Miyuki Matsuo
email: matsuomiyuki@rish.kyoto-u.ac.jp

Misao Yokoyama

Kenji Umemura

Junji Sugiyama

Shuichi Kawai

Joseph Gril

Shigeru Kubodera

Takumi Mitsutani

Hiromasa Ozaki

Minoru Sakamoto

Jo- Seph Gril

Mineo Imamura

Aging of wood -Analysis of color changing during natural aging and heat treatment

Keywords: treatment, historical building, kinetic analysis, natural aging

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Wood as a natural material can be deteriorated by biodegradation, weathering, and aging. The service life of wood can exceed thousands of years under conditions under which biodegradation and weathering is avoided. Then, aging becomes a major source of deterioration. The elucidation of the mechanism of wood aging is important not only for the preservation and restoration of wooden historical buildings but also for purposes of basic wood research. In Japan, there are many historical buildings made of wood with culturally significant properties, such as the Horyuji temple, which was constructed in the 7th century; it is the oldest wooden building in the world. Thus, the study of wood aging is of great significance in Japan, in a country with a long history of wood culture.

Aging is not well defined degradation, which proceeds slowly in wood under participation of the omnipresent oxygen and water. Some reports have described the properties of naturally aged wood in comparison with those of recent wood [START_REF] Kohara | Studies of Japanese old timbers[END_REF]Kohara 1958a, b;[START_REF] Fengel | Aging and fossilization of wood and its components[END_REF][START_REF] Sandu | Thermogravimetric study on the ageing of lime wood supports of old paintings[END_REF][START_REF] Giachi | Chemical characterisation of degraded wood in ships discovered in a recent excavation of the Etruscan and Roman har-bour of Pisa[END_REF][START_REF] Viel | NMR spectroscopy applied to the cultural heritage: A preliminary study on ancient wood characterisation[END_REF]Esteban et al. 2006;[START_REF] Popescu | Degradation of lime wood painting supports. Evaluation of changes in the structure of aged lime wood by different physico-chemical methods[END_REF][START_REF] Yokoyama | Mechanical characteristics of aged hinoki wood from japanese historical buildings[END_REF][START_REF] Budrugeac | The use of thermal analysis methods for conservation state determination of historical and/or cultural objects manufactured from lime tree wood[END_REF]. There is a large body of literature that reports also on the development of analytical methods suitable for studying naturally aged wood from heritages of cultural and historical importance. In an ideal case, the methods should be non-destructive, simple, and portable. Spectrometric methods were developed such as infrared or near-infrared spectrometry [START_REF] Marengo | Monitoring of pigmented and wooden surfaces in accelerated ageing processes by FT-Raman spectroscopy and multivariate control charts[END_REF][START_REF] Tsuchikawa | Near-infrared spectroscopic observation of the ageing process in archaeological wood using a deuterium exchange method[END_REF][START_REF] Kandemir-Yucel | In situ assessment of structural timber elements of a historic building by infrared thermography and ultrasonic velocity[END_REF][START_REF] Castellini | Portable electronic speckle interferometry device for the damages measurements in veneered wood artworks[END_REF][START_REF] Desnica | Portable XRF as a valuable device for preliminary in situ pigment investigation of wooden inventory in the trski vrh church in croatia[END_REF]Inagaki et al. 2008a, b). There is a large progress in this field and in the development of protecting and preserving wooden cultural heritages [START_REF] Falciai | Continuous monitoring of wooden works of art using fiber Bragg grating sensors[END_REF][START_REF] Giorgi | Nanoparticles of Calcium Hydroxide for Wood Conservation. The Deacidification of the Vasa Warship[END_REF][START_REF] Giorgi | Nanoparticles of calcium hydroxide for wood deacidification: Decreasing the emissions of organic acid vapors in church organ environments[END_REF][START_REF] Björdal | Reburial of shipwrecks in marine sediments: a long-term study on wood degradation[END_REF][START_REF] Mahltig | Functionalising wood by nanosol application[END_REF][START_REF] Bugani | Study on the impregnation of archaeological waterlogged wood with consolidation treatments using synchrotron radiation microtomography[END_REF]). However, to understand the basic mechanism of wood aging, sample materials with an extended time of aging periods are needed. Kohara andOkamoto (1955, 1958a, b) widely investigated the natural aging of wood in historical buildings but a drawback in these studies was that the age of the wood was estimated based on the architectural history and style of the buildings.

During long time use of wood, possible factors of aging may be due to the combined effect of thermal oxidation by air-oxygen, which is partly dissolved in water, and acid hydrolysis by bond water and acids contained in wood. The aging mechanism of wood has been discussed by investigating heat treatment of wood, which is a kind of simulated aging. Heat under dry conditions supposed to be accompanied by thermal oxidation of wood components, while under moist conditions the more frequent participation of hydrolysis can be expected. Kohara (1958b) compared the naturally aged wood and heat-treated wood at up to 175 C un-der both dry and moist conditions and claimed that thermal oxidation is prevalent under ambient conditions and at higher temperatures both oxidation and acid hydrolysis are active. [START_REF] Stamm | Thermal degradation of wood and cellulose[END_REF] and [START_REF] Millett | Accelerated aging: residual weight and flexural properties of wood heated in air at 115°C to 175°C[END_REF] also suggested that wood aging is a mild thermal oxidation at room temperature. However, few papers have evaluated the theoretical aspects and detailed mechanisms of thermal oxidation on aging.

As reviewed by [START_REF] Esteves | Wood Modification By Heat Treatment: a Review[END_REF] and reported in many literatures [START_REF] Windeisen | Relations between chemical changes and mechanical properties of thermally treated wood 10 th EWLP[END_REF][START_REF] Stanzl-Tschegg | Comparison of mechanical properties of thermally modified wood at growth ring and cell wall level by means of instrumented indentation tests[END_REF][START_REF] Pfriem | Alteration of the pore structure of spruce (Picea abies (L.) Karst.) and maple (Acer pseudoplatanus L.) due to thermal treatment as determined by helium pycnometry and mercury intrusion porosimetry[END_REF]Bryne and Wålinder 2010;Bryne et al. 2010), heat treatment induces various changes in wood properties: decrease in density, equivalent moisture content, and mechanical properties; improvement of dimensional stability and hydrophobicity; and both favorable and unfavorable change in color. Some properties of heat treated woods are in correlation with the inevitable color changes [START_REF] Bekhta | Effect of High Temperature on the Change in Color, Dimensional Stability and Mechanical Properties of Spruce Wood[END_REF][START_REF] Brischke | Quality control of thermally modified timber: Interrelationship between heat treatment intensities and CIE L*a*b* color data on homogenized wood samples[END_REF]González-Peña and Hale 2009a,b) Kinetic analysis could be an effective method for theoretical prediction and practical evaluation of natural aging of wood in comparison with accelerated aging of various materials. There are several publications on paper-aging kinetics (Zou et al. 1996a, b;[START_REF] Łojewska | FTIR in situ transmission studies on the kinetics of paper degradation via hydrolytic and oxidative reaction paths[END_REF]), but successful studies of wood-aging kinetics are rare because of the higher complexity of the problem and the lack of old wood with reliably known age.

The present study is dealing with the kinetics of color change of wood during natural aging and dry heat treatment in the context of historical buildings in Japan. It would be beneficial if significant properties of wood from the cultural heritage could be analyzed by color measurements as it is non-destructive and requires small areas. Practitioners working with wood of historical buildings and staturessuch as sculptors, carpenters, and restorersfrequently evaluate the aged wood quality based on its color. Experience shows that color properties are in direct relation to aging, i.e the lightness of wood decreases and the hue is shifted slightly to red (Kohara 1958a). The same behavior in color was observed in the change induced by thermal treatment [START_REF] Bekhta | Effect of High Temperature on the Change in Color, Dimensional Stability and Mechanical Properties of Spruce Wood[END_REF][START_REF] Brischke | Quality control of thermally modified timber: Interrelationship between heat treatment intensities and CIE L*a*b* color data on homogenized wood samples[END_REF]González-Peña and Hale 2009a,b;[START_REF] Matsuo | Color changes in wood during heating: Kinetic analysis by applying a time-temperature superposition method[END_REF].

In our previous study [START_REF] Matsuo | Color changes in wood during heating: Kinetic analysis by applying a time-temperature superposition method[END_REF], it was possible to predict color changes that occur during aging by means of the kinetic analysis method successfully applied to color changes of wood heated. In this study, colors of wood samples of historical buildings, the ages of which were evaluated reliably by scientific methods, were evaluated. The data will be compared with the colors of wood heated under the completely dry conditions by means of kinetic analysis. The results will show whether thermal oxidation is the main factor for color change during aging.

Materials and methods

Specimens

Hinoki wood (Chamaecyparis obtusa Endl.), the typical wood used in traditional buildings and Buddhist sculptures in Japan, was studied. Samples with homogeneous grain were carefully selected. The aging time and origin of eight naturally aging wood samples (A -H) collected from historical buildings are listed in Table 1 The age determined by dendrochronology, by radiocarbon dating, and data found in historical documents were in agreement.

Heartwood specimens were cut out from inner parts of the samples, which were free from discoloration by bio-degradation, weathering and any stain and defect; dimensions: of 60 mm (L) x 10 mm (R) x 2 mm (T). The mechanical characteristics of these samples are described by [START_REF] Yokoyama | Mechanical characteristics of aged hinoki wood from japanese historical buildings[END_REF].

The log (harvested 1988) from which the control specimens were taken, was grown from 1629 to 1988. It was dried for 18 years under ambient conditions in a shed. Its color properties were reported by [START_REF] Matsuo | Color changes in wood during heating: Kinetic analysis by applying a time-temperature superposition method[END_REF]. The specimens were heated at temperatures ranging from 90 to 180°C in the time scale from 0.5 to 18432 h (768 days) as described in Table 2 (a). The specimens were then cooled at room temperature in a desiccator with silica-gel.

To compare the effects of natural aging, heat treatment, and a combination of natural aging and heat treatment, specimens from sample F (shown in Table 1), aged for 921 years, were heated in an air-circulating oven at various temperatures and times given in Table 2 (b) and then cooled in the same way as the heat-treated specimens. All specimens were protected from photo-discoloration by storing in a box or a desiccator in a windowless room.

TABLE 1

Naturally aging wood samples with the names of their sources and their aging times.

Sample

TABLE 2

Treatment temperatures and times of sample F, aged 921 years, (a) heat-treated recent wood samples and (b) heat-treated historical naturally aging wood (sample F).

Treatment times for samples F heated to the temperatures

90°C (h) 120°C (h) 150°C (h) 180°C (h) a) Recent 256~18432 a 32~7680 4~960 0.5~120 b) Sample F - 384~2696 54~560 4~42
a The treatment at 90°C is now in process with a planned treatment time limit of 61440 hours.

Color measurement

The color of the specimens was measured with a spectrophotometer (KONICA MINOLTA CM-2600d) under a D65 light source and an observer angle of 10°. The sensor head of the spectrophotometer was 8 mm in diameter, which was sufficient to eliminate the influence of variation of earlywood and latewood on color values because the average annual ring width was 1.0 mm [START_REF] Yokoyama | Mechanical characteristics of aged hinoki wood from japanese historical buildings[END_REF][START_REF] Matsuo | Color changes in wood during heating: Kinetic analysis by applying a time-temperature superposition method[END_REF], and the specimens had a homogenous grain. The CIELAB color parameters (L*, a*, b*) and the color differences (ΔE* ab ) were used for the kinetic analysis. The differences in L*, a*, and b* and the total color differences ΔE* ab were calculated using the following formulas [START_REF] Jis | Colour specification-CIELAB and CIELUV colour spaces JIS[END_REF][START_REF] Jis | Colour specification-CIELAB and CIELUV colour spaces JIS[END_REF]:

* * * * * * * * * - = ; - = ; - = 0 0 0 b b b Δ a a a Δ L L L Δ (1) 1/2 2 * 2 * 2 * * ] + + [ = b Δ a Δ L Δ E Δ ab (2)
where L* is the lightness and a* and b* the color coordinates under any testing condition, and L 0 *, a 0 *, and b 0 * the corresponding reference values obtained as the average of 83 untreated specimens. L 0 *, a 0 *, and b 0 * were 82.0, 7.20, and 22.2, respectively. Nine to 16 specimens of naturally aging wood, 3 to 5 specimens of heat-treated wood, and 1 to 2 specimens of heat-treated naturally aging wood were tested at each condition. Three locations in each specimen were measured, and the average values with standard deviations were calculated for the whole set of measurements at the given condition.

Results and discussion

Color changes

Figure 1 shows the specimen images. The naturally aging and heat-treated wood became darker with increasing aging and treatment time, respectively. The color changed uniformly from the outside to the middle of the specimens. natural aged woods and those of heat treated recent woods are sufficiently larger than the reported variations in color of hinoki wood [START_REF] Mitsui | Changes in the properties of light-irradiated wood with heat treatment Part 1. Effect of treatment conditions on the change in color[END_REF][START_REF] Mitsui | Low atmospheric temperature dependence on photodegradation of wood[END_REF][START_REF] Tsushima | Variations of wood properties in forests of seedlings and cutting cultivars of hinoki (Chamaecyparis obtusa)[END_REF].

FIGURE 2

Changes of ΔE* ab during natural aging and heat treatment as a function of time and temperature. (error bar: standard deviation)

Kinetic analysis and color changes of natural and accelerated aging

Kinetic analysis using the time-temperature shift factor (a T ) was adopted to predict the color change during natural aging in our previous article [START_REF] Matsuo | Color changes in wood during heating: Kinetic analysis by applying a time-temperature superposition method[END_REF]. The brief description of the analysis is as follows.

Generally, it is known that a chemical reaction can be described by an Arrhenius equation:

RT E A k a - exp (3)
where k is the rate constant of the chemical reaction, A the frequency factor, E a the apparent activation energy, R the gas constant, and T the absolute temperature of the reaction. The apparent activation energy is then obtained from the slope of the Arrhenius plot, which is the ( )

( ) 1 = 2 1 = 2 2 - - = n i i n i i Y Y Y Y R (6)
where the values i Y ˆ are measured values, i Y the modeled values, and Y the average of measured data. The measured color properties of the naturally aging wood were superposed by using the multiplying factor a T on the time axis to fit the regression curve at 180°C. The proper a T values were determined by the non-linear iterative curve fitting method. Figure 3 shows the superposed data with the regression curve. with the change measured in naturally aging wood. That is, the Arrhenius plots were extrapolated to the temperature of 15°C, i.e. to the annual mean air temperature in historical buildings in Nara, Japan [START_REF] Nagata | Meteorological observations in old temple buildings (12) Sangatsudo and Daibutsuden of Todaiji temple and Shinyakushiji-hondo[END_REF](Nagata , 1971a, b), b). Then, the a T calculated from the extrapolation was compared with the a T determined from empirical data. The Arrhenius plot of E* ab is presented in Figure 4 (1) as an example, but the plots of L*, a* and b* exhibited similar features.

The a T calculated from empirical data was lower than that calculated from the extrapolation, implying that the plot did not necessarily keep a linearity over the reaction temperature range. Such a non-linearity of the Arrhenius plot has been observed for the mechanical properties of various polymeric materials [START_REF] Celina | Accelerated aging and lifetime prediction: Review of non-Arrhenius behaviour due to two competing processes[END_REF][START_REF] Ding | On the degradation evolution equations of cellulose. Cellulose 15(2):205-224. of the hygroscopic behaviour of 205-year-old and recently cut juvenile wood from Pinus sylvestris L[END_REF]. [START_REF] Gillen | Evidence of non-Arrhenius behaviour from laboratory aging and 24-year field aging of polychloroprene rubber materials[END_REF] and [START_REF] Bernstein | Nylon 6.6 accelerating aging studies: II. Long-term thermal-oxidative and hydrolysis results[END_REF] ensured the existence of a non-Arrhenius behavior by comparing the naturally aging polymer samples with the samples treated at widely-ranged temperatures. Or, as applied for a lot of accelerated deterioration tests, the lower a T of the naturally aging samples may result in that the change was accelerated because of the moisture in the cell wall which induces the hydrolysis, the repetition of drying and wetting, and the repetition of hot and cold periods.

However, the analysis by using the linear correlation of the Arrhenius plot is an effective way to predict the lifetime [START_REF] Rowe | Aging of HDPE geomembrane in three composite landfill liner configurations[END_REF][START_REF] Rowe | Effects of Thickness on the Aging of HDPE Geomembranes[END_REF][START_REF] Arrieta | Thermal aging of a blend of high performance fibers[END_REF]). The regression lines for the plots including both heat treatment and natural aging (Figure 4 (2))

showed fairly good linearity (r > 0.99) in all color parameters. Based on the good linearity, we can conclude that the color change during natural aging was similar to that of the heat treatment, namely the thermal oxidation. This conclusion needs further inspection concerning the linearity of Arrhenius behavior for exact prediction and elucidation of wood aging. Conceivable experiments are, for example, heat treatment at the temperature below 90 C or accelerated deterioration test considering moisture in the cell wall. (1) E a =113 kJ mol -1

(3) E a =133 kJ mol -1

(2) E a =90 kJ mol -1 15 C

FIGURE 4

Arrhenius plots of shift factors from empirical superposition of the change of ΔE* ab , regression lines and apparent activation energies for the plots of (1) heat-treated wood, (2) heat-treated wood and naturally aging wood, and (3) heat-treated naturally aging wood. (■: heat-treated, •: natural aging, ○: heat-treated after natural aging)

Color changes during heat treatment of naturally aging wood

In the preceding section, the conclusion was that color changes during natural aging could be explained mainly as thermal oxidation, and they could be accelerated by heating. The hypothesis is that color changes during natural aging involves similar processes as those observed during accelerated aging by heating. This means that the heat treatment of sample F (Table 2 b), which included a combination of natural aging and heat treatment, should cause a color change similar to that of natural aging or heat treatment only. According to the shift factor calculated, the color change (ΔE* ab ) after 921 years in the ambient temperature was almost equivalent to that of approximately 6.7 h at 180°C. Therefore, the total color change that occurred during natural aging for 921 years and during 180°C treatment for x h was plotted as the change for (6.7 + x) h. Figure 5 shows the superposed data obtained by the shift factors calculated from the color changes of heat-treated wood.

The aging time in the figure represents the total treatment time calculated as aging at 180°C. The changes of heat-treated naturally aging wood were well-superposed on those of heat-treated wood. This confirms the hypothesis that the mechanism of the color change during heat treatment might be the same as that occurring during natural aging. The values of the apparent activation energies are summarized in Table 4. Although those of heat-treated naturally aging wood were somewhat higher than the others, those of L* and ΔE* ab were within the framework of reported values [START_REF] Stamm | Thermal degradation of wood and cellulose[END_REF][START_REF] Millett | Accelerated aging: residual weight and flexural properties of wood heated in air at 115°C to 175°C[END_REF]. The higher energies of a* and b* means that they change more slowly than L* and ΔE* ab . However, the range of these data was not sufficient to evaluate them more accurately.

FIGURE 5

Superposed data of heated wood after aging for 912 years using a T calculated from heat-treated wood (•: heat-treated wood at 90-180°C superposed by a T , error bar: standard deviation).

The beginning of wood aging [START_REF] Fengel | Aging and fossilization of wood and its components[END_REF] indicated that the aging of wood begins with the cutting of a tree and that alterations of the wood substances begin shortly after a tree has been cut. Moreover, chemical changes after heartwood formation, i.e. the formation of a physiologically dead part of the xylem [START_REF] Panshin | Textbook of Wood Technology[END_REF], play probably also a role in wood aging. This section discusses the beginning of wood aging based on the results of the former section.

In our previous study, in which color changes were measured in a recently harvested wood sample [START_REF] Matsuo | Color changes in wood during heating: Kinetic analysis by applying a time-temperature superposition method[END_REF], there was a slight change in the color parameters with the time of heartwood formation. Figure 6 shows the L* variation within the recently harvested wood sample as compared with that variation predicted with E a of 90 kJ mol -1 , which was calculated from the a T of both heat treatment and natural aging. There was little change in L* within the range of approximately 160 years from which almost all specimens were cut out.

The variation within the wood sample was much smaller than the predicted change. This can be interpreted that most wood aging that is responsible for color changes begins with tree harvesting and wood processing. This conclusion also requires further examination, including an examination of the question how to evaluate the tree cutting time from wood samples that do not have their outer-most annual rings.

FIGURE 6

The L* value measured along the radial direction on the radial section from the sapwood/heartwood boundary toward the pith as compared with predicted natural color changes. Aging time was determined as the time from heartwood formation. The arrow indicates the area from which the specimens for heat treatment were cut out.

  i.e. aging time, which was determined as the age of the outermost part of the sample detected by dendrochronology as of AD 2007.

FIGURE 1

 1 FIGURE 1Color change of naturally aging and heat-treated wood (a: control (untreated wood), b:aged for 1573 years, c: treated at 180°C for 120 h). The specimens are arranged in order of increasing aging or treatment time.

  logarithm of the determined time versus the reciprocal of treatment temperature (Atkins and Paula 2010). The regression line of the Arrhenius plot allows the determination of the reaction rate at any temperature. To determine the activation energy based on all of the data, the time-temperature superposition principle (TTSP) (Ding and Wang 2007) is often applied. According to the TTSP, when the curves of the measured material parameter vs. logarithmic treatment time at different temperatures can be superimposed by proper scale changes on the log time axis, the shift distance along the logarithmic time axis is called the time-temperature shift factor a T , given by where t ref is the test time at a reference temperature T ref , and t T is the time required to give the same response at the test temperature T. Combining Eqs. (3) and (4and T ref are absolute temperatures. Plotting ln(a T ) vs. 1/T is another way to calculate E a and to predict changes in properties under ambient conditions. In the present study, a logistic function was chosen to describe the changes of L* and ΔE* ab and a polynomial expression for those of a* and b*. All parameters of the functions were estimated using a non-linear iterative curve-fitting method and the coefficient of determination R 2 is determined to express the goodness of fit:

  A well-superposed curve implied that the color changes might have been caused by the same process irrespective of natural aging or heat treatment. Regression curves fit well along the whole data set (R 2 > 0.99 in L* and E* ab , and R 2 > 0.87 in a* and b*). Our previous study showed that the calculated apparent activation energies of heat-treated wood on L*, a*, b*, and E* ab were 117, 94.3, 116, and 114 kJ mol -1 , respectively. The quoted study also concluded that the color change during the heat treatment was explained as thermal oxidation irrespective of treatment temperature. The color change in the ambient condition was predicted based on these results and compared

  FIGURE 3Superposed color properties with master curves using a T at each temperature. (error bar: standard deviation)

  ΔE*ab increased with aging time. The measured color values of control specimens were near to the reported values and color changes and the data between

Table 3 gives the changes in the L*, a*, b*, and ΔE*ab values of naturally aging wood, and Figure

2

compares ΔE*ab of natural aging wood to that of heat-treated wood

[START_REF] Matsuo | Color changes in wood during heating: Kinetic analysis by applying a time-temperature superposition method[END_REF]

. In both recent and naturally aging wood, L* decreased and a*, b*, and

TABLE 3

 3 Number of specimens and CIE data concerning L*, a*, b*, and E* ab of naturally aging wood with standard deviations in parentheses.

	Sample, age	# Speci-ments	L*	a*	b*	ΔE* ab
	A, 1573	16	62.11 (1.39)	11.36 (0.38)	27.82 (0.75)	21.11 (1.35)
	B, 1395	10	58.31 (1.68)	12.01 (0.50)	26.66 (0.79)	24.62 (1.62)
	C, 1505	11	59.34 (1.14)	11.19 (0.25)	26.29 (0.78)	23.40 (1.07)
	D, 1470	15	57.62 (1.59)	11.95 (0.32)	26.47 (1.22)	25.25 (1.46)
	E, 1215	15	63.25 (0.96)	11.09 (0.39)	27.23 (0.81)	19.82 (0.97)
	F, 921	15	65.66 (1.01)	10.56 (0.40)	27.00 (0.71)	17.39 (1.02)
	G, 737	9	67.41 (0.56)	10.91 (0.26)	27.70 (0.60)	16.04 (0.56)
	H, 569	15	73.20 (0.77)	9.37 (0.43)	25.89 (0.65)	9.81 (0.88)
	Cont., 19	83	82.01 (0.84)	7.20 (0.61)	22.22 (1.03)	0.00	-

Acknowledgements

The authors thank Horyuji-temple in Nara prefecture and Senjuji-temple in Mie prefecture for providing the aging wood samples. The authors also thank Dr. Kagemori for her critical review of the manuscript. This work was supported by a Grant-in-Aid for Scientific Research (A) (No. 20248020) and for JSPS Fellows (No. 21 2994) from the Japan Society for the Promotion of Science.

Conclusions

The color changes of naturally aging wood samples were measured and kinetically analyzed.

The value of L* decreased and those of a*, b*, and ΔE* ab increased with the aging time both for natural and artificial aged wood by heat-treatment. As a result of the kinetic analysis, the color changes during natural aging could be mainly explained as a mild thermal oxidation.

This result was also supported by analyzing the color changes of heat-treated naturally aging wood. Predictions of natural color changes were interpreted that most wood aging responsible for color changes begins not with heartwood formation but with tree harvesting and wood processing.


Carmen L Padrón

Paloma Díaz

Ignacio Aedo
email: aedo@ia.inf.uc3m.es

The automatic generation of semantic annotations for didactic materials and the use of models in the material development to improve its reusability

The didactic material reusability, understood as its capability to be used in different learning situations or in diverse knowledge domains, is one of its most desirable features. It depends, among other factors, on the use of semantic annotations to describe relevant material characteristics, which can improve its localization and retrieval. In spite of the recognized value of semantic annotations, they are usually considered as optional. In this paper we describe the mechanism proposed in the MD2 approach to automatically generate semantic annotations within the didactic material development. Such mechanism tries to relieve users (developers) from the complexity of material's annotation and intends to obtain materials with some reasonable degree of reusability.

Introduction

The use of learning technologies promises new opportunities for instructional reusability and personalized learning since they provide some means to describe main characteristics of materials, and infrastructure supports that help to localize, retrieve and reuse those materials in different educational situations or adapt them to the different educational preferences of learners. Instructional reusability and personalized learning are two basic features needed to face the challenges of the current information society. Bringing to reality such promises demand that those features will be somehow ensured within the development process of didactic materials.

The didactic materials reutilization capability depends, among other factors, on applying a material's design that is based on separation of the contents from its presentation and, the contents from its instructional design [START_REF] Polsani | Use and abuse of reusable learning objects[END_REF]. These separations help to severally reuse or adapt material or its components to different learning situations or in diverse knowledge domains Moreover, the material should comply with the current learning technology specifications and standards, specially with those related to interoperability that allow materials to be used in heterogeneous contexts and those concerned to meta-data annotations which allows the automatic o semi-automatic material search and retrieval. Thus, during the didactic material development those factors must be taken into account in order to achieve a reasonable level of reusability. But even if materials maintain a clear separation among contents, instructional design and presentation and are standard compliant, they can be hard to reuse. The main problem is that practitioners who intend to reuse them also need mechanisms to identify the material that fulfil their expectations, for which some kind of meta-data can be useful [START_REF] Litlejohn | Issues in reusing online resources in Reusing Online Resources: A sustainable approach to elearning[END_REF].

On the one hand, the didactic material has some pedagogical properties that can be relevant for reuse purposes such as its pedagogical strategy type, learning objectives supported, and time needed to achieve those objectives, level of difficulty, kind of material or its granularity. On the other hand, there is pedagogical information about the knowledge domain which is also important for reusing materials like the name of the topic or theme enclosed in its contents, the kind of learning competences that topic can cover, its knowledge prerequisites, the relation of that topic with other topics on the same knowledge domain, etc. And last but not least, some technical support features of material can be also essential for its reuse such as the medium used to publish or deliver it, its format, presentation time or the type of learner's interaction it promotes. A material which has been described using all those 3 perspectives, can have more chances to be discovered and adapted or reused when a learner or practitioner requires another material which has in common some of its described requirements or features. Unfortunately, most popular approaches to develop didactic material development like RELOAD [START_REF]RELOAD Reusable E-Learning Object Authoring and Delivery project[END_REF], LAMS [START_REF]Learning Activity Management System (LAMS) foundation website[END_REF] and CopperAuthor [1] consider the semantic annotation as optional and it must be carried out by experts of each of the aforementioned perspectives. In this paper we introduce a mechanism to deal with these issues by automatically generating semantic annotations from the models generated during the development process. In this way, a set of semantic annotations compliant to standards are obtained, increasing the potential of material reusability and relieving developers of the complexity of creating them manually. In the section 2 we briefly present the MD2 approach, which supports some of e-Learning standards and specifications like IMS LD [START_REF]IMS Content Packaging Information Model[END_REF] and IMS LRMI (IEEE LOM)

Eighth IEEE International Conference on Advanced Learning Technologies 978-0-7695-3167-0/08 $25.00 © 2008 IEEE DOI 10.1109/ICALT.2008.265 [START_REF]IMS Learning Resource Meta-data Specification[END_REF] and proposes a model, a method and architecture for the didactic material development. Section 3 is devoted to present some related work and to explain how semantic annotations are generated from the models in the MD2 approach. Finally in section 4 some conclusions and future works are outlined.

The MD2 approach

Didactic materials are herein considered as a conjunction of a set of contents, in the form of learning objects, and a pedagogical strategy, defined by an instructional design, and they take the form of units of learning to guide the educational process. This definition takes into account current e-Learning standards and specifications and it is based in two important concepts in the e-Learning domain: the learning objects and the units of learning [START_REF] Padrón | MD2 Method: The Didactic Materials Creation from a Model Based Perspective in Innovative Approaches for Learning and Knowledge Sharing[END_REF].

MD2 is an approach for developing didactic material whose rationale is "the development can be effectively supported if we count on means to describe the main features of the material (namely, contents and pedagogical strategy) taking into consideration the real abilities of material developers, who are not always and at the same time experts in pedagogy, in the knowledge domain and in technical issues". The approach consists of a method, a model and architecture for their implementation.

The method intends to assist users during the different stages of didactic development: selection, composition and evaluation [START_REF] Padrón | MD2 Method: The Didactic Materials Creation from a Model Based Perspective in Innovative Approaches for Learning and Knowledge Sharing[END_REF]. Underlying the method, there is a model that provides a number of elements to formally specify the features of the didactic material using four views: knowledge domain (KD), pedagogical information (P), technical support (S) and quality (Q-U). The main idea behind this approach is to use this model elements or descriptors to provide automatic mappings from complex technical descriptions of learning technology standards and specifications to simpler and closer descriptions to practitioners about material requirements. Thus, the relationships amongst the different MD2 model elements from K, P and S views are used by the method to guide the selection and composition stages of the development. Meanwhile another set of MD2 model elements (Q-U) are used in the evaluation stage to help to analyze the material's usability, pedagogical value and quality. Those elements had been defined taking into consideration previous experiences related to evaluation of Educational Hypermedia [START_REF]IMS Content Packaging Information Model[END_REF].

The method also defines a mechanism to automatically annotate material features taking advantage of the relations among elements of different MD2 model views and the descriptions they provide about material characteristics. Hence all values of MD2 model elements with the material's development rationales will be automatically stored as extended semantic annotations of the material, allowing its future localization and its retrieval for reutilization purposes.

Next section goes further into automatic generation of semantic annotations presented in this paper.

Automatic generation of semantic annotations

To the best of our knowledge there are no design or development methods which deal with the automatic generation of semantic annotations in the learning design arena, but there are authoring tools like HyCo [START_REF] Berlanga | Towards Semantic Metadata for Learning Elements[END_REF] which semi-automatically generates annotations using some elements of IMS LRMI (IEEE LOM). It automatically generates the values for some IMS LRMI elements according to information from the structure of created hypermedia book and it provides support to manually create values for the rest of IEEE LOM elements relying on the user knowledge. Also approaches from the software engineering discipline like KA2 initiative [START_REF] Erdmann | From Manual to Semi-automatic Semantic Annotation: About Ontology-based Text Annotation Tools[END_REF] are worthy of consideration since it automatically produces semantic annotations using a process of extracting annotation-relevant information from texts and multimedia resources.

The MD2 method includes a mechanism that generates semantic annotations, which is automatically triggered when the evaluation stage ends. This mechanism creates a set of extended semantic annotations. We consider them extended because they comprise descriptions of material features that comply with IMS LRMI (IEEE LOM) [START_REF]IMS Learning Resource Meta-data Specification[END_REF] as well as annotations concerning development rationales. Those development rationales include information about the set of actions taken during the different stages of development, their results and the reasons leading to take such actions. Our approach is different from the used in HyCo since MD2 supports different types of materials (learning objects, assessment and units of learning), automatically generates two different types of annotations and the descriptions about material features are obtained from the relations among the different MD2 views meanwhile HyCo uses the structure of hypermedia book that can be represented as learning object to generate the annotations. Next we explain each of these types of annotation and their influence on the potential reusability of material.

Automatic generation of LRMI semantic annotations

The descriptions of material features compliant to IMS LRMI (IEEE LOM) specification covered by the MD2 approach include a subset of elements grouped on four of the nine categories defined by the specification: General, Technical, Classification and Educational [START_REF]IMS Learning Resource Meta-data Specification[END_REF]. These categories are closely related to the three perspectives presented in the Introduction section. For their selection we also took into account which ones of the 100 elements defined by the specification were the most common used features to search and retrieve materials [START_REF]IMS Learning Resource Meta-data Specification[END_REF]. In table 1, the S_standarElements descriptor is presented and it includes mappings from elements of the different MD2 model views to the LOM descriptors of the aforementioned categories. The availability of such standardized descriptions about material features can help to search, localize and potentially reuse or adapt material or its components. Thus, during the selection stage the semantic annotations generated include the ideas that support selection decisions like the number of content resources needed, and per each one of them: the type of selection process (retrieval, creation or versioning); the kind of resources included on contents; the type of pedagogical strategy selected; the durability of the topic and right management issues.

The rationales related to the composition stage comprise whether the stated requirements have influences to modify the material presentation structure, which is an instance of unit of learning for the selected pedagogical strategy and it is represented according to IMS LD XML binding. The rationales also include what kind of adjustments was made to such structure and the results of content integration in that presentation structure.

Meanwhile rationales concerned to the evaluation stage include all the values of Q-U view elements which represent evaluation criteria [START_REF] Padrón | MD2 Method: The Didactic Materials Creation from a Model Based Perspective in Innovative Approaches for Learning and Knowledge Sharing[END_REF], the computed and observed values for each evaluation objective (pedagogical value and usability), whether redesign is needed and in those cases, the recommendation proposed. Also when redesign is needed, the annotations include information about corrective actions and the results of modifications done in each stage of development according to the proposed recommendation.

The availability of such kind of annotations can be useful to guide and reduce development efforts in those situations when materials with similar development requirements are needed.

The mechanism for the automatic generation of annotations

A general architecture of the MD2 development framework has been presented in [START_REF] Padrón | MD2 Method: The Didactic Materials Creation from a Model Based Perspective in Innovative Approaches for Learning and Knowledge Sharing[END_REF]. It includes a semantic annotations generation mechanism which interacts with the rest of mechanisms supporting the different development stages. The semantic annotations generation mechanism implements an annotation algorithm composed by the following steps I. Gather semantic information to describe a. Material features b. Development rationales II. Generate semantic annotation files III. Store didactic material with its annotations in the Repository. In step Ia. (Gather Material Features), all information that has been gathered during the selection and composition stages concerning the knowledge domain (KD), pedagogical information (P) and technical support (S) views provides data to describe material features according to IMS LRMI (IEEE LOM). The relationships between the elements of these three MD2 views (KD, P and S), play an important role to achieve such a goal since they establish which information must be used in each of the selected LOM descriptors, as has been shown in Table 1.

The step Ib. (Gathering development rationales) aims to log all data from the executions of modules supporting the different development stages and the reasons why certain action has been taken. This step uses the data flows from the MD2 selection, composition and evaluation mechanisms to the annotation mechanism. The development rationales include the name of each development stage, the MD2 model elements used in the stage, the results obtained in the development stage and the decisions taken through the process to obtain them. They also comprise information about the material redesign when it is needed, the results of proposed recommendations and the modified values of related MD2 elements.

The step II (Generate semantic annotation files) uses the data gathered in the previous steps to store them in 2 different annotation files. For the general material descriptions is created a lom.xml file using the IMS LRMDI XML schema meanwhile for the development rationales annotation file developmentrationales.xml is used the XML schema defined by the MD2 method. Thanks to this step the mechanism is able to provide developers with the semantic annotations.

Once the distribution package for the material is created according to the IMS CP [START_REF]IMS Content Packaging Information Model[END_REF], step III is in charge of adding the lom.xml file to the package and stores the package material with its development rationales file into the Repository. By this way, when a developer has to create a new material with similar requirements, the material previously created can be retrieved from the Repository during the selection stage using information from the semantic annotations. According to the degree of the coincidence found respect to the descriptors included in the lom.xml file, one of its components (content or strategy) or both could be reused in the new material. Furthermore, annotations concerning development rationales annotations can be used to guide the new development and also can be a good start point to automatically generate materials.

An example of automatic generation of semantic annotations

Let us introduce an example to help to understand how semantic annotations are generated within the MD2 approach. In this example, all evaluation stage details have been omitted, aiming to make the example simpler. If the reader is interested in a complete example, it is presented in [START_REF] Padrón | MD2 Method: The Didactic Materials Creation from a Model Based Perspective in Innovative Approaches for Learning and Knowledge Sharing[END_REF]. There is a development situation where a teacher from a Spanish university needs to create a material to guide a learning process that is related to Fundamental Data Structures, especially about the topic Linked List Data Structure. He will use an authoring tool which implements the MD2 approach and there is also available a Repository.

Step 1 of MD2 method asks him to select the topic to be covered by the material and his answer is the aforementioned topic. According to the method this information is used to consult a knowledge domain Ontology about Computer Science learning and to obtain data to complete all values of KD view like discipline (KD_discipline-Programming Fundamentals), general learning objectives addressed by the selected topic (KD_generalObjectives) and the estimated time to reach them (KD_requiredTime) or the topics related to the selected one (KD_sTopic). Then the method Steps from 2 to 8 ask teacher about some pedagogical features of the material. Step 2 ask to select a type of material from a list of possible types supported (i.e. unit of learning -UoL, learning object, and assessment) and he choose UoL that constitutes the value for the P_typeMaterial element. At this point the teacher also is asked to select a type of pedagogical strategy from the list of the most appropriated strategies for learning processes related to Computer Science. The values of that list are defined according to the definition of P_strategy element, he selects Problem based strategy and it is stored as the value for P_strategy. Step 3 demands him to select which are the required concepts and learning objectives to attain from the list of cognitive skills to be addressed by the selected topic, which has been assigned to KD_generalObjectives in Step 1. Some of the data from that list are (1) Knowledge-Know-Linked list data structures representation, operations and use; (2) Comprehension-Describe-Linked list data structure memory allocation. The teacher selects the first one and those values will be stored into the P_skills element. Step 4 ask teacher to define the estimated effort to execute material and to effectively achieve the learning objectives from a list of legal time values restricted by the 6hrs defined in KD__requiredTime element.

The teacher selects 2 hrs and that value is assigned to P_effort element. Step 5 asks teacher to define the kind of items needed for the material. To do so, a list of possible types of items or components is presented. Its values are proposed following the P_typeMaterial definition and they can be whole strategy, some activities or some activity structures for that strategy. The teacher selects some activities structures. Step 6 asks teacher about the number items he considers needed for the material and her answer is 3.

Step 7 requires from teacher to supply information about level of difficulty for the material. Thus he must select an option from the list of possible fuzzy values [High, Medium, and Low]. His answer is Medium and this value is assigned to the P_difficulty element. Next, Step 8 asks to the teacher to define if some score threshold is needed to consider that learning goals are achieved. Then he must select an option from a list of two valid values (Yes, No). He chooses Yes and he is prompted to provide a range of values for the score threshold and he gives a range between 2 and 5 points. This information is used to obtain suitable value for S view elements related to the e-Learning specification used for material delivery or presentation.

Method Steps from 9 to 11 ask teacher to provide some information about the technical support needed for the material. Thus, step 9 asks teacher to define if the material needs time presentation restrictions, he is asked to select an option from a list of two valid values (Yes, No). He selects Yes and he is prompted to provide a range of values to restrict the material (UoL) execution time. His answer is also controlled by a maximum value corresponding to the to the Step 4 answer. In this case he chose 2 hrs and this value is used by the composition mechanism to control the UoL execution time. Next in Step 10 teacher must select the desired supporting medium for the material from a list of possible media (Printed, hypertext, hypermedia-web, pervasive computing element) defined by the MD2 metamodel for the element S_medium and he also is asked to select the language of presentation. For the first question, he selects hypermedia-web and this value is assigned to the mentioned S view element. Such value is used to determine which will be the e-Learning standard or specification XML binding used to define the presentation structure, in this example is IMS LD. Also according to the S_medium definition, selected value will provide information about the format of presentation (XHTML) and the requirements for the operating system (any operating system) and browser needed for the material visualization (any browser). The Step 11 asks teacher to define what kind of learner interactivity with the material is needed to effectively achieve the stated learning outcomes. He is prompted to select of one type from the list of fuzzy values [High, Medium and Low]. He selects Medium and that answer is assigned to S_interaction element. Its also used by the MD2 inference mechanisms based on S view definition to the adequacy of his selection with respect to his answer to Step 10 and to confirm the proposal about the presentation and delivery standard. For the second question about the language, he must select a value from the list of possible presentation languages defined for the element S_language. He selects Spanish (es). All the information gathered in these 11 Steps is used by selection mechanism to select the appropriate contents for the material contents. In this example, was not found a developmentrationales.xml file for materials of the same type the teacher needed, thus was not previous developing experience obtained to guide this development. Thus during selection, 6 different contents (4 explanations and 2 simulations in form of learning objects) were retrieved from the Repository since their features matched to the gathered requirements. All of them were opensource and free to use thus, no rights management issues were found. And the teacher decided to make versions of 2 explanations related to Linked list operations to adequate them to desired difficult level (P_difficult value). Also the data obtained from the 11 steps were used by the composition mechanisms to select the presentation structure i.e. a UoL template for Problem based strategy with 2 hrs of presentation time and with 3 activity structures, the first structure was devoted to Linked list representations, the second one to Linked list operations and the last one for Link list uses. Such structure does not need any modification. As result of composition the different contents were glued to the presentation structure to make up a coherent material. Then, when evaluation stage ends, the semantic annotation generation mechanism is triggered. Thanks to the communication among previous mechanisms and the annotation mechanism the information to execute the annotation algorithm is supplied. Hence the step Ia of annotation algorithm can obtain and assign the values of .the selected LOM descriptors according to the Table 1. These values have been presented in this example with a bold type. Also the step Ib can gather the data from the aforementioned development rationales. Next the step II generates the lom.xml and developmentrationales.xml files and the step III adds the first one to the material distribution package and stores the package with the development rationales file in the Repository. Thus when a new material about Linked list with other similar requirements will be needed, it will be possible to reuse the recently created material about Linked lists.

Conclusions and Future works

In this paper we have presented the mechanism proposed by the MD2 approach to automatically generate extended semantic annotations while you are developing didactic materials. It is novel in the sense that automatic generation of semantic annotation includes standardized metadata derived from knowledge domain, pedagogical and technical descriptions for material development and also provides annotations about development rationales. Thanks to this mechanism the MD2 approach can help to ensure some degree of reusability of the obtained material and lightens developers from the complexity of the semantic annotation process.

The implementation of presented mechanism has been concluded and we are currently working on its assessment in real development situations. We already obtained some preliminary information that can confirm that presented mechanism lightens developers from the cognitive load of materials annotation. Further results of these evaluations will give us more information about previous conclusion and related to the usefulness of the automatic generated semantic annotations to achieve the desired and demanded instructional reusability.

Table 1 .

 1 Mappings from MD2 elements to selected LOM descriptors

	LOM descriptors included in the
	MD2 element S_standarElements
	Category	Element	MD2 elements
	General	title	KD_topic,
			P_materialType,
			developer, affiliation
		aggregation-level P_materialType
		language	S_language
	Technical	format	S_medium
		requirement-	S_medium
		operating-system
		requirement-	S_medium
		browser
		duration	P_effort
	Classification	classification-	KD_discipline,
		purpose	P_skills
		classification-	KD_discipline,	KD
		taxonpath-source	ontology name
		classification-	P_skills
		taxonpath-taxon
	Educational	learning resource	P_materialType
		type
		interactivity	S_interaction
		level
		difficulty	P_difficulty
		typical learning	KD_estimatedTime
		time
	3.2 Automatic generation of annotations about
	development rationales

MD2 generates another kind of annotations, which are concerned to development rationales and are extracted from different stages of the development process.

Authorized licensed use limited to: Univ Carlos III. Downloaded on September 16, 2009 at 08:39 from IEEE Xplore. Restrictions apply.

Acknowledgements: This paper is part of the MODUWEB project (TIN2006-09678), funded by the Ministry of Science and Technology, Spain