Optimization of ISSR-PCR Reaction System and Preliminary Construction of ISSR Fingerprinting of Some Species in Bryaceae

[Objective] The aim was to provide molecular basis for the identification of species in the moss family Bryaceae by the construction of inter-simple sequence repeats （ISSR） fingerprinting. [Method] In order to seek standardizing PCR reaction set-up, an orthogonal design was used to optimize ISSR-PCR amplification system of Bryaceae in five factors （Mg2＋, dNTPs, primer, DNA template, Taq DNA polymerase） at four levels respectively. [Result] A suitable ISSR reaction system was obtained, namely： 20 μl reaction system containing 5 ng of DNA template, 0.2 μmol/L primer, 2.25 mmol/L MgCl2, 0.6 U of Taq DNA polymerase, 0.4 mmol/L dNTPs. Proper annealing temperature was found at 48-50 ℃.The above system and six ISSR-PCR primers were used for the PCR amplification of 14 samples from Bryaceae and the related species in Mniaceae. A total of 86 bands were amplified, all showed polymorphism. NJ cluster analysis showed a star-shaped cladogram. [Conclusion] The results manifested that ISSR fingerprinting could provide the appropriate degree of polymorphism at low taxonomic level, so it would be a useful tool to provide additional evidence for resolving taxonomic relationships at the species level of Bryaceae.

Study on Establishment of cpSSR Marker Technology and Optimization of Its Reaction System in Jatropha curcas Linn

[ Objective] The aim of this study was to establish the optimum cpSSR-PCR system for Jatropha curcas Linn. [ Method] cpSSR-PCR amplification system for Jatropha curcas Linn influenced by five factors including Taq DNA polymerase, Mg^2＋ , DNA template, dNTP and primer were optimized from several levels. [ Result] The optimum concentration of 20 μl reaction system was 10 × Buffer, 2.00 mmol/L Mg^2＋ , 2 U/μl Taq DNA polymerase, 0.2 mmol/L dNTP, 0.2 μmol/L primer and 35 ng/μl DNA template. [ Conclusion] The optimum annealing temperature for cpSSR-PCR reaction system is 52 ℃, and the cpSSR reaction system is steady and reproducible.

Establishment and Optimization of Rye-specific PCR Reaction System

[Objective] The aim was to establish the optimal rye-specific PCR reaction system for rye.[Method] The ordinary wheat ＂Chinese Spring＂,S165,rye,octoploid triticale and hexaploid triticale were used as materials to carry out study on the effect of the amount of template DNA,primers,dNTPs,Mg2＋ concentrations,Taq DNA polymerase and annealing temperature on the rye-specific PCR reaction system of rye.[Result] The genomic DNA extracted by modified CTAB DNA extraction method showed high quality,which was satisfied for the PCR reaction template.The rye-specific PCR reaction system was 25 μl,including 10 × buffer solution,1.5 mmol/L MgCl2,200 μmol/L dNTP,40 ng primers,40-60 ng DNA template and 1 U Taq DNA polymerase.[Conclusion] The optimal rye-specific PCR reaction system was established,which provided basis for the identification of exogenous germplasm of rye in wheat background.

Optimization of PCR Reaction System for Random Single-strand DNA Pool in SELEX Technology

[Objective] This study aimed to optimize the PCR amplification conditions for random ssDNA pool in SELEX technology. [Method] L16（45） orthogonal experimental design was adopted for optimization of five important factors affecting PCR reaction system for random single-stranded DNA pool including Mg2＋ concentration, dNTP concentration, amount of Taq DNA polymerase, primer concentration and amount of random single-stranded DNA pool at four levels. Meanwhile, the annealing temperature and number of PCR reaction cycles were optimized to establish the optimal reaction system and PCR procedure. [Result] The optimal combination of PCR reaction system for random ssDNA pool was obtained, with a total system volume of 20 μl containing 2.0 μl of 10 × Buffer, 0.5 ng of random ssDNA pool, 2.5 mmol/L Mg2＋, 0.25 mmol/L dNTP Mixture, 0.6 μmol/L upstream and downstream primers and 1.5 U of Taq DNA polymerase; the optimal annealing temperature was 68 ℃ and the optimal number of cycles was 12. Under the above conditions, clear and stable bands with high specificity for random ssDNA pool were amplified. [Conclusion] This study laid the foundation for selection of parameters with higher specificity in SELEX technology.

Optimization of RAPD-PCR Reaction System for Glycyrrhiza uralensis Based on Orthogonal Design

[Objective] The aim was to obtain the optimum RAPD-PCR reaction system for Glycyrrhiza uralensis.[Method] Orthogonal design was adopted to screen the suitable concentration of four major factors（dNTPs,primers,Taq polymerase and DNA template） in PCR reaction system.[Result] The optimal reaction system obtained by orthogonal design was 25 μl in total volume,containing 2.5 μl of 10×PCR buffer solution（include MgCl2）,2.5 μl of 10 mmol/L dNTPs,2 μl（100 ng） of DNA template,2 μl of 10 μmol/L primers,0.4 μl（5 U） of Taq polymerase;the optimum annealing temperature was 34 ℃.[Conclusion] Orthogonal design was an effective method for the optimization of RAPD-PCR reaction system for G.uralensis.

Establishment and Optimization of ISSR-PCR Reaction System for Cymbidium ensifolium (Linn.) Sw

[Objective] This research aimed to search a best method for extracting the genomic DNA of Cymbidium ensifolium and establish the optimized ISSR-PCR reaction system.[Method] Genomic DNA was extracted from C.ensifolium leaves by modified CTAB method.ISSR-PCR reaction system for C.ensifolium was optimized.[Result] High-quality genomic DNA was obtained from C.ensifolium.The 25 μl optimized ISSR-PCR reaction system for C.ensifolium contained 2.5 μl 10× PCR buffer,2.5 mmol/L MgCl2,240 ng template DNA,160 μmol/L dNTPs,1.25 U Taq DNA polymerase,0.4 μmol/L primer and 15.78 μl ddH2O.The optimal PCR procedures were：94 ℃ pre-denaturation for 5 min and then 40 cycles,94 ℃ denaturation for 30 s,50-60 ℃ annealing for 30 s （annealing temperature according to different primers）,72 ℃ extension for 50 s and a 72 ℃ extension for 7 min.[Conclusion] An optimized ISSR-PCR reaction system for C.ensifolium was established,which provides a basis for further study on genetic diversity of C.ensifolium by using ISSR molecular marker technique.

Establishment and Optimization of ISSR-PCR Reaction System for Cymbidium faberi Rolfe

[Objective] By using the genomic DNA of Cymbidium faberi Rolfe as template,the factors that affect the result of ISSR-PCR reaction system were researched and the optimal system was established.[Method] The genomic DNA was extracted from C.faberi Rolfe with method of modified CTAB.Different factors which affected ISSR amplification reaction were optimized.[Result] High-quality genomic DNA was obtained from C.faberi Rolfe.And the optimal reaction system was as follows：25 μl amplification reactions system contained 2.5 μl 10 × PCR buffer,2.0 mmol/L MgCl2,60 ng template DNA,160 μmol/L dNTPs,1.25 U Taq DNA polymerase,0.4 μmol/L ISSR primer and 15.85 μl ddH2O.The optimal amplification procedures were pre-denaturing for 5 min at 94 ℃,followed by 40 cycles of denaturing for 30 s at 94 ℃,annealing for 30 s at a temperature of 2-3 ℃ lower than melting temperature of each primer pair,extension for 50 s at 72 ℃.Then extension step of 7 min at 72 ℃ was performed.[Conclusion] The optimal system could provide a favorable basis for further study on genetic diversity of C.faberi Rolfe by using ISSR molecular marker technique.

Study on trifluoromethanesulfonic acid-promoted synthesis of daidzein: Process optimization and reaction mechanism

Daidzein has been widely used in pharmaceuticals,nutraceuticals,cosmetics,feed additives,etc.Its preparation process and related reaction mechanism need to be further investigated.A cost-effective process for synthesizing daidzein was developed in this work.In this article,a two-step synthesis of daidzein(Friedel–Crafts acylation and[5+1]cyclization)was developed via the employment of trifluoromethanesulfonic acid(TfOH)as an effective promoting reagent.The effect of reaction conditions such as solvent,the amount of TfOH,reaction temperature,and reactant ratio on the conversion rate and the yield of the reaction,respectively,was systematically investigated,and daidzein was obtained in 74.0%isolated yield under optimal conditions.Due to the facilitating effect of TfOH,the Friedel–Crafts acylation was completed within 10 min at 90℃ and the[5+1]cyclization was completed within 180 min at 25℃.In addition,a possible reaction mechanism for this process was proposed.The results of the study may provide useful guidance for industrial production of daidzein on a large scale.

Multi-Objective Optimization of Multi-Product Parallel Disassembly Line Balancing Problem Considering Multi-Skilled Workers Using a Discrete Chemical Reaction Optimization Algorithm

This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle time.Based on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is designed.To enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular individuals.The established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,respectively.Introducing a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.

Optimization of SSR-PCR Reaction System and Screening of Polymorphic Primers for RIL Parents

[Objective] This study aimed to establish a high-efficiency and stable SSR amplification system and screen polymorphic primers in order to further compare the tri-group probability analysis method and traditional QTL mapping method. [Method] In this study, we preliminarily screened the 605 pairs of primers evenly distributed on the 12 chromosomes through investigating their polymorphism performance in amplification, and established an optimized SSR-PCR reaction system. [Result] A 10μL SSR-PCR reaction system suitable for rice was set up as fol ows： 2 μl of 10 × Buffer, 2.0 mmol/L Mg2＋ （final concentration）, 0.5 mmol/L dNTPs, 1.0 μmol/L primers （final concentration）, 1 μl of DNA template, 0.15 U Taq DNA polymerase. Among the SSR primers distributed over the genome, 142 pairs that were polymorphic upon the parents were screened. [Conclusion] This study lays a good foundation for sub-sequent QTL mapping studies.

Optimization of reaction for synthesis of polyisobutylene amine between amination agent and epoxy polyisobutylene

An optimization study on the amination reaction of epoxy polyisobutylene for synthesis of polyisobutylene amine is presented. The experimental results indicate that n-butanol and ethylenediamine are the suitable solvent and amination agents for the reaction, respectively. The reaction yield of the amination reaction is notably increased with the enhanced molar ratio of either n-butanol against epoxy polyisobutylene or ethylenediamine against epoxy polyisobutylene. Also, the yield is enhanced with increasing temperature and time during the experimental range. Strikingly, the yield reaches as high as 91. 30% under optimal conditions; with the molar ratio of ethylenediamine, n-butanol and PIBO of 10∶ 6∶ 1, the reaction temperature of 150 ℃ and the reaction time of 6 h. In addition, the yield of the reaction is slightly decreased with the enhanced water content of the system. Accordingly, the mass concentration of water should be controlled within 1. 7% during the reaction.

Cryo-electron microscopy structure of the intact photosynthetic light-harvesting antenna-reaction center complex from a green sulfur bacterium

The photosynthetic reaction center complex(RCC)of green sulfur bacteria(GSB)consists of the membrane-imbedded RC core and the peripheric energy transmitting proteins called Fenna–Matthews–Olson(FMO).Functionally,FMO transfers the absorbed energy from a huge peripheral light-harvesting antenna named chlorosome to the RC core where charge separation occurs.In vivo,one RC was found to bind two FMOs,however,the intact structure of RCC as well as the energy transfer mechanism within RCC remain to be clarified.Here we report a structure of intact RCC which contains a RC core and two FMO trimers from a thermophilic green sulfur bacterium Chlorobaculum tepidum at 2.9A resolution by cryo-electron microscopy.The second FMO trimer is attached at the cytoplasmic side asymmetrically relative to the first FMO trimer reported previously.We also observed two new subunits(PscE and PscF)and the N-terminal transmembrane domain of a cytochrome-containing subunit(PscC)in the structure.These two novel subunits possibly function to facilitate the binding of FMOs to RC core and to stabilize the whole complex.A new bacteriochlorophyll(numbered as 816)was identified at the interspace between PscF and PscA-1,causing an asymmetrical energy transfer from the two FMO trimers to RC core.Based on the structure,we propose an energy transfer network within this photosynthetic apparatus.

The Dynamic Flexibility of Batch Exothermic Reaction System： Take into Account the Effect of the Initial Operational Temperature

It is shown in this article that by changing the initial operation condition of the batch processes, the dynamic performance of the system can be varied largely, especially for the initial operational temperature of the exothermic reaction. The initial operation condition is often ignored in the designing batch processes for flexibility against disturbances or parameter variations. When the initial condition is not rigid as in the case of a batch reactor, where the initial reaction temperature is quite arbitrary, optimization can also be applied to determine the ＂best＂ initial condition to use. Problems for dynamic flexibility analysis of exothermic reaction including initial temperature and process operation can be formulated as dynamic optimization problems. Formulations are derived when the initial conditions are considered or not. When the initial conditions are considered, the initial condition can be transferred into control variables in the first optimal step. The solution of the dynamic optimization is on the basis of Rugge-Kutta integration algorithm and decomposition search algorithm. This method, as illustrated and tested with two highly nonlinear process problems, enables the determination of the optimal level. The dynamic performance is improved by the proposed method in the two exothermic reaction examples.

Modeling and Optimization of Ethane Steam Cracking Process in An Industrial Tubular Reactor with Improved Reaction Scheme

Ethane steam cracking process in an industrial reactor was investigated.An one-demsional(1D)steady-state model was developed firstly by using an improved molecular reaction scheme and was then simulated in Aspen Plus.A comparison of model results with industrial data and previously reported results showed that the model can predict the process kinetics more accurately.In addition,the validated model was used to study the effects of different process variables,including coil outlet temperature(COT),steam-to-ethane ratio and residence time on ethane conversion,ethylene selectivity,products yields,and coking rate.Finally,steady-state optimization was conducted to the operation of industrial reactor.The COT and steam-to-ethane ratio were taken as decision variables to maximize the annual operational profit.

Extreme learning with chemical reaction optimization for stock volatility prediction

Extreme learning machine(ELM)allows for fast learning and better generalization performance than conventional gradient-based learning.However,the possible inclusion of non-optimal weight and bias due to random selection and the need for more hidden neurons adversely influence network usability.Further,choosing the optimal number of hidden nodes for a network usually requires intensive human intervention,which may lead to an ill-conditioned situation.In this context,chemical reaction optimization(CRO)is a meta-heuristic paradigm with increased success in a large number of application areas.It is characterized by faster convergence capability and requires fewer tunable parameters.This study develops a learning framework combining the advantages of ELM and CRO,called extreme learning with chemical reaction optimization(ELCRO).ELCRO simultaneously optimizes the weight and bias vector and number of hidden neurons of a single layer feed-forward neural network without compromising prediction accuracy.We evaluate its performance by predicting the daily volatility and closing prices of BSE indices.Additionally,its performance is compared with three other similarly developed models—ELM based on particle swarm optimization,genetic algorithm,and gradient descent—and find the performance of the proposed algorithm superior.Wilcoxon signed-rank and Diebold–Mariano tests are then conducted to verify the statistical significance of the proposed model.Hence,this model can be used as a promising tool for financial forecasting.

Optimization of reaction conditions for the electroleaching of manganese from low-grade pyrolusite

In the present study, a response surface methodology was used to optimize the electroleaching of Mn from low-grade pyrolusite. Ferrous sulfate heptahydrate was used in this reaction as a reducing agent in sulfuric acid solutions. The effect of six process variables, including the mass ratio of ferrous sulfate heptahydrate to pyrolusite, mass ratio of sulfuric acid to pyrolusite, liquid-to-solid ratio, current density, leaching temperature, and leaching time, as well as their binary interactions, were modeled. The results revealed that the order of these factors with respect to their effects on the leaching efficiency were mass ratio of ferrous sulfate heptahydrate to pyrolusite 〉 leaching time 〉 mass ratio of sulfuric acid to pyrolusite 〉 liquid-to-solid ratio 〉 leaching temperature 〉 current density. The optimum conditions were as follows： 1.10：1 mass ratio of ferrous sulfate heptahydrate to pyrolusite, 0.9：1 mass ratio of sulfuric acid to pyrolusite, liquid-to-solid ratio of 0.7：1, current density of 947 A/m^2, leaching time of 180 min, and leaching temperature of 73°C. Under these conditions, the predicted leaching efficiency for Mn was 94.1%; the obtained experimental result was 95.7%, which confirmed the validity of the model.

A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction

Accurate prediction of stock market behavior is a challenging issue for financial forecasting.Artificial neural networks,such as multilayer perceptron have been established as better approximation and classification models for this domain.This study proposes a chemical reaction optimization(CRO)based neuro-fuzzy network model for prediction of stock indices.The input vectors to the model are fuzzified by applying a Gaussian membership function,and each input is associated with a degree of membership to different classes.A multilayer perceptron with one hidden layer is used as the base model and CRO is used to the optimal weights and biases of this model.CRO was chosen because it requires fewer control parameters and has a faster convergence rate.Five statistical parameters are used to evaluate the performance of the model,and the model is validated by forecasting the daily closing indices for five major stock markets.The performance of the proposed model is compared with four state-of-art models that are trained similarly and was found to be superior.We conducted the Deibold-Mariano test to check the statistical significance of the proposed model,and it was found to be significant.This model can be used as a promising tool for financial forecasting.

Solving Multi-Area Environmental/Economic Dispatch by Pareto-Based Chemical-Reaction Optimization Algorithm

In this study, we present a Pareto-based chemicalreaction optimization(PCRO) algorithm for solving the multiarea environmental/economic dispatch optimization problems.Two objectives are minimized simultaneously, i.e., total fuel cost and emission. In the proposed algorithm, each solution is represented by a chemical molecule. A novel encoding mechanism for solving the multi-area environmental/economic dispatch optimization problems is designed to dynamically enhance the performance of the proposed algorithm. Then, an ensemble of effective neighborhood approaches is developed, and a selfadaptive neighborhood structure selection mechanism is also embedded in PCRO to increase the search ability while maintaining population diversity. In addition, a grid-based crowding distance strategy is introduced, which can obviously enable the algorithm to easily converge near the Pareto front. Furthermore,a kinetic-energy-based search procedure is developed to enhance the global search ability. Finally, the proposed algorithm is tested on sets of the instances that are generated based on realistic production. Through the analysis of experimental results, the highly effective performance of the proposed PCRO algorithm is favorably compared with several algorithms, with regards to both solution quality and diversity.

Reaction network design and hybrid modeling of S Zorb

At present,many countries are becoming more and more stringent in terms of sulfur content in fuel oil.S Zorb is a kind of desulfurization technology with advantages of exceptional desulfurization efficiency and small impact on octane number.To meet the needs of environmental requirements and the trend of digitalization in the petrochemical industry,a first-principle model of S Zorb was established based on industry data.In order to describe the desulfurization and the other side reactions,a reaction network was designed and the kinetic parameters were estimated by the particle swarm optimization algorithm.Two hybrid models based on the first-principle model and support vector regression method were established to correct the mass fraction of sulfur and predict the research octane number of the refined gasoline respectively.The results indicate that the hybrid models can predict the mass fraction of PIONA,sulfur content and research octane number of the refined gasoline accurately,of which the mean absolute percentage errors are less than 6%.Hybrid models were then applied to optimize the decision variables to minimize the research octane number loss.Optimization results show that the average reduction of the loss of research octane number is 21.8%,which suggests that the models developed hold promise for guiding practical production.

Thiourea crystal growth kinetics,mechanism and process optimization during cooling crystallization

In the cooling crystallization process of thiourea,a significant issue is the excessively wide crystal size distribution(CSD)and the abundance of fine crystals.This investigation delves into the growth kinetics and mechanisms governing thiourea crystals during the cooling crystallization process.The fitting results indicate that the crystal growth rate coefficient,falls within the range of 10^(-7)to 10^(-8)m·s^(-1).Moreover,with decreasing crystallization temperature,the growth process undergoes a transition from diffusion-controlled to surface reaction-controlled,with temperature primarily influencing the surface reaction process and having a limited impact on the diffusion process.Comparing the crystal growth rate,and the diffusion-limited growth rate,at different temperatures,it is observed that the crystal growth process can be broadly divided into two stages.At temperatures above 25℃,1/qd(qd is diffusion control index)approaches 1,indicating the predominance of diffusion control.Conversely,at temperatures below 25℃,1/qd increases rapidly,signifying the dominance of surface reaction control.To address these findings,process optimization was conducted.During the high-temperature phase(35-25℃),agitation was increased to reduce the limitations posed by bulk-phase diffusion in the crystallization process.In the low-temperature phase(25-15℃),agitation was reduced to minimize crystal breakage.The optimized process resulted in a thiourea crystal product with a particle size distribution predominantly ranging from 0.7 to 0.9 mm,accounting for 84%of the total.This study provides valuable insights into resolving the issue of excessive fine crystals in the thiourea crystallization process.