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Data presented as the average values of triplicates and the maximum standard deviation among triplicate results.
The reduction ratio of total Zn concentration in the soil increased from 8.11% without the compost amendment to 10.15%, 16.15% and 20.05% with the amendment of 20, 40 and 60 g/kg compost to soil, subsequently decreased to 7.28% and 5.02% after the amendment of 80 and 100 g/kg compost to soil.
However, the reduction ratio decreased when the amount of compost amendment kept increasing to 80 or even 100 g/kg.
This reduction of Zn availability was due to the high pH of compost amendment, which raised the surface charges of Fe and Mn oxides.

Since p=const, and volume V changes, if at all, due to the reduction of atom spacing caused by the drop in temperature rather than by the changes in pressure.
We found a correlation between the relative metal volume reduction (compressibility) and the amount of pressure and the duration of its application shown in Fig. 1a and 1b.
It demonstrates that the application of high pressure turns liquid metal into a new state with the following characteristics: · due to a 12-13% reduction of volume the transition to the crystallized state takes place almost without any changes in volume and shrinkage defects; · when pressure is disengaged, liquid metal elastically recovers its original volume; · the compressibility of 6-8% is achieved when the pressure is relatively low (150-200 MPa) during the first 5-7 seconds; · the compressibility of 10-12% is observed when the pressure is increased up to 300-350 MPa within 7-12 seconds; · when the pressure amounts to 400 MPa, compressibility reaches 13% after over 40 seconds.
Since numerical computations of temperature patterns cannot be implemented due to the lack of reference data on thermophysical properties of molten metals, it is necessary to conduct more experiments.

For revealing the forming mechanism in micro level and for establishing the relationship between macroscopic deformation and microscopic changes, impact experiment of material property is conducted under the high speed cold roll-beating condition based on the plastic deformation mechanism of metal material, Based on the Zener-Hollomon constitutive relation, the macro change model is established, and the parameters of the 40 Cr are obtained according to the experimental data.
So in the whole deformation process, the relationship between the change of dislocation density and macroeconomic factors [12-14] is: (5) (6) In formula (6), r is dislocation density (cm-2), is strain, is strain rate (s-1), T is Thermodynamic temperature (K), da refers to dislocation increase while ds is dislocation reduction.
The reduction of dislocation is related with the absolute value of dislocation density, the varying relationship[16] between dislocation density and strain is: (9) In formula (9), K3 is the softening factor of material.
What’s more, there are inevitable errors among the process of the setting of experiment condition, the note of the experimental data, the choice of peak stress and material parameters, which leads to the tolerance of model.

When compared to the test data available from the literature, it showed that the porous zone model proposed by Liu and Weyers gives the best predictions.
Loss of the confining pressure eliminates entirely the frictional component of bond, accompanied by a significant stiffness reduction for the overall structural member.
Predicted results examined against test data endeavoured to draw conclusion on which rust deposition model is most suitable to apply in predicting concrete cover cracking due to steel bar corrosion.
Table 1– Critical corrosion penetration depth: model predictions in comparison with test data – assume a mean value for rust volume expansion coefficient n= 2.5.
Predicted results based these rust deposition hypothesis were compared with benchmark laboratory test data.

From the training data, create a bootstrap sample Z of size N. 2.
A decision tree doesn’t always require data to be normalized or scaled.
With inadequate data, the decision tree approach can be used.
With experimental data, we compared the results of the four models.
Maimon, “DATA MINING WITH DECISION TREES

Moreover, Current density-Electric Field measurements demonstrated a reduction of the leakage current and an improvement of the breakdown behaviour in the presence of the interfacial thermally grown SiO2.
Interestingly, a crystallization process of the Al2O3 occurred under electron beam irradiation during TEM analyses, in agreement with literature data [9].
While a higher conduction band discontinuity justifies the reduction of the leakage current, the better dielectric properties of the Al2O3/SiO2/4H-SiC MIS structures can be explained by a ALD denser Al2O3 growth in the presence of the thermal SiO2 template.

The model parameters are based on the structural and operational data of the pulverizing system.
Principle Before coal goes into furnace, the mass flux data are obtained by coal feeding machine weighing it up.
Online simulation of the model the data for off-line test is from operating record of power station DCS system.
The data of DCS real time data acquisition system has a millisecond update cycle.
The data have obvious falling, rising and relative long time stable loading section, which is convenient for investigation of model noise reduction ability to loading variation and steady section.

The aircraft structure was also used to acquire data with the same above condition.
However, the Lamb wave wavelet data need to be processed because it is impractical to feed the entire response signal into the statistical processing for pattern recognition due to possibility of data redundancy [7].
The data acquired from oscilloscope was voltage vs. time on a time-scale basis.
Figure 1 shows the typical wavelet data acquired and the extraction of the features for 1000 data points.
The distribution of the average data points for all surface conditions are shown in Figure 5.

Matlab programming is used for data processing.
Introduction It is important to for a sonar device to identify an object from the tons of data.
When this distance is small enough, the appropriate size of window will be found, which can to use to for future data partitioning.
The toughness of applying ANNs lies in the design of neurons and the data that are passed in between these neurons.
Mitchell, Despeckling SRTM and other topographic data with a denoising algorithm, Geomorphology, vol. 114, no. 3, pp. 238-252, 2010

All data, C8051f340 commands are transferred through the SPI bus.
Whenever the clock chips to produce a data acquisition and pulse data acquisition, MCU enters the interrupt service routine.
When the SPI bus is idle, it is used for data acquisition.
Because the internal registers of the ATT7022A are not used in ferroelectric memory implementation, i.e. if the reduction, value will change registers saved.
The ATT7022A measurement data is wrong, need to watch.