让学生在真实情景中自然表达——《Spare Time》教学案例

进入21世纪,我国基础教育信息化得以蓬勃发展,但一直以来的粗放式发展模式,导致教育信息化建设陷入“大投入没有大产出,高投资没有高效益”的尴尬境地。在应用层面,表面热闹的课程整合也一直没能走向深入,虽然新技术不断涌现并进入教育领域,但到目前为止,这些新技术的应用并没有为基础教育改革带来人们所热切期望的效果和效益。教育工作者们开始对现有的教育理论和教育实践方法进行反思。本刊在2005年11、12两期连载了何克抗教授的《基础教育跨越式发展创新实验》,在中小学教育实践领域中引起了强烈反响。何克抗教授提出的儿童思维发展新论、语觉论、双主教学结构理论等,从一个全新的角度揭示了学生思维发展的规律和可能潜藏的巨大的学习能力,为信息技术与学科教学进行深层次的整合奠定了新的理论基础。可以认为,这有可能成为信息技术促进教学发展,实现基础教育跨越式发展的一个有效的突破口。经历了5年的探索,“基础教育跨越式发展创新实验”项目在全国10多个实验区110所实验学校已经开始显现出良好的效果,得到实验区学校、教师、家长和教育行政部门的认可。为让关注该项目的教育工作者对其进展和效果有更深入、更全面的了解,本期我们邀请课题组专家详细介绍该项目的实施策略、保障措施及最新的实验结果,并选择语文、英语教学案例各2篇,供读者借鉴。

Joint optimization of LORA and spares stocks considering corrective maintenance time

Level of repair analysis（LORA） is an important method of maintenance decision for establishing systems of operation and maintenance in the equipment development period. Currently, the research on equipment of repair level focuses on economic analysis models which are used to optimize costs and rarely considers the maintenance time required by the implementation of the maintenance program. In fact, as to the system requiring high mission complete success, the maintenance time is an important factor which has a great influence on the availability of equipment systems. Considering the relationship between the maintenance time and the spares stocks level, it is obvious that there are contradictions between the maintenance time and the cost. In order to balance these two factors, it is necessary to build an optimization LORA model. To this end, the maintenance time representing performance characteristic is introduced, and on the basis of spares stocks which is traditionally regarded as a decision variable, a decision variable of repair level is added, and a multi-echelon multiindenture（MEMI） optimization LORA model is built which takes the best cost-effectiveness ratio as the criterion, the expected number of backorder（EBO） as the objective function and the cost as the constraint. Besides, the paper designs a convex programming algorithm of multi-variable for the optimization model, provides solutions to the non-convex objective function and methods for improving the efficiency of the algorithm. The method provided in this paper is proved to be credible and effective according to the numerical example and the simulation result.

Collaborative optimization of maintenance and spare ordering of continuously degrading systems

A collaborative optimization model for maintenance and spare ordering of a single-unit degrading system is proposed in this paper based on the continuous detection. A gamma distribution is used to model the material degradation. The degrading decrement after the imperfect maintenance action is assumed as a random variable normal distribution. This model aims to ob- tain the optimal maintenance policy and spare ordering point with the expected cost rate within system lifecycle as the optimization objective. The rationality and feasibility of the model are proved through a numerical example.

Mission-oriented dynamic optimization model of carrying spares for warship redundant system

Redundancy is a common structure for warship system,and it is an effective way to improve the reliability of the system.In this paper, warship system is taken as the object of study,based on the system reliability equivalence principle, a spares demand rate calculation method for redundant system is proposed through structure transformation. According to the system analysis method, the general modeling data structure of spares support echelon and system indenture is established, and the mission success probability is taken as the optimization target to build the dynamic optimization model of carrying spares during the process of multi-phase. By introducing the Lagrange multiplier, the spares weight, volume and cost are transformed to the single target of the spares total scale, and the initial Lagrange factors and its dynamic adjustment policy is proposed. In a given example, the main influence factors of the carrying spares project are analyzed, and the study results are in accordance with the reality, which can provide a new approach to mission-oriented carrying spares optimization for the redundant system.

System optimization-oriented spare parts dynamic configuration model for multi-echelon multi-indenture system

In order to optimize the spares configuration project at different stages during the life cycle, the factor of time is considered to relax the assumption of the spares steady demand in multi-echelon technique for recoverable item control (METRIC) theory. According to the method of systems analysis, the dynamic palm theorem is introduced to establish the prediction model of the spares demand rate, and its main influence factors are analyzed, based on which, the spares support effectiveness evaluation index system is studied, and the system optimization-oriented spares dynamic configuration method for multi-echelon multi-indenture system is proposed. Through the analysis of the optimization algorithm, the layered marginal algorithm is designed to improve the model calculation efficiency. In a given example, the multi-stage spares configuration project during its life cycle is gotten, the research result conforms to the actual status, and it can provide a new way for the spares dynamic optimization.

Joint optimization of maintenance inspection and spare provisioning for aircraft deteriorating parts

With the wide application of condition based maintenance(CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircraft operational cost, is receiving increasing attention. In order to optimize the inspection interval, maintenance decision and spare provisioning together for aircraft deteriorating parts, firstly, a joint inventory management strategy is presented, then, a joint optimization of maintenance inspection and spare provisioning for aircraft parts subject to the Wiener degradation process is proposed based on the strategy.Secondly, a combination of the genetic algorithm(GA) and the Monte Carol method is developed to minimize the total cost rate.Finally, a case study is conducted and the proposed joint optimization model is compared with the existing optimization model and the airline real case. The results demonstrate that the proposed model is more beneficial and effective. In addition, the sensitivity analysis of the proposed model shows that the lead time has higher influence on the optimal results than the urgent order cost and the corrective maintenance cost, which is consistent with the actual situation of aircraft maintenance practices and inventory management.

A General Repairable Spare Part Demand Model Based on Quasi Birth and Death Process

This paper aims at two problems which exist in most of repairable spare part demand models at present: the exponential distribution as the basic assumption and one typical distribution corresponding to a model. A general repairable spare part demand model built on quasi birth-and-death process is developed. This model assumes that both the operational time of the unit and the maintenance time of the unit follow the continuous time phase type distributions. The first passage time distribution to be out of spares, the first mean time to be out of spares, and an algorithm to get the minimal amount of spares under certain restrictions are obtained. At the end of this paper, a numerical example is given.

Proteomic analysis of the dorsal spinal cord in the mouse model of spared nerve injury-induced neuropathic pain

Peripheral nerve injury often causes neuropathic pain and is associated with changes in the expression of numerous proteins in the dorsal horn of the spinal cord. To date, proteomic analysis method has been used to simultaneously analyze hundreds or thousands of proteins differentially expressed in the dorsal horn of the spinal cord in rats or dorsal root ganglion of rats with certain type of peripheral nerve injury. However, a proteomic study using a mouse model of neuropathic pain could be attempted because of abundant protein database and the availability of transgenic mice. In this study, whole proteins were extracted from the ipsilateral dorsal half of the 4th-6th lumbar spinal cord in a mouse model of spared nerve injury（SNI）-induced neuropathic pain. In-gel digests of the proteins size-separated on a polyacrylamide gel were subjected to reverse-phase liquid-chromatography coupled with electrospray ionization ion trap tandem mass spectrometry（MS/MS）. After identifying proteins, the data were analyzed with subtractive proteomics using ProtAn, an in-house analytic program. Consequently, 15 downregulated and 35 upregulated proteins were identified in SNI mice. The identified proteins may contribute to the maintenance of neuropathic pain,and may provide new or valuable information in the discovery of new therapeutic targets for neuropathic pain.

Mission-Oriented Configuration Model of Aircraft Carrying Spares and Dynamic Optimization Policy

Spare parts are critical to scheduled maintenance and fault repair, and can directly affect the readiness and combat capability of equipment. Equipmentrs capacity of carrying spares is influenced by its storage space and scales, so it is necessary to consider economic factors, e.g. spares cost, as well as non-economic ones, such as spares volume, mass and scale, when optimizing spares configuration. Aiming at this problem, the optimization model based on multi-constraints for carrying spares is built by METRIC theory and system analysis. Through the introduction of Lagrange factors, the spares cost is transformed to shadow price, and the optimization method for carrying spares and the dynamic adjustment policy of Lagrange factors are proposed. The result of a given example is analyzed, and demonstrates that the proposed model can be optimized with all constraints, and the research can provide a new way for carrying spares optimization.

Location and allocation problem for spare parts depots on integrated logistics support

In equipment integrated logistics support(ILS), the supply capability of spare parts is a significant factor. There are lots of depots in the traditional support system, which makes too many redundant spare parts and causes high cost of support. Meanwhile,the inconsistency among depots makes it difficult to manage spare parts. With the development of information technology and transportation, the supply network has become more efficient. In order to further improve the efficiency of supply-support work and the availability of the equipment system, building a system of one centralized depot with multiple depots becomes an appropriate way.In this case, location selection of the depots including centralized depots and multiple depots becomes a top priority in the support system. This paper will focus on the location selection problem of centralized depots considering ILS factors. Unlike the common location selection problem, depots in ILS require a higher service level. Therefore, it becomes desperately necessary to take the high requirement of the mission into account while determining location of depots. Based on this, we raise an optimal depot location model. First, the expected transportation cost is calculated.Next, factors in ILS such as response time, availability and fill rate are analyzed for evaluating positions of open depots. Then, an optimization model of depot location is developed with the minimum expected cost of transportation as objective and ILS factors as constraints. Finally, a numerical case is studied to prove the validity of the model by using the genetic algorithm. Results show that depot location obtained by this model can guarantee the effectiveness and capability of ILS well.

Long-term treatment with PP2 after spinal cord injury resulted in functional locomotor recovery and increased spared tissue

The spinal cord has the ability to regenerate but the microenvironment generated after trauma reduces that capacity. An increase in Src family kinase （SFK） activity has been implicated in neuropathological conditions associated with central nervous system trauma. Therefore, we hypothesized that a decrease in SFK activation by a long-term treatment with 4-amino-5-（4- chlorophenyl）-7-（t-butyl）pyrazolo[3,4-d]pyramidine （PP2）, a selective SFK inhibitor, after spinal cord contusion with the New York University （NYU） impactor device would generate a permissive environment that improves axonal sprouting and/or behavioral activity. Results demonstrated that long-term blockade of SFK activation with PP2 increases locomotor activity at 7, 14, 21 and 28 days post-iniury in the Basso, Beattie, and Bresnahan open field test, round and square beam crossing tests. In addition, an increase in white matter spared tissue and serotonin fiber density was observed in animals treated with PP2. However, blockade of SFK activity did not change the astrocytic response or infiltration of cells from the immune system at 28 days post-injury. Moreover, a reduced SFK activity with PP2 diminished Ephexin （a guanine nudeotide exchange factor） phosphorylation in the acute phase （4 days post-injury） after trauma. Together, these findings suggest a potential role of SFK in the regulation of spared tissue and/or axonal outgrowth that may result in functional locomotor recovery during the pathophysiology generated after spinal cord injury. Our study also points out that ephexinl phosphorylation （activation） by SFK action may be involved in the repulsive microenvironment generated after spinal cord injury.

An Optimal Replacement Policy for a System with Finite Spares

This paper develops a new replacement policy for a system with multiple spare units.An optimal replacement period is determined by maximizing the mean time to failure of the system.We show that there exists a finite and unique optimal replacement period T for units with strictly increasing failure rates. We also proof that the optimal repIacement period for a system with spares is decreasing in k. Furthermore, an algorithm is presented to get the optimal replacement period and a numerical example is given to illustrate the result. with strictly

STUDY ON POWER SPARE COEFFICIENT OF ELECTRICAL MOTOR IN LARGE PUMP STATION BASED ON RELIABILITY

Characters of head of low head pump station and the pump shaft power areanalyzed. Influence of each single factor on pump shaft power is expressed as change of specificshaft power. (non-dimensional) and the probability density function is determined. Influences ofmultiple factors on pump shaft power are analyzed. Method of calculating none over-loadedprobability of motor by integration by successive reductions is put forward and then relationbetween power spare coefficient and none over-loaded reliability of electric motor is established.Influences of all factors on pump shaft power being considered completely; power spare coefficientsof motor are calculated in three kinds of heads (changing and unchanging), two kinds of dirty-outconditions. Electrical motor power spare coefficients should be chosen as 1.20 approx 1.44, 1.11approx 1.19, 1.09 approx.14 respectively when pump heads are 4, 7, 9.5 m. The results mean much toreasonable choose of electrical motors in large pump stations, increasing reliability of pump unitsand saving equipment investment.

Spare Parts Demand Forecasting:a Review

Spare parts are very common in industry and military fields, and the investigations of spare parts demand forecasting methods have draws much attention in recent years. However,to the best of our knowledge,only few papers reviewed the forecasting papers systematically. This paper is an attempt to provide a novel and comprehensive view to summarize these methods. A new framework was proposed to classify the demand forecasting methods into four categories,including empirical methods,methods based on historical data,analytical methods and simulation methods. Some typical literatures related to each category were reviewed.Moreover, a general spare parts forecasting procedure was summarized and some evaluation criteria were presented. Finally,characteristics of different forecasting methods and some avenues for further research were illustrated. This work provides the managers with a systematical idea about the spare parts demand forecasting and it can be used in practical applications.

Research on Three-Echelon Inventory Model and Algorithm for Valuable Spare Parts in Weapon Equipment

According to the current situation of repair and supply for valuable spare parts in the weapon equipment of the PLA,using the research results of the repairable spare parts inventory theory,an inventory model of the valuable spare parts in three-echelon repair and supply system is established by expanding the classical METRIC model and theory,and the genetic algorithm is utilized to solve the model.In the algorithm,the chromosome representation and initial population production,the crossover and mutation operators are designed.By using an example,a simulation analysis is carried out to verify the model's correctness.

Study to Cost of Air Spares Support Based on IPSO

Air spares support is general term of using and repairing of aircrafts which is the material foundation of aero technical support, its effectiveness influences operational effectiveness and equipments of aircrafts directly. Based on particle swarm optimization algorithm, a new model is proposed to optimize the distribution of the cost of air spares, it take the funds as resource and the improvement of performance efficiency as objective and deduces the expressions to get the best distribution plan. The results of experiments indicate that this model can make full use of the limited funds and obtain the highest efficiency of air spares support.

Forecasting Spare Parts Demand Using Statistical Analysis

Spare parts are very essential in most industrial companies. They are characterized by their large number and their high impact on the companies’ operations whenever needed. Therefore companies tend to analyze their spare parts demand and try to estimate their future consumption. Nevertheless, they face difficulties in figuring out an optimal forecasting method that deals with the lumpy and intermittent demand of spare parts. In this paper, we performed a comparison between five forecasting methods based on three statistical tools;Mean squared error (MSE), mean absolute deviation (MAD) and mean error (ME), where the results showed close performance for all the methods associated with their optimal parameters and the frequency of the spare part demand. Therefore, we proposed to compare all the methods based on the tracking signal with the objective of minimizing the average number of out of controls. This approach was tested in a comparative study at a local paper mill company. Our findings showed that the application of the tracking signal approach helps companies to better select the optimal forecasting method and reduce forecast errors.

Inventory Management of a Plant Spare Parts Supply Chain

In spare parts industries, firms are dealing with a situation which is more and more uncertain due to the supply chain structure and variable demands. This paper presents a Bayesian approach to forecast demand and subsequently determine the appropriate parameter S of an （ S - 1 ; S） inventory system for controlling plant spare parts. We apply the Bayesian approach in an innovative way to specify the initial prior distributions of the failure rates, using the initial estimates and the failure history of similar items. According to the proposed method, a lower base stock than the one currently used is sufficient to achieve the desired service level.

New Approach to Calculate the Unavailability of Identical Spares in Cold Spare Configuration

Cold spare is the most common configuration amongst the three types of configuration for systems used on board and for power generation systems. A new approach to calculate the unavailability of systems composed of identical spares in cold spare configuration was proposed in this study. Instead of using the spare gate of dynamic fault tree( DFT) and the Markov analysis,AND gate of static fault tree used for calculating the unavailability of cold spare systems was proposed in this paper. By using this approach,unavailability of identical cold spare systems composed of nonrepairable spare components can be calculated exactly and systems composed of both repairable and nonreparable identical spare components can be estimated without building large Markov state diagram.

Prioritizing Maintenance Spare Parts Based on Supportability Analysis and Neural Network

In order to facilitate spare parts management,an integrated approach of BP neural network and supportability analysis(SA)was proposed to evaluate the criticality of spare parts as well as to prioritize spare parts.Influential factors of prioritizing spare parts were detailedly analyzed.Framework of the integrated method was established.The modelling process based on BP neural network was presented.As the input of the neural network,the values of influential factors were determined by supportability analysis data.Based on the presented method,spare parts could be automatically prioritized after supportability analysis for a new system.A case study results showed that the new method was applicable and effective.