小学英语课堂教学的整合性及其提升路径

整合性是课堂教学的基本属性,表现为外在结果的整体性与内在过程的融合性。提升课堂教学的整合性是促进学生全面发展的本质要求,也是培育学生核心素养的重要途径。教师应秉持育人为本的理念,以发展学生的核心素养为目标,通过构建整体性目标、生成整合性教学内容以及设计循环递进的教学活动,提升课堂教学的整合性。

Survey of Multidrug Resistance and Class I Integron Prevalence in Chicken-derived Salmonella

[Objective] This study aimed to investigate the multidrug resistance and prevalence of class I integrons in Salmonel a. [Method] Salmonel a strains were isolated from chicken farms in Shandong Province. Kauffmann-White classification method was employed to analyze the serotypes of Salmonel a strains. Minimum in-hibition concentration （MIC） of Salmonel a strains against 19 common antimicrobial drugs was analyzed determined with microdilution method. The class I integrons and carried drug resistance gene cassettes were detected by PCR. [Result] A total of 311 Salmonel a strains were isolated and classified into two serotypes, including 133 Salmonel a Indiana strains and 178 Salmonel a Enteritidis strains. Drug sensitivity test showed that the isolated Salmonel a strains were general y resistant to sulfadiazine, sulfamethoxazole, nalidixic acid, ampicil in, tetracycline, doxycycline and trimethoprim, with a multidrug resistance rate of 91.0% （283/311）; 99% strains were sensitive to amikacin and colistin. PCR assay indicated that the detection rate of class I integrons was 65.0% （202/311）; the positive rate of class I integrons in Salmonel a strains with multidrug resistance was 92.6%; among 202 positive strains, six strains carried gene cassette dfr17-aadA5. [Conclusion] According to the above results, class I integrons exist general y in Salmonel a and are closely associated with the multidrug resistance of Salmonel a strains.

Discrimination for minimal hepatic encephalopathy based on Bayesian modeling of default mode network

In order to classify the minimal hepatic encephalopathy （MHE） patients from healthy controls, the independent component analysis （ICA） is used to generate the default mode network （DMN） from resting-state functional magnetic resonance imaging （fMRI）. Then a Bayesian voxel- wised method, graphical-model-based multivariate analysis （GAMMA）, is used to explore the associations between abnormal functional integration within DMN and clinical variable. Without any prior knowledge, five machine learning methods, namely, support vector machines （SVMs）, classification and regression trees （ CART ）, logistic regression, the Bayesian network, and C4.5, are applied to the classification. The functional integration patterns were alternative within DMN, which have the power to predict MHE with an accuracy of 98%. The GAMMA method generating functional integration patterns within DMN can become a simple, objective, and common imaging biomarker for detecting MIIE and can serve as a supplement to the existing diagnostic methods.

Study on the Feasibility of the Calculation Methods of Consolidating Rural Residential Land into Arable Land in China

Since the increasing demand for arable land and low efficient and disordered use of rural residential land,land consolidation for rural settlement has become a hot issue in China.Many Chinese scientists studied the topic from different angles.However,there is no reference systematically summarizing and discussing feasibility of consolidating rural residential land into arable land.The authors listed and analyzed the calculation methods of consolidating rural residential land into arable land,and discussed the feasibility and reasonability of those methods.Moreover,this paper put forward the study orientation in this regard for providing references for relevant researches.

Aurantiamide Acetate from Stems of Zanthoxylum Dissitum Hemsley

The genus Zanthoxylum (Rutaceae) is comprised of about 50 species in China.Zanthoxylum dissitum Hems-ley, locally called 'Shanpipa', has been used to treat pains in the loin,limbs and arthritis in Chinese folk medicine. Our previous study reported the isolation andidentification of five quinoline alkaloids . In this continuing study on the chemcial constituentsof Zanthoxylum dissitum Hemsley, a phenylalanine derivative was obtained .

Multi-objective Evolutionary Algorithms for MILP and MINLP in Process Synthesis

Steady-state non-dominated sorting genetic algorithm (SNSGA), a new form of multi-objective genetic algorithm, is implemented by combining the steady-state idea in steady-state genetic algorithms (SSGA) and the fitness assignment strategy of non-dominated sorting genetic algorithm (NSGA). The fitness assignment strategy is improved and a new self-adjustment scheme of is proposed. This algorithm is proved to be very efficient both computationally and in terms of the quality of the Pareto fronts produced with five test problems including GA difficult problem and GA deceptive one. Finally, SNSGA is introduced to solve multi-objective mixed integer linear programming (MILP) and mixed integer non-linear programming (MINLP) problems in process synthesis.

Effects of pore size and porosity of surface-modified porous titanium implants on bone tissue ingrowth

The effects of surface-modified porous titanium implants with different porosities and pore sizes on osseointegration were investigated in vivo.Three porous titanium implants(A30,A40 and A50 containing volume fractions of space-holder NaCl being 30%,40%and 50%,respectively)were manufactured by metal injection moulding(MIM).The surface-modified implants were implanted into muscles and femurs of hybrid male dogs.Interface osteogenic activity and histological bone ingrowth of porous titanium implants were evaluated at 28,56 and 84 d.The results showed that when additive space-holder amount of NaCl increased from 30%to 50%(volume fraction),the general porosity and mass fraction of macropores of porous titanium rose from 42.4%to 62.0%and from 8.3%to 69.3%,respectively.Histologic sections and fluorescent labeling showed that the A50 implant demonstrated a significantly higher osteogenic capacity at 28 d than other implants.Bone ingrowth into the A30 implant was lower than that into other implants at 84 d.Therefore,the pore structure of A50 implant was suitable for new bone tissue to grow into porous implant.

Arterial traffic signal coordination model considering buses and social vehicles

Considering the difference in driving parameters of buses and social vehicles on the arterial,an arterial traffic signal coordination model that takes into account social vehicles and buses on the basis of the maximum bandwidth is proposed.By using the pre-set parameters of a common cycle,green/red duration and known parameters of bus dwell time distribution,link length and vehicle speed and solving the mixed-integer-linear programming and optimizing the signal offsets,the model obtains the signal control parameters of the green bands both of social vehicles and buses.Finally,taking Wangjiang Road in Hefei as an example,simulation and evaluation are carried out by VISSIM.The results show that the new model has 15.2%and 13.2%reduction in average person delay and number of stops,respectively,compared with the traditional coordinated control method.

A Property Based Approach for Simultaneous Process and Molecular Design

In this work, property clustering techniques and group contribution methods are combined to enable simultaneous consideration of process performance requirements and molecular property constraints. Using this methodology, the process design problem is solved to identify the property targets corresponding to the desired process performance. A significant advantage of the developed methodology is that for problems that can be satisfactorily described by only three properties, the process and molecular design problems can be simultaneously solved visually on a ternary diagram, irrespective of how many molecular fragments are included in the search space. On the ternary cluster diagram, the target properties are represented as individual points if given as discrete values or as a region if given as intervals. The structure and identity of candidate components is then identified by combining or ＂mixing＂ molecular fragments until the resulting properties match the targets.

ANALYSIS OF CELL-AVERAGING BASED DETECTORS FOR χ^2 FLUCTUATING TARGETS IN MULTITARGET ENVIRONMENTS

The χ^2 family of signal fluctuation distributions represents the main fluctuation models which most radar targets follow it in their reflections. This family can be categorized as fluctuation distribution with two degrees of freedom and those with four degrees of freedom. The first category represents all important class of fluctuation models which when illuminated by a coherent pulse train, return a train of fully correlated pulses （Swerling Ⅰ model） or fully decorrelated pulses （Swerling Ⅱ model）. The detection of this type of fluctuating targets is therefore of great importance. This paper is devoted to the analysis of Cell-Averaging （CA） based detectors for the case where the radar receiver noncoherently integrates M square-law detected pulses and the signal fluctuation obeys 2 statistics with two degrees of freedom. These detectors include the Mean-Of （MO）, the Greatest-Of （GO） and the Smallest-Of（SO） schemes. In these processors, the estimation of the noise power levels from the leading and the trailing reference windows is based on the CA technique. Exact formulas for the detection probabilities are derived, in the absence as well as in the presence of spurious targets. The primary and the secondary interfering targets are assumed to be fluctuating in accordance with the χ^2 fluctuation model with two degrees of freedom （SWI ＆ SWII）. The numerical results show that the MO version has the best homogeneous performance, the SO scheme has the best multiple-target performance, while the GO procedure does not offer any merits, neither in the absence nor in the presence of outlying targets.

Modeling and optimization methods of integrated production planning for steel plate mill with flexible customization

With diversified requirements and varying manufacturing environments, the optimal production planning for a steel mill becomes more flexible and complicated. The flexibility provides operators with auxiliary requirements through an implementable integrated production planning. In this paper, a mixed-integer nonlinear programming(MINLP) model is proposed for the optimal planning that incorporates various manufacturing constraints and flexibility in a steel plate mill. Furthermore, two solution strategies are developed to overcome the weakness in solving the MINLP problem directly. The first one is to transform the original MINLP formulation to an approximate mixed integer linear programming using a classic linearization method. The second one is to decompose the original model using a branch-and-bound based iterative method. Computational experiments on various instances are presented in terms of the effectiveness and applicability. The result shows that the second method performs better in computational efforts and solution accuracy.

Strategic mining options optimization:Open pit mining, underground mining or both

Near-surface deposits that extend to considerable depths are often amenable to both open pit mining and/or underground mining. This paper investigates the strategy of mining options for an orebody using a Mixed Integer Linear Programming(MILP) optimization framework. The MILP formulation maximizes the Net Present Value(NPV) of the reserve when extracted with(i) open pit mining,(ii) underground mining, and(iii) concurrent open pit and underground mining. Comparatively, implementing open pit mining generates a higher NPV than underground mining. However considering the investment required for these mining options, underground mining generates a better return on investment than open pit mining. Also, in the concurrent open pit and underground mining scenario, the optimizer prefers extracting blocks using open pit mining. Although the underground mine could access ore sooner, the mining cost differential for open pit mining is more than compensated for by the discounting benefits associated with earlier underground mining.

Improved Mixed Integer Optimization Approach for Data Rectification with Gross Error Candidates

Mixed integer linear programming （MILP） approach for simultaneous gross error detection and data reconciliation has been proved as an efficient way to adjust process data with material, energy, and other balance constrains. But the efficiency will decrease significantly when this method is applled in a large-scale problem because there are too many binary variables involved. In this article, an improved method is proposed in order to gen- erate gross error candidates with reliability factors before data rectification. Candidates are used in the MILP objec- tive function to improve the efficiency and accuracy by reducing the number of binary variables and giving accurate weights for suspected gross errors candidates. Performance of this improved method is compared and discussed by applying the algorithm in a widely used industrial example.

Integrated Data Processing Method for GPS and INS Field Test over Rocky Mountain

The method of integrated data processing for GPS and INS(inertial navigation system) field test over the Rocky Mountains using the adaptive Kalman filtering technique is presented. On the basis of the known GPS outputs and the offset of GPS and INS, state equations and observations are designed to perform the calculation and improve the navigation accuracy. An example shows that with the method the reliable navigation parameters have been obtained.

PRINCIPLE,SOFTWARE AND EXPERIMENT OF GPS-SUPPORTED AEROTRIANGULATION

In conventional aerial photogrammetry, the high accurate photogrammetric point determination is always carried out by aerotriangulation using a great deal of ground control points around the perimeter and in the center of block area because the exterior orien- tation parameters of aerial photographs are unknown. A technological revolution in pho- togrammetry has taken place since Navstar global positioning system (GPS) was applied to determine the 3D coordinates of exposure station positions during the photo flight missions. GPS-supported aerotriangulation is conducted by a combined bundle adjustment for pho- togrammetric observations and the camera orientation data. In this case, the essential ground control points are replaced by GPS-determined camera positions. Recent investigations show this method is coming to the practice. We have been engaged in the theoretical studies, soft- ware development, and related experiments and production in the field since 1990. So far the abundant research achievements are obtained in terms of the theory and application. In this paper,we first derives the mathematical model of GPS-supported aerotriangulation from the geometry between camera and airborne GPS antenna, then describes briefly a software pack- age WuCAPS (Wuhan combined adjustment program system) developed newly by the au- thor,which serves the purpose of the combined bundle adjustment for photogrammetric and non-photogrammetric observations. At the end of the present work, a set of actual aerial pho- tographs,at the image scale of 1: 34 000, with airborne GPS data taken from Tianjing site, China were processed by WuCAPS. The empirical results have verified that the accuracy of the combined bundle adjustment with 4 XYZ ground control points around the corners of block area is very close to that of the conventional bundle adjustment with 3 additional pa- rameters, that leads to reduce 88% field survey and 75% production cost, and can meet the specification of topographic mapping at small or medium scale by GPS-supported aerotriangu- lation without ground control. This shows the ample applicability and the economic benefit of kinematic GPS relative positioning in high accurate photogrammetric point determination.

Modeling and Multi-objective Optimization of Refinery Hydrogen Network

The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming （MINLP）. A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.

Fabrication of titanium-based alloys with bioactive surface oxide layer as biomedical implants:Opportunity and challenges

Titanium and its alloys have long been used as implant materials due to their outstanding mechanical properties and apparent biocompatibility.Despite this,the search for better alloys has continued to be active by researchers and industries alike,as there are still pressing issues that require attention.These include(1)a large mismatch in the elastic modulus of the implant material,which causes a stress shielding problem;(2)the release of harmful ions from Ti alloys after long-term use;(3)a low bioactivity of the Ti alloy surface,which prolongs the healing process.More research has been directed toward finding new generation Ti alloys composed of more biocompatible phases and modifying the surface of Ti alloys from naturally bio-inert to bioactive in order to circumvent the problems.This review examines recent work reported on the fabrication of Ti alloys,and based on the survey,major characteristics highlighted the importance of elastic modulus and the use of non-toxic metal elements to improve biocompatibility.In terms of surface modification of Ti alloys,numerous studies have found that a nano-scaled surface oxide layer grown on the surface is always beneficial to improving the bioactivity of Ti alloys for rapid recovery after implantation.This comprehensive review focuses on the appropriate phase and composition for new Ti alloys intended for use as biomedical implants,emphasizing both fabrication and surface modification methods.

Improved Hybrid Differential Evolution-Estimation of Distribution Algorithm with Feasibility Rules for NLP/MINLP Engineering Optimization Problems

In this paper, an improved hybrid differential evolution-estimation of distribution algorithm (IHDE-EDA) is proposed for nonlinear programming (NLP) and mixed integer nonlinear programming (MINLP) models in engineering optimization fields. In order to improve the global searching ability and convergence speed, IHDE-EDA takes full advantage of differential information and global statistical information extracted respectively from differential evolution algorithm and annealing mechanism-embedded estimation of distribution algorithm. Moreover, the feasibility rules are used to handle constraints, which do not require additional parameters and can guide the population to the feasible region quickly. The effectiveness of hybridization mechanism of IHDE-EDA is first discussed, and then simulation and comparison based on three benchmark problems demonstrate the efficiency, accuracy and robustness of IHDE-EDA. Finally, optimization on an industrial-size scheduling of two-pipeline crude oil blending problem shows the practical applicability of IHDE-EDA.

Modeling and optimization for oil well production scheduling

In this paper,an oil well production scheduling problem for the light load oil well during petroleum field exploitation was studied.The oil well production scheduling was to determine the turn on/off status and oil flow rates of the wells in a given oil reservoir,subject to a number of constraints such as minimum up/down time limits and well grouping.The problem was formulated as a mixed integer nonlinear programming model that minimized the total production operating cost and start-up cost.Due to the NP-hardness of the problem,an improved particle swarm optimization(PSO) algorithm with a new velocity updating formula was developed to solve the problem approximately.Computational experiments on randomly generated instances were carried out to evaluate the performance of the model and the algorithm's effectiveness.Compared with the commercial solver CPLEX,the improved PSO can obtain high-quality schedules within a much shorter running time for all the instances.

Thermodynamic design of a cascade refrigeration system of liquefied natural gas by applying mixed integer non-linear programming

Liquefied natural gas(LNG) is the most economical way of transporting natural gas(NG) over long distances. Liquefaction of NG using vapor compression refrigeration system requires high operating and capital cost. Due to lack of systematic design methods for multistage refrigeration cycles, conventional approaches to determine optimal cycle are largely trial-and-error. In this paper a novel mixed integer non-linear programming(MINLP)model is introduced to select optimal synthesis of refrigeration systems to reduce both operating and capital costs of an LNG plant. Better conceptual understanding of design improvement is illustrated on composite curve(CC) and exergetic grand composite curve(EGCC) of pinch analysis diagrams. In this method a superstructure representation of complex refrigeration system is developed to select and optimize key decision variables in refrigeration cycles(i.e. partition temperature, compression configuration, refrigeration features, refrigerant flow rate and economic trade-off). Based on this method a program(LNG-Pro) is developed which integrates VBA,Refprop and Excel MINLP Solver to automate the methodology. Design procedure is applied on a sample LNG plant to illustrate advantages of using this method which shows a 3.3% reduction in total shaft work consumption.