Cécile Daversin

Christophe Prudhomme

Christophe Trophime

Full 3D MultiPhysics Model of High Field PolyHelices Magnets

Keywords: Magnets, Magnetic fields, Multi-physics Analysis

High field Resistive magnets for static field developed at the Laboratoire National des Champs Magnétiques Intenses (LNCMI) are based on the so-called polyhelix technique. Their design relies on non-linear 3D multi-physic models. As the user demands for higher magnetic field or specific field profile are growing we have to revisit our numerical models. They need to include more physics and more precise geometry. In this context we have rewritten our numerical model in the frame of a collaboration with Institut de Recherche en Mathématique Avancée (IRMA). New models have been implemented with the finite element library Feel++. This paper gives a status of these developments and the new features available. Results are presented for a 14 polyhelices insert targeting 36 Tesla in a 34 mm bore.

I. INTRODUCTION

The LNCMI is a French large scale facility [START_REF] Bard | The french high magnetic field facility[END_REF] enabling researchers to perform experiments in the highest possible magnetic field. DC magnetic fields up to 36 T are provided at the Grenoble site and pulsed fields up to 90 T at Toulouse. The technology used for DC magnets relies on the so-called polyhelix inserts for the most stressed parts of the magnets [START_REF] Debray | Dc high field magnets at the lncmi[END_REF]. To design efficiently such magnet multi-physic models are mandatory.

A common practice in magnets design consists in using several commercial software, each of them dedicated to a specific physic, to deal with the coupled phenomena involved. On top of these codes, several homemade software have to be developed to ensure the actual coupling either for the meshes used either for the input data to be exchanged between models. Such a magnet design process may be found in [START_REF] Toth | Fea-aided design for a working model of a split florida-helix[END_REF].

To avoid the burden of writing and maintaining dedicated interfaces or scripts to glue several software together, more integrated approach may be considered using general purpose finite element codes (eg. Ansys, Comsol). But still this approach may also exhibits some limits especially when meshing the magnet geometry provided by some CAD software.

At the light of these observations, we have decided to rework our design process [START_REF] Trophime | Magnet calculations at the grenoble high magnetic field laboratory[END_REF] by using a single software based on modules dedicated each to a specific physic. The data needed to ensure the couplings are integrated within the software. The developments have been carried in the frame of a collaboration with IRMA from University of Strasbourg using their Finite Element library Feel++ (www.feelpp.org) [START_REF] Prud'homme | A domain specific embedded language in C++ for automatic differentiation, projection, integration and variational formulations[END_REF]. As for the meshes they are obtained from a geometry built with OpenSalome CAD/CAE platform [START_REF] Ribes | Salome platform component model for numerical simulation[END_REF] which greatly eases this step thanks to its Python interface. This approach is quite similar to the one developed in [START_REF] Nunio | Salome as a platform for magneto-mechanical simulation[END_REF].

In this paper we present in more details our approach. We illustrate the progress achieved with the study of a polyhelix resistive insert planed to be operated in the future hybrid magnet [START_REF] Pugnat | Progress report on the 43 t hybrid magnet of the lncmi-grenoble[END_REF]. Finally, we demonstrate the possibility offered by Reduced Order Methods in this context to perform uncertainty quantification in our design. This work enjoys the Reduced Basis framework available in Feel++ library.

II. APPROACH

As mentioned in [START_REF] Nunio | Salome as a platform for magneto-mechanical simulation[END_REF] the design and optimization of magnets is an iterative process that involves numerical multiphysics modeling, namely eletromagnetics, thermics and mechanics. In the case of resistive magnets we also have to consider thermo-hydraulics as our magnets are water cooled. This aspect is treated with standard Colburn correlation that won't be detailed in the sequel. The heat exchange between water and resistive magnet is governed by forced convection. This is modeled by adding a boundary condition on the water flux, depending on heat transfer coefficient and water temperature.

This process always starts with some initial guessed magnet geometries provided by some optimization procedure. In our case the initial polyhelix magnet geometry, made of concentric copper alloy tubes, is derived from an optimization of the current density distribution in each tube based on an axisymetrical semi-analytical model [START_REF] Trophime | Magnetic field homogeneity optimization of the giga-nmr resistive insert[END_REF]. This procedure actually provides the helical path for each tube which will be cut by electro discharge machine. The cut is then either filled with a mix of glass spheres and epoxy glue to produce "longitudinally cooled helix", either let free with the exceptions of insulators disposed at regular angles to produce "radially cooled helix" (for details see [START_REF] Debray | Dc high field magnets at the lncmi[END_REF]).

Once the helical path is determined, an automatic procedure may be derived to create the actual helix CAD geometry. Thanks to its Python interface, this operation may be carried out without human interaction within Salome. However special care has to be taken to properly define interfaces between copper and insulators in case of radially cooled helices. This is mandatory to have conformal meshes with may also be built via the Python interface. In our experience we only manage to have this CAD and Meshing steps using Salome. On fig. 1 given a CAD view of a 14 helices resistive insert with current leads. The whole insert geometry is automatically generated with Python scripts. This allows to easily take into account some geometric parameters if ever needed during the design process. At this point we can perform simulations using our numerical models.

is

Our model is splitted into 3 modules which can be coupled at will in the main software. The configuration of this coupling can be easily managed by users from a configuration file, without any act on the code itself. The Electro-Thermal model computes the electrical potential V and the temperature field T by solving a set of two non-linear PDEs as the physical properties of the copper alloys are temperature dependent. The Elasticity module computes the displacements and stresses (Tresca, Von-Mises) from both thermal dilatation and Lorentz forces by solving the linear elasticity equation. Finally the Magnetostatic module computes the magnetic vector potential and the induction field B, often abusively referred as the magnetic field H. The computation of B field in the region of interest for the researchers from the current distribution j = -σ(T )∇V is also provided, based on the Biot and Savart's law.

These modules have been developed with Feel++. This stands for Finite Element Embedded Language in C++ (see www.feelpp.org). The formalism behind Finite Element Method, variational formulations, is embedded into C++. This way we can reduce the semantic gap between mathematics and the code. The library enables user to perform simulations with both high order finite elements and high order meshes. It is interfaced with large scale parallel linear and non-linear solvers, and enjoys seamless parallel computing possibilities enabling use from workstation to supercomputers without changes. Owning to these features, our modules may benefits to state of the art techniques and most important can be easily port and use on parallel computers. This is an important point in the perspective of magnet design. Indeed the higher magnetic field we are trying to reach, the more detailed analysis we need. This implies to consider more physics and more precise geometrical modeling in our simulation. Consequently it leads to large scale problems, with costly systems. The results are displayed on fig. 2a to 2c. As expected the maximum temperature is reached in the innermost helices. The maximum Von-Mises stress is obtained in the intermediate helices and reaches 510 Mpa. The displacements are about 0.7 mm for the outermost helices. This values correspond to a field of 44.5 Tesla which fulfill our requirements for the Hybrid magnet to be operational in 2018.

To validate our models we have also run simulations on existing polyhelices insert. As the experimental data are very limited we have restricted ourselves to the comparison of B along the central axis of the insert. Measures were performed with a pick-up coil, calculations were carried out using the semi-analytical expression from the optimization procedure and with our 3D Biot-Savart parallel implementation in the Magnetostatic module. The results show a great agreement between the measures and the calculations. A detailed analysis shows that with our 3D Biot-Savart we have a more precise view on B. The error at the vicinity of the entrance and exit of the magnet is improved by a factor 2 (see fig. 3).

IV. TOWARDS A ROBUST DESIGN

In the previous paragraph the status of our models was illustrated on a concrete example. However during a classical design process we would like to run such kind of simulations to explore some parametric space, for instance to evaluate the impacts of some parameters either geometric or physical. Moreover we would like to be able to evaluate the impact of some uncertainties, for instance on material physical properties on some quantities of interest, such as the magnetic field at some given points, the mean temperature of the magnet, or the total power.

A lot of simulations would then be required to explore this parametric space and to address these questions. Even if we have some quite efficient tools the computational cost associated may become rapidly unaffordable. Fortunately Feel++ provides a Reduced Basis Method framework [START_REF] Daversin | A reduced basis framework: Application to large scale nonlinear multi-physics problems[END_REF] that can tackle this kind of situations.

From a naive point of view, Reduced Basis Method [START_REF] Prud'homme | Reliable real-time solution of parametrized partial differential equations: Reduced-basis output bound methods[END_REF] may be seen as a kind of interpolation for the Finite Element method. The idea consists in making a smart selection of some points in the parameter space and performing the associated finite element approximations. The Reduced Basis approximation for any set of parameters then reads as a linear combination of these previously computed and stored solutions -the so-called reduced basis.

Whereas the first step -selecting and computing some finite element solutions -often referred as the offline step is time consuming, the second one -the interpolation of the reduced solution -referred as the online step is very light in comparison since the associated system to solve has a greatly reduced size -from 10 to 100 basically, compared with few million. As an application of the reduced basis method, we will consider a radially cooled helix. This kind of helices -better cooled than the longitudinal ones -are foreseen to replace the innermost helices of the resistive polyhelices insert which are mostly thermally limited. In this context we investigate the mean temperature in such an helix in the actual range of parameters representative of nominal operating conditions with an current intensity around 31kA :

h ∈ [70000; 90000](W.m -2 .K -1 ) T w ∈ [293, 313](K)
We have also considered some uncertainties on the copper physical properties : the electrical conductivity is of the form σ = σ 0 /(1 + α(T -T 0 ) and the thermal conductivity is given by the Wiedemann-Frantz law k = LσT : σ 0 ∈ [50.10 6 ; 50, 2.10 6 ](S.m -1 ) α ∈ [3, 3.10 -3 ; 3, 5.10 -3 ](K -1 ) L ∈ [2, 5.10 -8 ; 2, 9.10 -8 ]

For this example we have used a set of 10 reduced basis. Once the basis are computed, the evaluation of a solution is about 150 faster than solving the finite element problem. Evaluations of the mean temperature has been performed on a set a 300 samples of the parameter spaces. This allows the use of openturns [START_REF] Dutfoy | OpenTURNS, an Open Source initiative to Treat Uncertainties, Risks'N Statistics in a structured industrial approach[END_REF] to perform some statistics on the results. The interested reader can find more details about implementation in [START_REF] Daversin | A reduced basis framework: Application to large scale nonlinear multi-physics problems[END_REF].

For this parameter space, the "mean" temperature is 95 • C with an standard deviation of 6.2 • C. With this analysis we may also have access to quantiles, that is, value of the mean temperature that may not be exceed at a given probability. In the present case, we show that the mean temperature may not exceed 107 • C at 99%. These quantiles may be useful to set up tighter bounds on the threshold for the magnet control system. In addition we also have access to the Sobol indices (see fig 5 which represents the influence of the parameters on the output, here the mean temperature. From a practical engineering point of view the Sobol indices provide some guidelines on which parameters should acted upon to improve the target output. In this case, the most influential parameter turns out to be the water temperature.

V. CONCLUSION AND PERSPECTIVES

The design of magnets at the LNCMI, beside the initial optimization step, have been reworked from scratch in the frame of a collaboration with IRMA using their state of the art finite element library Feel++. Combined with the automation of CAD/Meshing procedure introduced using Salome platform Python interface we have set the first steps towards a software toolchain dedicated to resistive high field magnets. Following a similar approach to [START_REF] Nunio | Salome as a platform for magneto-mechanical simulation[END_REF] we plan to integrate more tightly our numerical models with Salome. Thus doing we will have a complete and integrate software with user-friendly GUI facilities which may be used routinely in a R & D context.

Our choice to base our design and optimization tools on Feel++ and Salome has been illustrated on the study resistive polyhelices. Since these two software are opensource we can easily port and use our toolchain on parallel computers at moderate cost compared to commercial solutions. Finally Feel++ permits to envision the development of more robust design by using its reduced basis method framework to perform sensitivity analysis and uncertainties quantifications like in the last example.

In parallel to these developments we will improve our models by adding some more physics in it -especially to account for the non-linearity in the elasticity model and to have better insights of the cooling flow and heat exchange. We are also enriching our reduced Electro-thermal model, to go towards a multi-physics reduced model including magnetostatics and mechanics. From associated quantities of interest, this will provide further uncertainty quantification to be used in optimization process.

Fig. 1 .

 1 Fig. 1. A 14 Helices resistive insert with current leads

Fig. 2 .

 2 Fig. 2. Displacements and stress

Fig. 3 .

 3 Fig. 3. Comparison of the profile of B vs the experimental data along z axis obtained by 2D axi B (from optimization step) calculations

Fig. 4 .

 4 Fig. 4. Temperature in K within a radially cooled helix with a zoom of on insulators in the central zone.

Fig. 5 .

 5 Fig. 5. Sensitivity indices (Sobol) for the mean temperature. Only the most significant ones have been plotted.

ACKNOWLEDGMENT

The authors acknowledge PRACE for awarding us access to Curie supercomputer based in France at TGCC. We also acknowledge the French Research Agency which support this work through the project CHORUS as well as the Labex IRMIA.


Liying Cao

Chunan Li

Guifen Chen
email: guifchen@163.com

Lixia Cai

Hang Chen
email: cchenhang@163.com

Analysis and Evaluation of Soil Fertility Status Based on Weighted K-means Clustering Algorithm

Keywords: AHP, Weighted K-means clustering, Optimal classification, Soil fertility evaluation

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

3S technology (GPS, GIS and RS), networking technology and expert system (ES) technology are widely used in precision agriculture with the rapid development of information technology. That all make soil fertility data appear to rich, multidimensional, dynamic, incomplete, uncertainty and other characteristics [START_REF] Turner | Land use and land cover in global environmental change:considerations for study[END_REF] .How to be more timely and accurately show the differences in temporal and spatial data, comprehensive evaluation and correct analysis of the data have an important practical significance [START_REF] Li | Application of Clustering Analysis in Classifying Site Type and Evaluating Soil Fertility[END_REF] . Data mining technology [START_REF] Amirmahdi | A Survey on Data Mining Approaches[END_REF] is the process of generating new regular, which through the massive amounts of data classification, extraction to discover the mutual contact between data.

Related data show that variable region and the traditional region of N, P, K nutrient variation coefficients in soil fertilization were compared by ZHANG. Which indicate that variable rate fertilization has a balanced effect to soil nutrient fertilization [START_REF] Zhao Jiewen | Application of Support Vector Machine to apple classification with near-infrared spectroscopy[END_REF] . The research on weighted space fuzzy dynamic clustering algorithm by CHEN Gui-fen, proved the effectiveness of soil fertility evaluation [START_REF] Chen Gui-Fen | Application of Weighted Spatially Fuzzy Dynamic Clustering Algorithm in Evaluation of Soil Fertility[J][END_REF] . And Li Yan.etc. [START_REF] Li | Definition of management zones based on fuzzy clustering analysis in coastal saline land[J][END_REF] Who used fuzzy clustering method to classify partition and introduced two kinds of partitions to compare and evaluate, such as fuzzy clustering index and normalized classification. That can offer the decision basis for soil management. Even K-means clustering algorithm based on the classification method could differentiate soil fertility according to soil nutrient, However, it can't consider the nutrient differences between each attribute. As a result, we use the improved K-means algorithm, considering the linkages between soil nutrients of the fertility in Nong'an country [START_REF] Yang | Comparisons of uniform and variable rate nitrogen and phosphorus fertilizer applications for grain sorghum[END_REF] and give a comprehensive evaluation.

Analysis of k-means algorithm

K-Means algorithm is a clustering algorithm based on partitioning method [START_REF] Sun Ji-Gui | Clustering Algorithms Research[END_REF][START_REF] Yang | Comparisons of uniform and variable rate nitrogen and phosphorus fertilizer applications for grain sorghum[END_REF][START_REF] Umeda | Effect of variable rate fertilizing for paddy field[END_REF][START_REF] Wittry | Comparison of uniform-and variable-rate phosphorus fertilization for corn-soybean rotations[END_REF][START_REF] Li | Application of Clustering Analysis in Classifying Site Type and Evaluating Soil Fertility[END_REF][START_REF] Chawan | Improvement of K-Means clustering Algorithm[END_REF][START_REF] Yuxia | K-means clustering analysis based on genetic algorithm[END_REF][START_REF] Backer | A clustering performance measure based on fuzzy set decomposition[END_REF][START_REF] Zahn | Graph2theoreticalmethods for detecting and describing gestalt clusters[END_REF][START_REF] Tan Yong | Implementation of A Clustering Algorithm Based on High Density[END_REF][START_REF] Leung | Personalized Concept-based Clustering of Search Engine Queries[END_REF] , it is first suggested and one of the more classical clustering algorithms [START_REF] Backer | A clustering performance measure based on fuzzy set decomposition[END_REF][START_REF] Zahn | Graph2theoreticalmethods for detecting and describing gestalt clusters[END_REF] . [START_REF] Shibao | Improved k -average clustering algorithm research[END_REF] Algorithms: k-means. Divided k-means algorithm based on the average value of the objects in the cluster.

The process of K-means algorithm

Input: the number of clusters (k) and the database contains n objects.

Output: k clusters, so that the minimum squared error criterion.

Method:

(1) Choose k objects as the initial cluster centers;

(2) Repeat;

(3)According to the average value of the objects in the cluster, each object is (re) assigned to the most similar clusters;

(4)Update the average value of cluster. That is to say, calculate the average value of each cluster in the object;

(5) Until no change.

Advantages and disadvantages of k-means algorithm

Using k-means algorithm [START_REF] Chawan | Improvement of K-Means clustering Algorithm[END_REF] to clustering, the effect is good. While the result is a dense cluster, the differences between clusters are obvious. When we deal with large data sets, this algorithm is relatively scalable and efficient, because of its complexity is O (nkt), where, n is the number of all objects, k is the number of clusters, t is the number of iterations. Typically k«n and t«n. This algorithm often ends with a local optimum. However, k-means method [START_REF] Yuxia | K-means clustering analysis based on genetic algorithm[END_REF][START_REF] Backer | A clustering performance measure based on fuzzy set decomposition[END_REF][START_REF] Zahn | Graph2theoreticalmethods for detecting and describing gestalt clusters[END_REF][START_REF] Tan Yong | Implementation of A Clustering Algorithm Based on High Density[END_REF][START_REF] Leung | Personalized Concept-based Clustering of Search Engine Queries[END_REF][START_REF] Xiaomei | Incremental -K Medoids clustering algorithm[END_REF] is only used in the case of the average value of clusters were defined. This attribute data is not applicable for processing symbol attribute data, it also requires user to give the value of k (the number of clusters to be generated) in advance. In addition, for the "noise" and outlier data is sensitive, a small amount of such data can have a significant impact on the average value.

Analysis of weighted k-means algorithm Based on AHP

Using AHP to determine the weight coefficients

The algorithm is as follows:

Step 1: Construct paired comparison matrix;

Step 2: Take any n-dimensional normalized initial vector

) 0 ( w ; Step 3: Calculation  , 2 , 1 , ~) ( ) 1 (    k k k Aw w ;
Step 4: Normalization

) 1 ( ~ k w ;
Step 5: For the pre-specified precision  , when

n , , i w w k i k i , 2 1 , ) ( ) 1 (       Established, ) 1 (
~ k w shall be eigenvector; otherwise return Step 2;

Step 6: Calculate the maximum eigenvalue

    n i k i k i w w n 1 ) ( ) 1 ( 1  ;
Step 7: Calculate consistency index

1    n n CI  ;
Step 8: Calculate consistency ratio

The establishment of the weighted k-means model

In this paper, we used the weighted fuzzy dynamic clustering approach to process spatial data, which is proposed by CHEN [START_REF] Chen Gui-Fen | Application of Weighted Spatially Fuzzy Dynamic Clustering Algorithm in Evaluation of Soil Fertility[J][END_REF] .

(1) Data's standardization

Since in practical problems, different data generally have different dimensions, in order to have the amount of different dimensions can be compared, we need to standardized data, which data are compressed to the [0, 1] interval. Now we use the range transformation,

} min{ } max{ } min{ ij j ij ij ij x xi x x x     (1)
(2) Weighted calculation Resulting in fuzzy similar matrix

                                                nm n n m m m nm n n m m y y y y y y y y y a a a x x x x x x x x x Y                    
n n ij r R   ) ( . 4
The application of weighted k-means algorithm

Data Sources

Application and research of soil fertility data after precision fertilization for many years [START_REF] Umeda | Effect of variable rate fertilizing for paddy field[END_REF][START_REF] Wittry | Comparison of uniform-and variable-rate phosphorus fertilization for corn-soybean rotations[END_REF] , which is based on the "863" plan --"research and application of corn 1. 2).

Second, the author use AHP to get the nutrient weights of soil alkaline hydrolysis nitrogen, available potassium, available phosphorus, three nutrient weights are 0.3782, 0.2032 and 0.4185. CI = 0.026420513 << 0.1, which is closer to the complete consistency. Then, compared with the classical k-mean clustering algorithm, the weighted K-means clustering algorithm has a significantly higher accuracy, and operational efficiency. We can see the results have shown in Table 2. the soil will offset the gap between the highest and lowest and delimit in the same class, while weighting the gap will be assigned to different classes, this method can reflect the real situation of soil nutrient. Weighted k-means for the "noise" and outlier data is not very sensitive; a small amount of this kind of data does not have great influence on the average value.

Finally, using the weighted k-means algorithm, weighted clustering the soil nutrient data of Nong'an town for five consecutive years from 2007 to 2011.

Experimental results as shown in Table 3 and Figure 3.

Fig. 3. Clustering results

The Table 3 and Figure 3 show that, in the same category case, the degree of similarity between the data is gathered and the differences between clusters are decreasing year by year after a continuous precise fertilization. The value of Cluster 0 decreased from 42% in 2007 to 13% in 2011, cluster 1 from 3% in 2007 years rose to 35% in 2010.All above shows that the weighted k-means algorithm is an effective method for soil fertility evaluation. After a continuous precise fertilization, alkaline hydrolysis nitrogen,available phosphorus and available potassium, the comprehensive similarity of three kinds of nutrient data have been improved year by year. The results tally with the actual situation, so weighted k-means algorithm is an effective method of fertility evaluation.

Results and Discussion

Analysis and evaluation of soil nutrient data by using weighted k-means algorithm. The data of Nong'an town for five consecutive years from 2007 to 2011.

We can see that significant changes in soil fertility occur after five consecutive years of precision fertilization. Experimental results show that the weighted k-means algorithm is an effective method of fertility evaluation.

(1)AHP is used to determine the initial weight values; the weighted original decentralized data can avoid the shortcomings that unweighted k-means algorithm does not distinguish between data imbalance between attributes as well as sensitive to "noise" and isolated points data .

(2)The use of weighted and unweighted k-means algorithm for comparative analysis soil nutrient data about soil alkaline hydrolysis N, available P and available K from Nong'an town in 2011, and the results showed that weighted K-means clustering algorithm has better effect than unweighted k-means algorithm, in the terms of accuracy which is increase1.88% and operating efficiency which is increase 25%.

(3)From the experimental results of the algorithm, after five consecutive years of precision fertilization on soil nutrient data in Nong'an town, Comprehensive similarity in increase year by year.This evaluation results and the actual situation is consistent, provides a new reference for analysis of soil fertility status in future.

The initialization of weighted and unweighted k-means clustering algorithm should depend on iterative method to determine the number of clusters that is relatively close to the true value and the initial center. However, this article only analysis verification of soil nutrient data that after five consecutive years of precision fertilization on soil nutrient data in Nong'an town. And the improved algorithm has not tested the application of large data sets or fully confirmed that the validity of new algorithm for massive data sets. How to simplify the clustering algorithm and combine with soil nutrient data of many years, more townships (towns) and soil types. They are all problems. So these parts still need further research.

( 3 )

 3 Fuzzy similar matrixCalculating Closeness ij r of fuzzy sets i and fuzzy sets j ,

1 :Fig. 1 .

 11 Fig. 1. GIS-based sampling points

4. 2 Fig. 2 .

 22 Fig. 2. Soil nutrient (N, P, K) spatial variation in Xi haolai, Nong'an town

Table 1 .

 1 Part of the sample data

	Town name	Alkaline hydrolysis (mg/kg) nitrogen	Available (mg/kg) phosphorus	Available (mg/kg) potassium	latitude	longitude
	Nong'an town	154.0	28.0	208.0	44.58417 125.2898
	Nong'an town	136.0	31.3	217.0	44.49895 125.2512
	Nong'an town	132.0	16.3	198.0	44.49926 125.2507
	Nong'an town	125.0	36.8	140.0	44.51392 125.2540

Table 2 .

 2 The comparison result

	Algorithm	Average accuracy (%)	Average running time(s)
	K-means	95.03	0.08
	K-Wmeans	96.91	0.06
	From table 2, the weighted and unweighted k-means both are better classification
	methods (the accuracy are 96.91%, 95.03% respectively, and the running times are
	0.06 s, 0.08 s respectively). When we use unweighted clustering, different nutrients in

Table 3 .

 3 The result of soil nutrient data weighted clustering

			2007		2008	2009		2010		2011
		Clust	Perce	Clust	Perce	Clus	Perce	Clust	Perce	Clust	Perce
		ered	ntage	ered	ntage	terd	ntage	ered	ntage	ered	ntage
		Data	(%)	Data	(%)	Data	(%)	Data	(%)	Data	(%)
	Clust er 0	310	42	247	33	161	22	198	27	99	13
	Clust er 1	26	3	257	35	126	17	254	34	235	32
	Clust er 2	225	30	194	26	234	31	151	20	134	18
	Clust er 3	183	25	46	6	223	30	141	19	276	37
			2007			2009				2011

Acknowledgment

This work was supported by the national -863‖ project (2006AA10A309), National Spark Plan (2008GA661003) and Shi Hang of Jilin province projects (2011-Z20).


Li Ma

Helong Yu

Guifen Chen

Liying Cao

Yue Wang

Research on the Construction and Implementation of Soil Fertility Knowledge Based on Ontology

Keywords: data mining, ontology, soil fertility, multi-Agent 1

Soil fertility is the comprehensive reflection of related factors and the related factors. Soil fertility evaluation knowledge is stored by relational database as usually, and it is difficult to show the correlation and constraints among attributes .In this paper, Nongan county farmland productivity data is as the research object, Using rough set approach to do attribute reduction, using ontology method to establish the soil fertility level knowledge base, using multi Agent technology to implement the prototype system, and complete the reuse and sharing of knowledge, lay the foundation for semantic level reasoning.

Introduction

The cultivated land fertility is integrated by soil characteristics, natural conditions and farm management and other elements of the productive capacity of cultivated land, is the comprehensive reflection of related factors and the influence of the nature of the soil properties [START_REF] Chen Gui-Fen | The combination of clustering and rough set and decision tree algorithm applied in the evaluation of soil fertility[END_REF][START_REF] Li | Research on Rough Set and Decision Tree Application in Evaluation of Soil Fertility Level[END_REF][START_REF] Jian | Clustering support decision tree model in the evaluation of cultivated land application[END_REF]. In soil fertility evaluation, the description of the knowledge and rules is mostly used relational database. And is less considering the relationship among properties of the soil, and there are no sound constraints on attributes, Can't describe the implicit relationships between concepts, Cannot carry out the sharing and reuse of the data, cause a large amount of data redundancy. Rough set can reduce the redundant attribute in database under the premise of guarantee the same classification and decision, simplify the knowledge representation, and improve the efficiency of system processing [START_REF] Huang | Development of soft computing and applications in agricultural and biological engineering[END_REF]. Ontology is a new method of data description, Can be a clear description of concept in concept level, and expression association and constraints between concepts [START_REF] Li | The Knowledge Representation and Semantic Reasoning Realization of Preductivity rade Based on Ontology and SWRL[END_REF].

In this paper, on the basis of the research of data mining and ontology technology, the cultivated land of NongAn of Jilin province is as the research object, make extraction and classification of the knowledge in the field, use of ontology technology for knowledge representation, Construct of soil fertility of ontology library, and realize knowledge sharing using Multi-agent Technology, present a new method for data storage.

2

The Research Data and Related Technologies

The Rough Set Theory

The rough set (RS) theory is a new mathematical tool which can process fuzzy and uncertainty knowledge, its characteristic is that it does not need to assign quantity descriptions of some characteristics and attributes in advance, starts from the description of given problems, discovers the inherent laws, its basic philosophy is closer to the realistic situation [START_REF] Guifen | For the spatial data mining technology research and application of precision agriculture[END_REF].

The basic philosophy of is rough set is that S=(U, A,{Va}, a) is called the knowledge expression system, and U is a non-spatial finite set,called the universe ; A is a non-spatial finite set, called attributes set; Va is the range of a∈A , a:U→Va is a injective maps. If A composes of condition attribute set C and conclusion attribute set D, C and D satisfy C∪D=A,C∩D=Φ, then S is called the decision system. In a decision system, the dependence or the connection are existence in certain degrees between each condition attribute, the reduce may be considered that under the premise of losing no information ,using simple description to express the dependence and connection between conclusion attributes to condition attributes in a decision system(Z.Pawlak , 1995). Indiscernibility relation ind

(C) divide U into t indiscernibility classes X1,X2,…,Xt, makes D(Xi) is a set of All values of conclusion attribute d of Xi, that is D(Xi)={v=d(x):x ∈ Xi}, if D( [ Xi ] ind(C-{a}))=D(Xi),
then said that the condition attribute a∈C can be removed compared with indiscernibility classes Xi. C′  C is called the reduce of C relative to indiscernibility classes Xi , if a∈C ', then a cannot be removed relative to Xi.All reduce sets compared with Xi is recorded SRED(C, Xi), Score(C,Xi)=∩SRED(C, Xi) is called core of Xi.

The Ontology

The concept of ontology is from the field of philosophy. In the 1960 s, computers started to use ontology. At present, the definition of ontology is a shared standard conceptual model explicit formal specification [START_REF] Xiaoyong | Ontology learning research review[END_REF]. As to how to use ontology to organize knowledge, Perez et al. summed up the 5 basic modeling primitives using classification: class, relation, function, the axiom and examples.

(1) classes or Concepts. Classes can be any transaction, such as job, function, behavior, strategies, and reasoning process, and so on. Semantically, the meaning of class is a collection of objects, Its definition generally adopts frame structure, including the name of a concept, with the rest of the concept of the relationship between the collections, as well as in natural language description of the concept, etc.

(2) relations. Formal definitions for the n dimension of a subset of the Cartesian product: R:C1×C2×…×Cn. For example, the subclass relationship (subclass-of), which represents the interaction between domain concepts.

(3) functions. Function is a kind of special relationship. The formal definition of F is C1×C2×…×Cn-1→Cn .The n element can be uniquely determined by n-1 elements before of the relationship, such as is-a is a function, is-a (m, n) means that n is an instance of m. (4) axioms. Axiom represents the eternal truth assert, is defined in the "concept" and "property" on the limit and rules, such as the concept of A belongs to the scope of the concept of B.

(5) the instance (instances). Instances represent elements. Semantically representation is the object, is a concrete entity refers to a concept class.

Construction of Soil Fertility Ontology

Attribute Reduction in Rough Set

This paper uses the genetic algorithm for attribute reduction, the process is: (1) A randomly generated population. (2) Evaluation of the merits of each chromosome, then choose the excellent chromosome, format a new species. (3) Operators (crossover and mutation) to the new population genetic, then get new specie. (4) Repeat the genetic operation chose the best chromosomes as a solution [START_REF] Guangcai | A kind of attribute reduction algorithm based on genetic algorithm[END_REF].

According to rough set theory, data set is divided into attribute set and decision set. Attribute set includes 24 attributes, those are soil humidity, groundwater depth, light radiation intensity, soil irrigation capacity, annual rainfall, soil drought resistance and soil erosion degree, soil texture, crop rotation suitability, topography, soil parent material, part into layer thickness, salt concentration, humus soil pH value, effective copper, iron, effective slowly available k, effective k, effective fierce, total nitrogen, phosphorus, organic matter and cationic content, effective zinc. Decision set contains 1 attributes that is fertility level.

Using genetic algorithms to do the reduction, attribute set contains soil humidity, groundwater depth, light radiation intensity, soil irrigation capacity, annual rainfall, soil drought resistance and soil erosion degree, soil texture, crop rotation suitability, topography, soil parent material, part into layer thickness, salt concentration, humus soil pH value, iron, effective slowly available k, effective k, total nitrogen, phosphorus, organic matter and cationic content, A total of 21 properties. Reduces 3 attributes including effective copper, effective fierce, effective zinc The decision set contains an attribute {soil fertility level}.

Construct The Soil Ontology

Using the seven step of ontology construction as the guidance, taking fertility evaluation based on the series of elements, Soil data based on the actual situation, according to the actual situation of the soil data, establishing the ontology classes and attributes. Soil ontology construction process is as follows:

Define classes and class rating system: (1)to establish the section and physical and chemical properties of physical attributes of, ph value, soil moisture, salt concentration, humus layer thickness, soil texture, cationic content and groundwater depth; (2)The site conditions, including attribute of site topography, soil erosion degree and parts into soil organic; (3)Meteorological conditions of weather, contain attributes rainfall and light radiation intensity; (4)Establish the nutrient content of nutrient, contain attributes effective iron, slowly available k, effective, total nitrogen, phosphorus, effective organic matter; (5) Establish the soil management class management, including attribute soil drought resistance, irrigation and crop rotation suitability; (6)Set up the soil, the soil as a kind of all kinds of the father; [START_REF] Xiaoyong | Ontology learning research review[END_REF]Established the kind of equipment, including productivity grade attributes.

Define a relationship class_is, used to determine a specific example belonging to which productivity grade, its domain of definition is soil, its range is class.

Fig.1. Ontology Construction

Multi -Agent technology with the development of distributed artificial intelligence can effectively solve the problem of distributed data integration. This paper uses the Agent oriented software development method , designs and develops data integration and exchange system for the soil fertility data. System development tools is VC++, it is used to achieve the Agent procedures for the preparation and encapsulation. The main function of Agent consists of information exploration of Agent, Agent, intelligent evaluation task decomposition and scheduling Agent, ontology evaluation Agent and ontology information processing Agent and Ontology learning Agent [START_REF] Chune | Multi Agent technology applications in disease diagnosis system[END_REF]. Using KQML as the message protocol Agent interaction, Enables Agent to exchange knowledge and information to other Agent and Agent running environment. System model is shown as figure 2

Fig.2. System Model

Soil fertility level evaluation process can be described as: User submitted data remotely through the client, after the system receives the data, the system preliminary analysis, using the evaluation model for data that is stored in advance,if no match is found in the model, then uses of ontology learning Agent, to study the corresponding evaluation model. Task scheduling of Agent will evaluate the task decomposition, Uses intelligent evaluation Agent call the evaluation module algorithm, then ontology evaluation evaluates the algorithm Agent, Or the ontology information processing Agent deals with the corresponding evaluation results. The final conclusion is reached, and the evaluation results will be output to the user.

Summary

In this paper, we study the rough set theory and ontology technology, propose a new method to describe the soil fertility data, realize the sharing and reuse of heterogeneous system knowledge. Using rough set approach to attribute reduction of data, can remove redundant attribute data, reduced data set; Using ontology can make the concept in the field of pattern be understood more accurately, can more clearly express the relationships and rules among the concepts. In this paper, the application of multi Agent technology, realized the sharing of knowledge of soil fertility preliminary. Future research will combine the multi platform interoperability, in-depth development and establish standards ontology of the application domain, and further promote the knowledge sharing and information integration.

  The exact makeup of soil ontology is: Class soilclass { Class physical ( ph , moisture , salinity , humus , textrue , cation , groundwater) Class site(position,erosion,material) Class weather(rainfall,light) Class nutrient(fe,slow k,k,n,p,om) Class management(irrigation,drought,crop) } Class class(attribute is soil_class) Class relations attribute:class_is The domain of definition of these attributes including pH,fe,slow k,k,n, p,om,cation is soil,and the range is int. The domain of definition of these attributes including moisture,groundwater,light,irrigation,rainfall,drought, erosion,textrue ,crop,position,material,humus,salinity, is soil,and the range is float. The domain of definition of soil_class is class,and the range is int. Ontology construction result is shown in figure 1.

Table 1 .

 1 The data this paper used is from the cultivated land fertility survey data, the NongAn (2006), offers by agricultural technology extension center of NongAn. The data includes 25 attributes, such as soil humidity, groundwater depth, light radiation intensity, soil irrigation capacity, annual rainfall, soil drought resistance and soil erosion degree, soil texture, crop rotation suitability, topography, soil parent material, part into layer thickness, salt concentration, humus soil pH value, effective copper, iron, effective slowly available k, effective k, effective fierce, total nitrogen, phosphorus, organic matter and cationic content, effective zinc and productivity grade. Some data are shown in table 1. Some fertility data

	2.1	The Data Source
	ground	soil		annual	soil	soil	soil	part into	salt	pH	effective	effective
	water	irrigation	rainfall	drought	texture	parent	layer	concen-	value	copper	iron
	depth	capacity		resistance		materia	thickness	tration
						Light	alluvial
	3-5m	no		400-450mm strong	clay		10-20cm	<0.1	6.6	1.25	8.72
		strong		strong	Light	alluvial 10-20cm
	<3m			400-450mm		clay			>0.1	6.7	1.26	8.47
	3-5m	strong	>450mm	strong	loam	alluvial 10-20cm	<0.1	6.7	1.39	4.70
		strong		strong	sandy	alluvial 10-20cm	<0.1
	3-5m			400-450mm		loam				6.5	1.21	9.45
		strong		strong	sandy	alluvial 10-20cm	<0.1
	<3m			400-450mm		loam				6.7	1.27	9.71
						sandy			<0.1
	5-8m	no		400-450mm weak	loam	loess	0-10cm		6.6	1.20	8.30
						sandy			<0.1
	3-5m	no		400-450mm weak	loam	diluvial 20-30cm		6.6	1.30	8.50
		strong		strong	sandy	alluvial 10-20cm
	<3m			400-450mm		loam			>0.1	6.7	1.28	8.48
		strong		strong	sandy	alluvial 10-20cm
	<3m			400-450mm		loam			>0.1	6.7	1.30	0.10
					strong	sandy	alluvial 10-20cm	<0.1
	3-5m	no		400-450mm		loam				6.6	1.27	8.28

Acknowledgment

Funds for this research was provided by the development of science and technology plan projects of Jilin province (NO. 201101114), Jilin provincial projects(NO.201248),The word bank project(No. 2011-Z20), Hall of Jilin province science and technology science and technology support program(20110237, 20110237,20120802), Science and technology research project of Jilin province department of education(No. 2013-68)


Chen Huiping

Tian Zhihong

Wang Yubin

Han Xue

The Analysis of County Science and Technology Worker Internet Usage and its Influence Factors

Keywords: county, science and technology workers, internet use, determinants

The county science and technology workers are critical components of Chinese science and technology workers, playing an important role in science and technology application and popularization. Improving the skills for Internet use of Chinese county science and technology workers can promote the level of science and technology in our counties and towns and expand the way of transformation of advance scientific and technological achievements. This paper analyzes county science and technology worker Internet use and the determinants based on the Second National Survey data of county science and technology workers. The results show that, among all Chinese science and technology workers in counties, there are only 51% were proficient in Internet use while computer configuration, education, age, length of service are the crucial factors affecting their proficiency . Hence, three recommendations are proposed to improve the skills for internet use of county science and technology workers.

County science and technology workers are the main component of Chinese science and technology workers, the main force in application and promotion of science and technology, and the important power of promoting the progress of science and technology, the development of regional economy and the construction of new socialist countryside. Counties consist of more than 90% of China's land area and more than 80% of China's population.

With the advancement of science and technology, computers and internets become popular. As to science and technology workers, under the background of knowledge "explosion" and information "flood", computer and Internet provide a vast information space and dramatically reduce science and technology workers' workload.

The powerful search feature of the Internet facilitates retrieving literature, and greatly improves the efficiency of scientific research.

Currently, research on science and technology workers are all based on census data or survey data, involving all aspects of science and technology workers.

According to the "Second National Survey of scientists " data, science and technology workers' job satisfaction, views on academic misconduct, and status of participation in science activities were analyzed by Zhang Jian [START_REF] Zhang Jian | The empirical analysis on working satisfaction of S&T professionals--based on the data of Tianjin[END_REF] , Zhao Yandong [START_REF] Yandong | Chinese science and technology views on academic misconduct: A survey result of 30,000 science and technology personnel[END_REF] , Xue Shu [START_REF] Shu | Level and obstacle of S&T Professionals'participation in popularization of science in China----based on the data of the general survey of Chinese S&T Professionals[END_REF] et al.

Based on questionnaire data, Lu Genshu [START_REF] Genshu | Analysis of basic characteristics of social responsibility consciousness of Chinese scientific and technical workers[END_REF] summarized the characteristics of social responsibilities of scientists, He Guangxi [START_REF] Guangxi | Public image of S&T professionals and its cognitive basis in China[END_REF] analyzed the public evaluation and attitudes to science and technology workers.

In the existing literature, Internet use and behavior have been studied mainly through descriptive statistics, nonparametric statistics and Logistic regression and other methods. Cao Rongrui [START_REF] Rongrui | Report on Internet use of college students in ShangHai[END_REF] analyzed the purpose, behavior, and obsession status of Shanghai college students' Internet use via the questionnaire data. The determinants of Beijing residents' Internet use were studied by Xu Meng [START_REF] Meng | Determinants of Internet Adoption in Beijing's Residents--a HLM Analysis[END_REF] using hierarchical linear model. Research about determinants, consequence variables, and intervening or regulatory mechanism on Internet use were summarized by Wang Jinliang [START_REF] Jinliang | Current directions on Internet use: antecedents, outcome variables, and influencing mechanism[END_REF] .Previous studies indicate that socio-demographic factors, family factors, regional factors, psychological factors, and other factors can affect personal Internet use behavior significantly.

There are also many related research abroad. Education, gender, age, income, place of residence, broadband applications, and so on are consider as the most important factors of internet use in the study of Sciadas (2002) [9]、 Singh (2004) [10]、 Whitacre and Mills (2006) [11]. Larry McKeown (2007) [12]analyzed the factors associated with internet use in rural and small town of Canada. In 2005, only 58% of residents living in rural and small town areas accessed the Internet, well below the national average. Individuals that are older, those with lower levels of education and those living in households with lower incomes were less likely to have used the Internet. Research has got deeply with the population of internet. Ohbyung Kwon(2010) [13] Natural Science teachers: refers to those who teach mathematics, physics, chemistry, biology, information technology, labor and technical and physical geography for primary education and secondary education (junior and senior); teachers who are engaged in science, engineering, agriculture, medicine and other disciplines in educational institutions for vocational education (secondary, tertiary), higher education.

Student village officials: refers to the fresh or previous college graduates, who served as the village party branch secretary, deputy secretary, committee director and assistant, or other positions of the village "two committees" in the rural areas (including community), or who engaged in secretarial, finance and accounting for rural credit cooperatives, science parks and other public service institutions.

Analytical Method

The analyses of Internet use of county scientific and technical workers mainly uses comparative analysis and proportion analysis. From view of the education background, 49% of the respondents are with undergraduate degree; 36% of the respondents are with junior college degree; only 2% of the respondents are with graduate or higher degree. In terms of the job title, most of the titles of respondents are intermediate and primary. The proportion of these two titles were 36% and 28%, respectively and the proportion of sub-senior and senior were 10% and 4%, respectively.

According to the industry, the proportion of agricultural science, health technicians, natural sciences teaching staff, engineering technicians and student village officials among the respondents were 26%, 24%, 23%, 21% and 5%, respectively. Except the student village officials, the proportion of science and technology workers in other industry personnel is closer.

In the survey, the proportion of institutions is 79%, ranking top; the proportion of government departments is 12%, ranking second; the third is private enterprise, accounting for 5%; private non-enterprise, state-owned enterprises, community groups, and other units account for 4%.

Internet use of science and technology workers

Equipped with computer and Internet is precondition for using the Internet.

Although computers and the Internet have been popularized in urban areas, some of science and technology workers in some rural areas cannot use the Internet due to the absence of computers and the Internet. Survey data indicate that 90% of science and technology workers are equipped with computers in the units, in which 88% have access to the Internet, that is 88% of the science and technology workers may use computer to surf the Internet.

There are 63% of the respondents that share computes with others. Their work condition is poor. There are only 27% of respondents that are equipped with their own computers. For the access to the Internet, there are only 55% of respondents whose Internet use is unrestricted. In this case, among the investigated county science and technology workers, those who can access the Internet freely accounted for 49.5%.

In spite of poor work conditions and infrastructure, among all the investigated county science and technology workers, 51% of them believe that they are proficient in sending and receiving e-mail and searching information and data; only 7% are unable to access the Internet. Even though the popularity of the Internet technique of county science and technology workers is quite low, it will be improved with the further promotion of Internet technology.

With regard to the person using the Internet skillfully, the proficiency is significantly different in gender. The proportion of female county science and technology workers who can use the Internet skillfully is higher than that of male.

Female choosing "quite skilled" account for 51% of all female; male choosing "quite skilled" account for 50% of all male, while the proportion of male choosing "no" is 8%, 2% higher than that of female.

The proportion of sciences and technology workers who can use the Internet skillfully in different industries varies. Specific conditions are shown in Table 2.We can observe that Internet use of engineering technicians and natural sciences teacher is better than that of agricultural technicians and health technicians, which is related to the characteristics of their industries. The proportion of persons using the Internet expertly among the student village officials is very high, mainly because the student village officials are mostly the generation after 80s and familiar with the Internet in school.

Analysis of Determinants

The Probit model was estimated via maximum likelihood estimation. The results are shown in Table 3. As we can see, influence of every variable on the dependent variable is significant except nature of the enterprise/institution. If one is male and equipped with computer, younger and with high degree and short work years, the more likely to access internet.

Whether computers are equipped in enterprises/institutions is the most influential factor of county science and technology worker proficiency in Internet use. Increasing 1% of the worker to computer ratio can increase the Internet utilization rate 0.67%.

The financial difficulty and the fact that leaders overlook the importance of equipping computer result in that science and technology workers have no access to computers.

Hence, the possibility of using the Internet proficiently dramatically reduced.

Increasing the worker to computer ratio is the most important factor of promoting Internet use of scientific and technology workers.

Age is also an important factor affecting the Internet skill of county science and technology workers. The younger one has the higher possibility of using the Internet skillfully. The number of observation born before 1950 and born in 1950-1959 is small. In addition, behavior of two age groups is similar, so the simulated result is not significant. Because the rise of computer and internet is in the late 1990s and Probably because the number of observation worked under 3 years and worked between 3-5 years is small and their behavior is similar, the results of two variables above are insignificant.

Education degree affects the Internet use of county science and technology workers markedly. The higher one's degree is, the higher possibility of one's ability to use the Internet will be. Among 6 dummy variables of education degree, the variables of undergraduate and master degree have significant differences from junior high school and below and the other 3 variables are adverse. Generally, those who are able to obtain higher degree are those with strong desire of knowledge and ability of learning. If this person has experience in using computers and the Internet after having a job, his desire of knowledge will be significantly stronger and speed of learning the Internet will be faster than the others. If the person has experience in using computer and the Internet in school, the higher his degree, the higher possibility of using the Internet skillfully will br. Requirement for Internet skills in school education is increasing in degree. Based on the analysis of determinants, the following suggestions are offered:

(1)To better the work conditions for county science and technology workers, to increase worker to computers ratio, to achieve everyone has an access to a computer or one people per computer if possible. As long as appropriate hardware is sufficiently provided, science and technology workers will have the motivation and possibility of improving their Internet use skills.

( (3)To improve the compensation incentive mechanism in order to encourage science and technology workers to make progress and to make more contribution. For some science and technology workers with longer length of services, who have made certain achievements, got some job titles and have little learning motivation, we can stimulate their learning enthusiasm so as to improve their Internet use skills by such methods as setting job grading, examining regularly, grading division results, and awarding the staff who got great achievement and so on.

1 Introduction

 1 Science and technology workers are those who are engaged in generation, development, dissemination and application of systematic scientific and technical *Corresponding author. knowledge, with corresponding scientific and technological work as their occupation in modern society. From the perspective of occupation, science and technology include scientific researchers, engineering technicians, agricultural technicians, health technicians and natural science teachers. Science and technology workers in our country are characterized by its large size and significant impact. With the increasing impact of science and technology innovation on the development of China, science and technology workers are also paid more and more attention by the public and also different talents projects are launched endlessly.

  make an empirical analysis on the factors affecting social network service use, individual characteristics and psychological factors have been considered in. There are many studies on science and technology workers but research about Internet use has not been studied. Although there are many studies on Internet use, the observations in those studies use the Internet for both work and entertainment. A few observations use the Internet mainly for entertainment, especially the college students in the study of Internet use behavior. As for science and technology workers, their purpose of using the Internet is to facilitate work and to improve productivity. Therefore, the study about Internet use and determinants of county science and technology workers is very necessary. Data used in this study are the research data from the "Second National Survey of county science and technology workers". In order to understand the difficulties in work and life of county science and technology workers, the China Association for Science implemented and led the Second National Survey of work conditions of county science and technology workers in 2011, which involves 206 Counties of 31 provinces (autonomous regions and municipalities) in total. 12360 copies of questionnaires were issued and 18913 valid copies were returned. In this study, the county agricultural science and technology workers are divided into 5 groups, such as agro-technicians, health workers, engineering technicians, science teaching staff and student village officials. Agro-technicians: refers to those who are engaged in agriculture technology in companies or institutions, including senior agronomists (veterinarians, livestock engineers), agronomists (veterinarians, livestock engineers), assistant agronomists (veterinarians, livestock engineers), technicians and technical staffs without professional titles. Health technicians: refers to those who are engaged in medical work in companies or institutions, including licensed doctors, assistant practicing doctors, registered nurses, pharmacists,inspection technicians,imaging technicians,health supervisors and doctors (pharmacists, nurses, technicians) on probation and other health professionals and technical personnel without professional titles. Engineering technicians: refers to those who are engaged in engineering technology in companies or institutions, including senior engineers, engineers, assistant engineers, technicians and other technical personnel without professional titles.

7 3

 7 , 1950-1959= 2, 1960-1969 =3, 1970-1979 =4,1980-1989 =5,After 1990 =6 length of service 1-7 Less than 3 years =1,.3~5 years=2,6~10 years =3, 11~20 years =4,21~30 years =5,31~40 years =6, more than 41 years=7 education degree 1-6 Junior high school and below = 1, senior high school / Higher vocational education/ technical secondary school= 2, junior college = 3, , undergraduate=4, master = 5 , Dr.low level = 1, fiscal funding institutions = 2, non-fiscal funding institutions = 3, state-owned enterprises= 4, private enterprises = 5 , private non-enterprise= 6, social groups = Empirical analyses

  technology is changing rapidly, many technology workers, especially mid-aged, learn new things slowly. Also, since training of Internet technology in enterprises/institutuions and society is limited, some county science and technology workers are not proficient in using the Internet or unable to access the Internet by the limitation of their own internet skills, even equipped with computers and the Internet.The effect of work age and real age are similar, but directions are opposite. The longer one works, the lower possibility one is able to use the Internet. The one with long length of service learns new technology about the Internet slowly and inactively.

)

  To strengthen on-the-job training of county science and technology workers , to train them regularly and especially to train middle-aged and older ones about Internet use skills. Since the Internet emerges in a short time and develops rapidly, many people know about the after having their first job. Mutual learning between colleagues is inconvenient but Internet related training organized by enterprises/institutions can work more effectively.

Table 1

 1 The analysis of determinants is conducted by constructing Probit model and processing data via Stata 12.0. According to existing research, socio-demographic factors affect Internet use behavior significantly. Based on the previous studies and the data obtained in this survey, variables such as gender, age, length of service, education degree, job title, industry, nature of the enterprise/institution are considered as major factors affecting Internet use of county science and technology workers. Internet use is the dependent variable which is classified into two types, skilled and unskilled. Value is assigned to other variables. Table 1 shows the setting of the Probit model of every variable. Probit model variable setting and definition

	Variable Name	Value	Definition
	dependent variable:

3.1Basic characteristics of science and technology workers

  In the observations, 18,913 county science and technology workers, males and women accounted for 56% and 44%, respectively. As for age, in all observations, 31~50 age people accounted for 66%; 18~30 age people accounted for 27%; only 7% of people are over the age of 50. Corresponding to age, 34% of respondents' length of service is from 11 to 20 years; 26% of the respondents' length of service is from 21 to 30 years; and11% is from 6 to 10 years and under 3 years. It is observed that most of science and technology workers engaged in the same profession from the beginning of their career, since the proportion of 30 to 50 years old worker and the proportion of the workers with10 to 30 years length of service is similar.

Table 2

 2

		the computer configuration and Internet use of county science
		and technology workers in different industries
	Industry	Agricultural technicians	Engineering technicians	Health technicians	Science teachers	Student officials village	Average
	skilled
	user	47%	57%	37%	54%	85%	51%
	proportion
	unskilled
	user	9%	5%	11%	6%	2%	7%
	proportion

Table 3

 3 As an important mean of communication and research, Internet technology is an important skill which technical personnel need to have when science and technology becomes more and more important and changes rapidly. However, among the numerous county science and technology workers who make significant contributions, there is still a portion of them who are unable to use the Internet or to know little about Internet use and 51% of them think they can use the Internet skillfully. To improve the Internet skill of China's county science and technology workers is to enhance the level of science and technology in county and to advance the expanding way of achievements transformation. So, it is necessary to progressively enhance the Internet skills of county scientific and technical workers by effective means.

		probit model estimation results
	variable name	Coefficient	Std. Err.	P>z
	PC configuration-1	0.6796	0.0500	0.0000
	Gender-1	0.0991	0.0288	0.0010
	Age
	2	0.1691	0.2808	0.5470
	3	0.5740	0.2765	0.0380
	4	1.0022	0.2784	0.0000
	5	1.3393	0.2831	0.0000
	6	1.2809	0.3452	0.0000
	Length of service

Acknowledgments.

This study is supported by China Association for Science and Technology research project -The Second Survey of County S&T Workers in China ‖(KXDC201002). Thanks all participants of the project.


Jonas G Croissant
email: jonasc@chem.ucla.edu

Olivier Mongin

Vincent Hugues

Mireille Blanchard-Desce
email: m.blanchard-desce@ism.u-bordeaux1.fr.

Xavier Cattoën

Michel Wong

Chi Man

Vanja Stojanovic

Clarence Charnay

Marie Maynadier

Magali Gary-Bobo

Marcel Garcia

Laurence Raehm

Jean-Olivier Durand
email: durand@um2.fr

à la diffusion de documents scientifiques de niveau recherche, publiés ou

Keywords: Mesoporous silica nanoparticles, two-photon, cancer cells, imaging, cross-section

non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Influence of the synthetic method on the properties of two-photon-sensitive mesoporous organosilica nanoparticles

organosilica (M2PS) NPs. The M2PS NPs porous structure could be tuned from radial to wormlike and MCM-41 types of organization. Besides, the 2PS precursor spatial dispersion was found to be highly dependent of both the 2PS initial concentration and the elaboration process.

As a result, two-photon properties were modulated by the choice of the synthesis, the best results being found in aqueous media at 25 or 80°C (Scheme 1). Finally, the M2PS NPs were used for in-vitro two-photon imaging of cancer cells.

Introduction :

Over the past few years, two-photon-sensitive NPs have attracted a lot of attention for theranostic nanomedicine. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] Near-infrared (NIR) two-photon excitation is indeed very attractive for its deep-tissue penetration and 3D-spatiotemporal accuracy, which are crucial for site-specific cancer treatment. 17 Among various nanoplatforms, mesoporous silica nanoparticles (MSN) are particularly suited nanomedical devices for their low cytotoxicity, excretion 18,19 , selective endocytosis through the enhanced permeability and retention effect (EPR), and multifunctionality. [20][21][22][23][24][25] The diversity of MSN features arises from their large surface areas, tunable pore size, controllable shape and morphology, and known silicon chemistry. 26,27 Besides, conversely to other non-porous inorganic NPs applied for two-photon nanomedicine, the sol-gel elaboration enables the co-condensation of versatile species with silica precursors to obtain organosilica NPs with high porosity. 28,29 Hence, two-photon fluorophores and photosensitizers (2PS) could be doped 8,13,30 or covalently bound in the material. 2,31 Phase segregation, low doping efficiency of 2PS moieties, as well as the photosensitizer diffusion out of the nanomaterial often make the chemical grafting more attractive. 32 The 2PS concentration and spatial distribution in the NPs will be crucial for the final two-photon properties of each chromophore. 33 The control of many different parameters is thus required for the construction of efficient M2PS NPs.

Herein, we report a study on M2PS NPs designed from three different elaboration processes, in order to investigate the influence of the synthetic method on the properties of the

Results and discussion

Firstly, the M2PS nanomaterials were designed via various synthetic approaches. Three procedures were compared which involved the co-condensation of a previously reported tetraalkoxysilylated two-photon photosensitizer (2PS) [2][3][4] with the TEOS silica precursor, through sodium hydroxide catalysis with a template of cetyltrimethylammonium bromide. The first approach involved modified Mann's conditions, 34 the six minutes reaction in aqueous media at 25°C. Two materials are compared from this procedure, M2PS-1 and M2PS-2, with 9 and 18 weight percent (wt%) of 2PS respectively (see Table 1). In the second approach, the synthesis was carried out at 80°C in a water/ethanol mixture (5:2, v:v) for 30 minutes; the related compound will be called M2PS-3. The third approach is a modified Lin's reaction, 35 which was performed in aqueous media at 80°C for 1 hour 30 minutes. Higher concentrations of 2PS precursor were used in this procedure, with 44 and 20 wt% of 2PS were obtained for M2PS-4

and M2PS-5 respectively.

Secondly, the structure and morphology of the M2PS nanomaterials were characterized.

Transmission electron microscopy (TEM) images depicted nearly 80 nm nanospheres for all types of M2PS particles, except the 200 nm nanospheres obtained from the water/ethanol mixture for M2PS-3 (Fig. 1A). Dynamic light scattering (DLS) size distributions showed that the best approaches to obtain monodisperse non-aggregated M2PS NPS were in aqueous media at 25°C for low 2PS concentration, or in aqueous media at 80°C for higher concentrations (Fig. 1B). Besides, electron micrographs revealed different types of porous frameworks for each reaction (see Scheme 1 and Fig. 1A). Typically, MCM-41 P6mm structure was obtained with the aqueous route at 25°C for M2PS-1, but the pore organization was very sensitive to the 2PS content. Comparing the same procedure in M2PS-1 and M2PS-2, the increase of the 2PS content from 8 to 16 wt% led to an important structural disorganization, as testified with the small angle X-ray diffraction (XRD) patterns (Fig. 1C). Conversely, the third strategy performed at 80°C retained the MCM-41 hexagonal array of the pores for the M2PS-4 and M2PS-5 materials at high 2PS concentration, as displayed by TEM and XRD patterns, but enlargement of the Bragg peak and the TEM image for M2PS-4 indicated a more slightly disordered structure.

Alternatively, a radial porosity was obtained on M2PS-3 NPs in the water/ethanol mixture (Fig. 1A,1C). The mesoporous structure of the materials was validated by the nitrogen-adsorptiondesorption technique. The BJH transform indicated pore diameters from 2.1 to 2.6 nm (see Table 2); high BET surface areas were found for all samples, ranging from 500 to 700 m²/g (Fig. S1 to S5). Thus, both the size and the porosity of the M2PS nanomaterials make them suitable nanocarriers for nanomedicine applications. Thirdly, the efficiency of the 2PS encapsulation in the nanomaterials was found to be highly dependent on the synthetic route. UV-Visible spectroscopy demonstrated the successful encapsulation of the 2PS molecules in the silica framework of all M2PS NPs (Fig. S6 andS7).

Solid state nuclear magnetic resonance (NMR) 29 Si and 13 C CPMAS spectra (Fig. S8) further supported that assertion. Besides, as shown in Table 1 with the comparison of the 2PS wt% in the NPs and in the reactants, the efficacy of the 2PS condensation was higher than that of TEOS.

Interestingly, highly organically functionalized M2PS NPs could be designed with both syntheses at 80°C. However, the usefulness of the M2PS-3 nanocarriers (water/ethanol mixture) is greatly impoverished, as we shall see with the photophysical properties. The 2PS spatial distribution in the silica was then studied by absorption and emission of fluorescence, since this factor affects directly the photophysical properties of the NPs. The emission spectra (Fig. 2A) and the fluorescence quantum yields (Table 3) of the M2PS compounds were measured and compared to those of the 2PS molecular reference (2PS-Ref, see structure Fig. S9). The most fluorescent NPs were found to be M2PS-1, M2PS-4, and M2PS-5, the latter having a quantum yield two to four times larger than the formers. A bathochromic effect was also observed on the 2PS band, as seen in the normalized spectra (Fig. 2B). The most red-shifted band corresponds to the synthesis performed in the water/ethanol mixture, with an absorption maximum at 469 nm; then follows the aqueous mixture at 25°C (max = 453-455 nm), and finally the aqueous reaction at 80°C (max ≈ 448-450 nm). Such an observation was consistent with the absorption spectra of the M2PS NPs (Fig. S7). These results are the direct outcome of the spatial dispersion of the 2PS molecules in the mesoporous silica matrices, with an important aggregation 36 of the 2PS for the M2PS-3 material. Thus we expected to obtain poorer two-photon properties on material having the most red-shifted 2PS emission bands. Indeed, the aggregation of 2PS moieties via - stacking interactions or condensation generally leads to increased non-radiative de-excitation rates and therefore to a quenching of the fluorescence, as well as to a decrease of the two-photon absorption properties. 37 Finally, the two-photon photophysical properties of the M2PS nanocarriers were investigated. The two-photon absorption cross-sections (2) were determined between 700 and 900 nm by investigating their two-photon excited fluorescence, and as anticipated M2PS-1, M2PS-4, and M2PS-5 displayed the highest cross-sections (see Table 3, and Fig. 3). It should be noticed that M2PS-1, M2PS-4, and M2PS-5 also exhibit the largest quantum yields (11, 26, and 41%, respectively), while their maximum cross-sections ranged from 110 to 200 GM. In the case of the synthesis at 25°C, the increase of the 2PS concentration from 8% (M2PS-1) to 16% in M2PS-2 leads to a decrease of both the fluorescence and the two-photon absorption cross-section, from 11 to 8%, from 110 to 80 GM. On the other hand, comparing M2PS-3 (reaction in water/ethanol) with M2PS-5 (synthesis in water at 80°C), which both have 20% of photosensitizer, drastically different properties were obtained. Indeed, the latter exhibits a twophoton brightness ( max F) of 82 GM, which is 40 times larger than that of the former (2 GM, see Fig. 3B). Furthermore, for a given reaction, the 2PS threshold for optimum properties was different, in the first synthetic approach, 8% was the maximum, whereas in the third approach the 2PS content could be increased at least up to 25 % without quenching the properties.

Consequently, the modulation of the two-photon properties of M2PS NPs could be done by an appropriate choice of the elaboration process. [c] Maximum two-photon action cross-section (two-photon brightness) per chromophore.

Conclusions

In summary, we report a study of the properties of organically modified mesoporous silica NPs for two-photon excitation. The modulation of the two-photon properties was found to be highly dependent on the synthetic approach used, which directly affected the spatial distribution of the photosensitizers. Furthermore, the threshold of the photosensitizer maximum concentration varied according to the elaboration method, the best results being observed with a modified Mann's reaction in aqueous media at 25°C for low concentration, whereas the Lin's method at 80°C in water was preferred at higher concentrations. Hence, M2PS nanomaterial was used for in-vitro two-photon fluorescence imaging. This study highlights the intricacies implied in the design of efficient NIR two-photon-sensitive nanomaterials for various applications such as nanomedicine.

Experimental

Materials

Tetraethoxysilane, cetyltrimethylammonium bromide, sodium hydroxide, ammonium nitrate and tetrahydrofuran were purchased from Sigma-Aldrich. Absolute ethanol was purchased from Fisher Chemicals. R. Norma Pure.

Apparatus

Absorption spectra were recorded on a Hewlett-Packard 8453 spectrophotometer and fluorescence data were collected on an Edinburgh Instruments (FLS920) fluorimeter.

Fluorescence quantum yields were measured in ethanol using quinine bisulfate in aqueous H2SO4 (0.5 M) as a reference (F = 0.546). Mass spectrometry was carried out at the Laboratoire de Spectrometrie de Masse (Lyon, France) with a Thermo-Finnigan MAT95 apparatus in electronic impact ionization mode. Dynamic light scattering analyses were performed using a Cordouan

Technologies DL 135 Particle size analyzer instrument. 29 Si and 13 C CPMAS solid state NMR sequences were recorded with a VARIAN VNMRS300, using Q8MH8 and adamantane references respectively. TEM analysis performed on a JEOL 1200 EXII instrument. SEM analysis performed on a FEI Quanta FEG 200 instrument.

Synthesis

M2PS-1 NPs. A mixture of cetyltrimethylammonium bromide (345 mg, CTAB), and sodium hydroxide (20 mL, 0.2 M) was stirred at room temperature during 50 minutes at 700 rpm in a 250 mL three neck round bottom flask. Then, the stirring speed was changed to 1000 rpm. TEOS

(1.6 mL) was added and after 40 seconds water (260 mL) was poured out. Afterwards, an ethanolic solution of the 2PS precursor (n0 = 9.0 10 -5 mol, in 1 mL EtOH) was added. The solution was then heated using a hair drier (from T0=25 °C to T'=27 °C over 1-2 minutes), in order to trigger the condensation process. After 5 minutes 30 seconds of reaction, a solution of hydrochloric acid (0.2 M, ca 36 mL ) was added to reach pH 6.9. Fractions were gathered in polypropylene tubes and collected by centrifugation for 15 minutes at 21 krpm. The sample was then extracted twice with an ethanolic solution of ammonium nitrate (6 g.L -1 ), and washed three times with ethanol, water, and ethanol. Each extraction involved a sonication step of 30 minutes at 50 °C; the collection was carried out in the same manner. The as-prepared material was dried under air flow for few hours.

M2PS-2 NPs.

A mixture of cetyltrimethylammonium bromide (345 mg, CTAB), and sodium hydroxide (20 mL, 0.2 M) was stirred at room temperature during 50 minutes at 700 rpm in a 250 mL three neck round bottom flask. Then, the stirring speed was changed to 1000 rpm, TEOS (1.6 mL) was added along with an ethanolic solution of the 2PS precursor (n0 = 1.3*10 -4 mol, in 1 mL EtOH). After 40 seconds, water (260 mL) was poured out. The solution was then heated using a hair drier (from T0=25 °C to T'=27 °C over 1-2 minutes), in order to trigger the condensation process. After 5 minutes 30 seconds of reaction, a solution of hydrochloric acid (0.2 M, ca 36 mL) was added to reach a pH of 6.9. Fractions were gathered in polypropylene tubes and collected by centrifugation for 15 minutes at 21 krpm. The sample was then extracted twice with an ethanolic solution of ammonium nitrate (6 g.L -1 ), and washed three times with ethanol, water, and ethanol. Each extraction involved a sonication step of 30 minutes at 50 °C in order to remove the CTAB surfactant; the collection was carried out in the same manner. The asprepared material was dried under air flow for few hours.

M2PS-3

M2PSScheme 1 .

 1 Scheme 1. Modulation of the two-photon properties of M2PS NPs via various synthetic pathways. Typical TEM images of the NPs porous framework are presented for each reaction.

Figure 1 .

 1 Figure 1. TEM images (A), DLS size distributions (B), and small angles XRD patterns of M2PS-1 to M2PS-5 NPs (C).

  Elemental analysis by combustion measurements of the NPs. [b] Determination based on the nitrogen wt% in the condensed 2PS moieties (O1.5Si-R-SiO1.5).

Figure 2 .

 2 Figure 2. Fluorescence emission spectra of M2PS NPs (A), and the associated normalized spectra in ethanol (B).

  Quinine bisulfate standard at 0.5 M in H2SO4. [b] Maximum two-photon absorption cross-section per chromophore.

Figure 3 .

 3 Figure 3. Two-photon absorption cross sections of M2PS NPs (A), and the corresponding two-photon brightness spectra in ethanol (B).

Figure 4 .

 4 Figure 4. Two-photon in vitro imaging of M2PS-3 NPs on living MCF-7 cells demonstrating the cellular uptake of the nanocarriers. Arrows pointed nanoparticles located inside the cells. Scale bar 20 m.

M2PS- 4 M2PS- 5

 45 photon excited fluorescence spectroscopy was performed using a mode-locked Ti:sapphire laser generating 150 fs wide pulses at a 76 MHz rate, with a time-averaged power of several hundreds of mW (Coherent Mira 900 pumped by a 5 W Verdi). The laser light is attenuated using a combination of half-wave plates and a Glan-laser polariser and the excitation power is further controlled using neutral density filters of varying optical density mounted in a computercontrolled filter wheel. After five-fold expansion through two achromatic doublets, the laser beam is focussed by a microscope objective (10X, NA 0.25, Olympus, Japan) into a standard 1 cm stirred absorption cuvette containing the sample. The applied average laser power arriving at the sample was between 0.5 and 15 mW, leading to a time-averaged light flux in the focal volume on the order of 0.1-1 mW/μm 2 . The generated fluorescence is collected in epifluorescence mode, through the microscope objective, and reflected by a dichroic mirror (675dcxru, Chroma Technology Corporation, USA). Residual excitation light is removed using a barrier filter (e650-2p, Chroma) and the fluorescence is coupled into a 600 μm multimode fiber by an achromatic doublet. The fiber is connected to a compact CCD-based spectrometer

Table 1 .

 1 2PS weight per cent determination in M2PS NPs.

Table 2 .

 2 Textural properties of M2PS NPs.

	Sample	M2PS-1 M2PS-2 M2PS-3 M2PS-4 M2PS-5
	SBET (m²/g)	713	647	603	503	677
	Dpore (nm)	2.0	2.3	2.3	2.5	2.6

Table 3 .

 3 Photophysical properties of M2PS NPs in ethanol.

Acknowledgements

We thank ANR P2N Mechanano for funding. Technological support from the Rio Imaging Platform is gratefully acknowledged.