Overall Selection Design Based on the Mega Highway Bridge Project

In the continuous development of the modern highway and bridge engineering industry,the reasonable selection of mega highway bridges and their design is crucial.Based on this,this paper takes the actual bridge project as an example,and analyses the overall selection design of such highway bridges,including the basic overview of the project,the basic selection principle of mega highway bridge project structure and its design strategy,etc.,to provide scientific reference for its selection design.

Landscape Plants Selection and Design in the Peony Garden of Xibaipo

Peony is a traditional famous flower in China.With the peony garden of Xibaipo as an example,the landscaping planning of functional divisions,the selection and design of landscaping plants for the peony garden are introduced in this study,then the landscaping plants selection and design principles are summarized.

Extractive distillation: Advances in conceptual design, solvent selection,and separation strategies

Extractive distillation(ED) is one of the most promising approaches for the separation of the azeotropic or closeboiling mixtures in the chemical industry. The purpose of this paper is to provide a broad overview of the recent development of key aspects in the ED process involving conceptual design, solvent selection, and separation strategies. To obtain the minimum entrainer feed flow rate and reflux ratio for the ED process, the conceptual design of azeotropic mixture separation based on a topological analysis via thermodynamic feasibility insights involving residue curve maps, univolatility lines, and unidistribution curves is presented. The method is applicable to arbitrary multicomponent mixtures and allows direct screening of design alternatives. The determination of a suitable solvent is one of the key steps to ensure an effective and economical ED process. Candidate entrainers can be obtained from heuristics or literature studies while computer aided molecular design(CAMD) has superiority in efficiency and reliability. To achieve optimized extractive distillation systems, a brief review of evaluation method for both entrainer design and selection through CAMD is presented. Extractive distillation can be operated either in continuous extractive distillation(CED) or batch extractive distillation(BED), and both modes have been well-studied depending on the advantages in flexibility and low capital costs. To improve the energy efficiency, several configurations and technological alternatives can be used for both CED and BED depending on strategies and main azeotropic feeds. The challenge and chance of the further ED development involving screening the best potential solvents and exploring the energy-intensive separation strategies are discussed aiming at promoting the industrial application of this environmentally friendly separation technique.

Multi-Agent Few-Shot Meta Reinforcement Learning for Trajectory Design and Channel Selection in UAV-Assisted Networks

Unmanned aerial vehicle(UAV)-assisted communications have been considered as a solution of aerial networking in future wireless networks due to its low-cost, high-mobility, and swift features. This paper considers a UAV-assisted downlink transmission,where UAVs are deployed as aerial base stations to serve ground users. To maximize the average transmission rate among the ground users, this paper formulates a joint optimization problem of UAV trajectory design and channel selection, which is NP-hard and non-convex. To solve the problem, we propose a multi-agent deep Q-network(MADQN) scheme.Specifically, the agents that the UAVs act as perform actions from their observations distributively and share the same reward. To tackle the tasks where the experience is insufficient, we propose a multi-agent meta reinforcement learning algorithm to fast adapt to the new tasks. By pretraining the tasks with similar distribution, the learning model can acquire general knowledge. Simulation results have indicated the MADQN scheme can achieve higher throughput than fixed allocation. Furthermore, our proposed multiagent meta reinforcement learning algorithm learns the new tasks much faster compared with the MADQN scheme.

Evaluation and selection of the ship collaborative design resources based on AHP and genetic and simulated annealing algorithm

The characteristics of the design resources in the ship collaborative design is described and the hierarchical model for the evaluation of the design resources is established. The comprehensive evaluation of the co-designers for the collaborative design resources has been done from different aspects using Analytic Hierarchy Process （AHP） ,and according to the evaluation results,the candidates are determined. Meanwhile,based on the principle of minimum cost,and starting from the relations between the design tasks and the corresponding co-designers,the optimizing selection model of the collaborators is established and one novel genetic combined with simulated annealing algorithm is proposed to realize the optimization. It overcomes the defects of the genetic algorithm which may lead to the premature convergenee and local optimization if used individually. Through the application of this method in the ship collaborative design system,it proves the feasibility and provides a quantitative method for the optimizing selection of the design resources.

Bayesian Variable Selection for Mixture Process Variable Design Experiment

This paper discussed Bayesian variable selection methods for models from split-plot mixture designs using samples from Metropolis-Hastings within the Gibbs sampling algorithm. Bayesian variable selection is easy to implement due to the improvement in computing via MCMC sampling. We described the Bayesian methodology by introducing the Bayesian framework, and explaining Markov Chain Monte Carlo (MCMC) sampling. The Metropolis-Hastings within Gibbs sampling was used to draw dependent samples from the full conditional distributions which were explained. In mixture experiments with process variables, the response depends not only on the proportions of the mixture components but also on the effects of the process variables. In many such mixture-process variable experiments, constraints such as time or cost prohibit the selection of treatments completely at random. In these situations, restrictions on the randomisation force the level combinations of one group of factors to be fixed and the combinations of the other group of factors are run. Then a new level of the first-factor group is set and combinations of the other factors are run. We discussed the computational algorithm for the Stochastic Search Variable Selection (SSVS) in linear mixed models. We extended the computational algorithm of SSVS to fit models from split-plot mixture design by introducing the algorithm of the Stochastic Search Variable Selection for Split-plot Design (SSVS-SPD). The motivation of this extension is that we have two different levels of the experimental units, one for the whole plots and the other for subplots in the split-plot mixture design.

Comparative Study of Visual and Instrumental Analyses of Shade Selection

The difference between visual and instrumental analyses of a shade selection on natural teeth was investigated. With visual analysis, five prosthodontist examined the middle third of the unrestored maxillary right central incisor of a patient using VITAPEN classical and Vita Toothguide 3D-MASTER tooth shade guide. In instrumental analysis, one prosthodontist examined the same teeth using a spectrophotometer （ShadepilotTM, Degudent, Hanau-Wolfgang, Germany, software 2.40）. Overall, instrumental analysis is more accurate and reproducible than a visual assessment. However, the difference is clinically acceptable.

Variable Selection in Randomized Block Design Experiment

In the experimental field, researchers need very often to select the best subset model as well as reach the best model estimation simultaneously. Selecting the best subset of variables will improve the prediction accuracy as noninformative variables will be removed. Having a model with high prediction accuracy allows the researchers to use the model for future forecasting. In this paper, we investigate the differences between various variable selection methods. The aim is to compare the analysis of the frequentist methodology (the backward elimination), penalised shrinkage method (the Adaptive LASSO) and the Least Angle Regression (LARS) for selecting the active variables for data produced by the blocked design experiment. The result of the comparative study supports the utilization of the LARS method for statistical analysis of data from blocked experiments.

Optimal Selection Model of Equipment Design Scheme Based on Set Pair Analysis

Selecting the optimal one from similar schemes is a paramount work in equipment design.In consideration of similarity of schemes and repetition of characteristic indices,the theory of set pair analysis(SPA)is proposed,and then an optimal selection model is established.In order to improve the accuracy and flexibility,the model is modified by the contribution degree.At last,this model has been validated by an example,and the result demonstrates the method is feasible and valuable for practical usage.

PENETRATION RATE MEASUREMENT AND ITS INSTRUMENT DESIGN

The practical method for precise penetration rate measurement in a short time and the instrument design have been specially discussed in this paper.Considering the defects of the penetration rate meters available,via the balanced design in consideration of service life,costs,accuracy and reliability,a kind of penetration rate meter has been put forward.The meter consists of a magnetic clutch,a gear box and a raster disk system to pick up the signal.The meter has the following advantages-it might measure a low speed with higher accura-cy,it could disengage automatically without being divorced from the driving device during tripping rods at high speed,it has a circuit of rotary direction discrimination and of repeated counting prevention so as to eU-minate error caused by rod vibration.

Selection diagram of design algorithms for neutron-focusing supermirrors

The neutron supermirror is an important neutron optical device that can significantly improve the efficiency of neutron transport in neutron guides and has been widely used in research neutron sources.Three types of algorithms,including approximately ten algorithms,have been developed for designing high-efficiency supermirror structures.In addition to its applications in neutron guides,in recent years,the use of neutron supermirrors in neutronfocusing mirrors has been proposed to advance the development of neutron scattering and neutron imaging instruments,especially those at compact neutron sources.In this new application scenario,the performance of supermirrors strongly affects the instrument performance;therefore,a careful evaluation of the design algorithms is needed.In this study,we examine two issues:the effect of nonuniform film thickness distribution on a curved substrate and the effect of the specific neutron intensity distribution on the performance of neutron supermirrors designed using existing algorithms.The effect of film thickness nonuniformity is found to be relatively insignificant,whereas the effect of the neutron intensity distribution over Q(where Q is the magnitude of the scattering vector of incident neutrons)is considerable.Selection diagrams that show the best design algorithm under different conditions are obtained from these results.When the intensity distribution is not considered,empirical algorithms can obtain the highest average reflectivity,whereas discrete algorithms perform best when the intensity distribution is taken into account.The reasons for the differences in performance between algorithms are also discussed.These findings provide a reference for selecting design algorithms for supermirrors for use in neutron optical devices with unique geometries and can be very helpful for improving the performance of focusing supermirror-based instruments.

On the design and selection of vehicle coordination policies for underground mine production ramps

Traffic management in underground mines,especially on production ramps,is a difficult problem to optimize and control.Most operations use one of a few common policies;e.g.,the so-called ‘‘lock-out" and‘‘loaded-vehicle-priority" policies.The work presented in this paper uses discrete-event simulation to study the efficiency of multiple policies.Based on simulation results,an improvement to the common lock-out policy is proposed.This new policy utilizes the rules of the lock-out policy but integrates an option that allows a group of vehicles to be given temporary priority in a certain direction of travel.Quantitative results are provided and,based on these,a systematic technique for ramp design that aims to optimize the efficiency of underground mine ramp traffic flow is described.

The Selection and Application of Non-Conventional Decoration Materials in Indoor Design

In indoor design innovation, the material role can not be ignored. In indoor design, using non-conventional decoration materials can make space more personalized and charming. This is one of the material innovation modes and also one of the indoor design innovation modes. The design method should obtain more attention.

Logical Framework,Path Selection and Mechanism Design for Cultivation of New Type Professional Farmers

New type professional farmers are farmers who possess certain resources and capitals,have certain extent of spirit of entrepreneurship,and are fully capable of obtaining and allocating resources related to agricultural production and management,and engaged in agricultural production and management for obtaining average profit.Cultivation of new type professional farmers should be promoted in the process and at the background of"coordinated development of industrialization,informationization,urbanization and agricultural modernization".It should establish a proper cultivation subject system consisting of government,enterprises,rural communities and nonprofit organizations.Relying on multiple motive forces,efforts should be concentrated on cultivating those farmers with enterprising,highly innovative and learning ability,to guide traditional farmers to change into learning,enterprising and innovative ones.In addition,cultivation of new type professional farmers must rely on farmer education and training,modern agricultural development,increase in agricultural comparative advantage,innovation of rural management system and mechanism,multiple types of agricultural operation on a fairly large scale,as well as construction and regulation of new rural communities.Finally,it is recommended to provide system guarantee from long-term input mechanism of new type professional farmer education and training,incentive and restrictive mechanism of new type professional farmer cultivation,and construction of favorable environment for agricultural entrepreneurship.

Chemical Reaction Route Selection Based on Green Chemical Engineering

In the preliminary stage of chemical process design, the choice of chemical reaction route is the key design decision, and the concepts of atom utilization and environmental quotient have become extremely useful tools. However, the waste quality such as chemical toxicity and other engineering factors have not been taken into account. Therefore, a synthetic route selection index, Iroute, is proposed to determine the suitability of a chemical route in this paper. Iroute considers the effects of 'extended atom economy', material renewability, chemical characteristics and some engineering factors. The extended atom economy concept regards not only the value of the desired product but also the value of byproducts. The methodology by using Iroute to compare different routes is illustrated in case study of cyclohexanone oxime and acrylonitrile manufacture.

Marker-assisted Selection of ZmC_4Ppc in Rice Breeding and Yield Trait Performances of Advanced Lines

The full-length of intact Zea mays gene for phosphoenolpyruvate carboxylase gene （ZmC4Ppc） is 6 781 bp. The products of PCR for this gene were not clear with poor repeatability, resulting in that it was difficult for marker-assisted selection （MAS） both in rice and maize. For selecting the markers for MAS, sequences presented only in maize rather than in rice were identified by BLAST, and used for primer design using Primer Premier 5.0. A pair of specific primer termed MRpc （Forward： 5＇ AAGCAGGGAAGCGAGACG 3＇, Reverse： 5＇ GATTGCCGCCAGCAGTAG 3＇） was used for selection of transformed rice, and ZmC4Ppc could be highly and constitutively expressed at each tested developmental stages in the transformed rice selected by using MRpc. Thus, MRpc was used for MAS of progenies carrying ZmC4Ppc gene in rice and some restorer lines with ZmC4Ppc （e.g. FPM881） derived from ZmC4Ppc-transformed Kitaake backcrossed with a restorer line Shuhui 881 were obtained. The analyses on genetic background, PEPCase activity, net photosynthetic rate, general combining ability （GCA） and specific combining ability （SCA） of FPM881 showed that similarity of genetic background reached above 95%, the PEPCase and net photosynthetic rate were higher than those of the control, and some of the progenies carrying ZmC4Ppc gene had better GCA and SCA for grain yield per plant, number of panicles per plant, and 1000-grain weight than those of the control. This suggested that the introduction of maize ZmC4Ppc gene via MAS and its stable expression could increase grain yield of rice and would likely provide a pathway for rice varietal improvement.

Tuning the Morphology of Pharmaceutical Compounds via Model Based Solvent Selection

In this paper we present a strategy for tuning the crystal morphology of pharmaceutical compounds by the appropriate choice of solvent via an optimization model. A three-stage approach involving a pre-design stage, a product design stage and a post-design experimental verification stage is presented. The pre-design stage addresses the tormulation of the property constraint tor crystal morphology. This involves crystallization experiments aria development of property models and constraints for morphology. In the design stage various property requirements for the solvent along with crystal morphology are considered and the product design problem is formulated as a mixed integer nonlinear programming model.The design stage provides an optimal solvent/list of candidate solvents. Similar to the pre-design stage, in the post design experimental verification stage, the morphology of the crystals （precipitated from the designed solvent） is verified through crystallization experiments followed by product characterization via scanni＇ng electron microscopy, powder X-ray diffraction imaging and Fourier transform spectra analysis.

Systematic Selection of Green Solvents for Organic Reacting Systems

The solvent selection methodology developed earlier by. Gani （tal. （Comp. Chem. Eng., 2005）has been extended to handle multi-step reaction systems. The solvent selection problem was formulated based on the methodology guidelines, and solved using ICAS software tool. A list with solvent candidates is generated so that it can be further investigated experimentally. Comments and clarifications from chemists have been incorporated into the problem forrnulations to clarify the role of the solvents in the chemistry and potential reactivity issues. Highly promising results were obtained, in accordance with. industrial process data.

Development of Landscaping and Selection of Contemporary Landscaping Plants

With the acceleration of urbanization in various places,the landscaping in various provinces and cities has been developed to varying degrees.Therefore,further standardizing the principles of urban greening landscape design plays an important role in rationally preparing urban landscaping and highlighting urban characteristics and regional cultural characteristics.From the perspective of the locations of gardens,occupiers identities,the development mode,the design principle and the arrangement of flowers,this paper classified and expounded the key points of contemporary landscaping,aiming to provide reference for the subsequent construction of landscaping and plant arrangement according to local conditions.

Theoretical Basis in Regression Model Based Selection of the Most Cost Effective Parameters of Hard Rock Surface Mining

What determines selection of the most cost effective parameters of hard rock surface mining is consideration of all alternative variants of mine design and the conflicting effect of their parameters on cost. Consideration could be realized based on the mathematical model of the cumulative influence of rockmass and mine design variables on the overall cost per ton of the hard rock drilled, blasted, hauled and primary crushed. Available works on the topic mostly dwelt on four processes of hard rock surface mining separately. This paper dwells on the theoretical part of a research proposed to enhance effectiveness in the selection of the parameters of hard rock surface mining design based on the regression model of overall cost per tonne of the rock mined fit on the determinant variations of rockmass and mine design. The regression model could be developed based on the statistical data generated by many of the hard rock surface mines operating in variable conditions of rockmass and mine design worldwide. Also, a regression model based general algorithm has been formulated for the development of software and computer aided selection of the most cost effective parameters of hard rock surface mining.