was evaluated.All three multivariate strategies were efficient in the statistical modeling and optimization of the influential process variables but BBD and FCCD realization involved less number of experiments,generating smaller costs,requiring less work and consuming shorter time than the corresponding FFD.All three designs resulted in the same optimal catalyst loading(1.25%of oil)and EOMR(12:1).The reduced two-factorinteraction(2 FI)models based on the BBD and FCCD defined a range of optimal reaction temperature(25℃–75℃)and 25℃,respectively while the same model based on the 33 FFD appointed 75℃.The predicted FAEE content of about 97%–98.0%was close to the experimentally obtained FAEE content of about 97.0%–97.6%under the optimal reaction conditions.Therefore,the simpler BBD or FCCD might successfully be applied for statistical modeling of biodiesel production processes instead of the more extensive,more laborious and more expensive FFD.

Automatic placement and routing technology for interactive 3D application

Automatic placement and routing technology provides an effective tool for designing simulation and information guidance.Various intelligent algorithms in mechanical design,ocean and ship engineering and aerospace design have been implemented.However,automatic placement and routing has never been integrated into interactive 3D application.In this paper,idea of combining the interactive 3D application with automatic placement and routing is proposed,and its main issue is discussed.Then we present a new placement and routing algorithm suitable for 3D interactive application containing model design,fundamental algorithm and global optimization to remove routing blockage.Experimental results demonstrate that the proposed algorithm works effectively in simulation,meets the requirements of real-time rendering and has great practical value.

Kinetics of phenol and m-cresol biodegradation by an indigenous mixed microbial culture isolated from a sewage treatment plant

An acclimatized mixed microbial culture,predominantly Pseudomonas sp.,was enriched from a sewage treatment plant,and its potential to simultaneously degrade mixtures of phenol and m-cresol was investigated during its growth in batch shake flasks.A 22 full factorial design with the two substrates at two different levels and different initial concentration ranges(low and high),was employed to carry out the biodegradation experiments.The substrates phenol and m-cresol were completely utilized within 21 h when ...

Effect of Welding Parameters on Dilution and Weld Bead Geometry in Cladding

The effect of pulsed gas metal arc welding （GMAW） variables on the dilution and weld bead geometry in cladding X65 pipeline steel with 316L stainless steel was studied. Using a full factorial method, a series of experiments were carried out to know the effect of wire feed rate, welding speed, distance between gas nozzle and plate, and the vertical angle of welding on dilution and weld bead geometry. The findings indicate that the dilution of weld metal and its dimension i.e. width, height and depth increase with the feed rate, but the contact angle of the bead decreases first and then increases. Meantime, welding speed has an opposite effect except for dilution. There is an interaction effect between welding parameters at the contact angle. The results also show forehand welding or decreasing electrode extension decrease the angle of contact. Finally, a mathematical model is contrived to highlight the relationship between welding variables with dilution and weld bead geometry.

Uncertainty and Sensitivity Analyses of the Simulated Seawater—Freshwater Mixing Zones in Steady-State Coastal Aquifers

The uncertainty and sensitivity of predicted positions and thicknesses of seawater-freshwater mixing zones with respect to uncertainties of saturated hydraulic conductivity, porosity, molecular diffusivity, longitudinal and transverse dispersivities were investigated in both head-control and flux-control inland boundary systems. It shows that uncertainties and sensitivities of predicted results vary in different boundary systems. With the same designed matrix of uncertain factors in simulation experiments, the variance of predicted positions and thickness in the flux-control system is much larger than that predicted in the head-control system. In a head-control system, the most sensitive factors for the predicted position of the mixing zone are inland freshwater head and transverse dispersivity. However, the predicted position of the mixing zone is more sensitive to saturated hydraulic conductivity in a flux-control system. In a head-control system, the most sensitive factors for the predicted thickness of the mixing zone include transverse dispersivity, molecular diffusivity, porosity, and longitudinal dispersivity, but the predicted thickness is more sensitive to the saturated hydraulic conductivity in a flux-control system. These findings improve our understandings for the development of seawater-freshwater mixing zone during seawater intrusion processes, and give technical support for groundwater resource management in coastal aquifers.

Uncertainty analysis of seawater intrusion forecasting

In order to describe the importance of uncertainty analysis in seawater intrusion forecasting and identify the main factors that might cause great differences in prediction results, we analyzed the influence of sea level rise, tidal effect, the seasonal variance of influx, and the annual variance of the pumping rate, as well as combinations of different parameters. The results show that the most important factors that might cause great differences in seawater intrusion distance are the variance of pumping rate and combinations of different parameters. The influence of sea level rise can be neglected in a short-time simulation （ten years, for instance）. Retardation of seawater intrusion caused by tidal effects is obviously important in aquifers near the coastline, but the influence decreases with distance away from the coastline and depth away from the seabed. The intrusion distance can reach a dynamic equilibrium with the application of the sine function for seasonal effects of influx. As a conclusion, we suggest that uncertainty analysis should be considered in seawater intrusion forecasting, if possible.

Monitoring Flue-Cured Tobacco Leaf Chlorophyll Content under Different Light Qualities by Hyperspectral Reflectance

Rapid assessment of foliar chlorophyll content in tobacco is critical for assessment of growth and precise management to improve quality and yield while minimizing adverse environmental impact. Our objective is to develop a precise agricultural practice predicting tobacco-leaf chlorophyll-a content. Reflectance experiments have been conducted on flue-cured tobacco over 3 consecutive years under different light quality. Leaf hyperspectral reflectance and chlorophyll-a content data have been collected at 15-day intervals from 30 days after transplant until harvesting. We identified the central band that is sensitive to tobacco-leaf chlorophyll-a content and the optimum wavelength combinations for establishing new spectral indices (simple ratio index, RVI;normalized difference vegetation index, NDVI;and simple difference vegetation index, DVI). We then established linear and BackPropagation (BP) neural network models to estimate chlorophyll-a content. The central bands for leaf chlorophyll-a content are concentrated in the visible range (410 - 680 nm) in combination with the shortwave infrared range (1900 - 2400 nm). The optimum spectral range for the spectral band combinations RVI, NDVI, and DVI are 440 and 470 nm, 440 and 470 nm, and 440 and 460 nm, respectively. The linear RVI, NDVI, and DVI models, SMLR model and the BP neural network model have respective R2 values of 0.76, 0.77, 0.69, 0.78 and 0.86, and root mean square error values of 0.63, 1.60, 1.59, 2.04 and 0.05 mg chlorophyll-a/g (fresh weight), respectively. Our results identified chlorophyll-a sensitive spectral regions and new indices facilitate a rapid, non-destructive field estimation of leaf chlorophyll-a content for tobacco.

A new rotation method for constructing orthogonal Latin hypercube designs

Latin hypercube designs(LHDs)are very popular in designing computer experiments.In addition,orthogonality is a desirable property for LHDs,as it allows the estimates of the main effects in linear models to be uncorrelated with each other,and is a stepping stone to the space-filling property for fitting Gaussian process models.Among the available methods for constructing orthogonal Latin hypercube designs(OLHDs),the rotation method is particularly attractive due to its theoretical elegance as well as its contribution to spacefilling properties in low-dimensional projections.This paper proposes a new rotation method for constructing OLHDs and nearly OLHDs with flexible run sizes that cannot be obtained by existing methods.Furthermore,the resulting OLHDs are improved in terms of the maximin distance criterion and the alias matrices and a new kind of orthogonal designs are constructed.Theoretical properties as well as construction algorithms are provided.