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CSA cement is characterized by fast strength development and a shrinkage reduction and thus its use was proposed, also mixed with the traditional OPC, for the production of shrinkage-compensating concrete (SHCC) [11-13].
For example, the electrical resistivity of CSA mix at 28 days was more than one order of magnitude higher than that of the OPC mix, that showed values of about 100 Ω·m (in agreement with data reported in literature for OPC concrete [28]).
A continuous reduction of the values was observed over time; at the end of the 24 h of polarization 0.74 mA/m2 was reached.
The images of steel fibers and concrete surfaces of CSA cement-based concretes clearly show that corrosion was occurred in these mixes, and in some cases a reduction in the cross section of steel fibers was noted.
A review of alternative approaches to the reduction of CO2 emissions associated with the manufacture of the binder phase in concrete.

THE PREPARATION OF IPMC The experiment adapted here involved the chemical decomposition method of preparing silver-based IPMC primarily by chemical reduction and dividing final treatment process into two branches.
Fig.1 IPMC preparation process procedure 2.1 Preparing IPMC by chemical reduction IPMC is composed of an inner ionic polymer film with two outer metal electrodes.
The chemical reaction equation adopted for the chemical reduction method of ionic polymer film plates of Nafion-117 with Silver (Ag), is shown in type (1).
The chemical reduction process diagram is shown in figure 2. 2Ag(NH3)2OH+C6H12O6→2Ag↓+C6H11O7 NH4+3NH3+H2O (1) Fig.2 Chemical reduction process diagram The chemical reduction pretreatment process for preparation of IPMC is divided into the basement membrane and the silver plating reduction reaction process.
Fig.5 Tip output displacement of IPMC which had ion exchange for different exposure durations From this novel test, the experimental data obtained showed that: samples with 1, 2 and 3 hour ion exchange exposure times showed gradual increase in their displacement with time.

Size Distribution To estimate the particle size distribution, a colloidal solution of nanoparticle was subjected to data acquisition using Zetasizer Nano Instrument (Malvern, UK) and measurements.
One of the disadvantages of the enzymatic reduction of silver is the slow rate of the reaction.
The time required for reduction ranges has varied between 24 and 120 h.
The non-enzymatic reduction is often fast, taking only a couple of minutes.
The non-enzymatic reduction of silver is based on the chemical reduction where the reducing and stabilizing compounds are produced by microorganisms or plants.

Therefore, the XRD data suggests that the silica shell consists mainly of amorphous phase rather than polycrystalline one [36] since there is the absence of silica-derived diffraction peaks.
The reduction in the calculated crystallite size which had also caused the reduction in other structural properties might be due to the size selection process done to disaggregate the particles.
Some researchers have reported the reduction in the crystallite size of nanoparticles after coating [37].
The reduction in magnetization might also be due to the lesser amount of magnetic substance per gram in the silica coated sample compared with the bare sample [5].
A reduction in magnetization was also reported for silica coated LSMO particles [25].

Reconstructed spectra with the data drawn out from every ten points of raw spectrum data, were used for developing PLS model after several pre-processing preparation.
Fig. 2 shows data preprocessing scheme consisting of 7 step procedures.
To reduce the data processing time, the raw spectral data were reconstructed by performing data preprocessing procedure.
Reconstructed 10-pixel skip spectrum was composed of 92 data points.
Data reduction effects on performance of prediction model with raw spectra.

This model can got high prediction accuracy in short-term prediction with less raw data and not more calculation steps[8,9].
In this paper, Equal-dimensional new information grey model is proposed which based on the rule of metabolism, the oldest data will be replaced by the new generated data as the input for the model to keep the equal dimensions .This method can get a good balance between the precision and complexity of the model and be well used in meeting with the requirement of real-time control.
However the flow data in diesel nozzle grinding is not very smooth.
The method is as follows: First, assuming the original data as Q=(q(1)，q(2)，… ，q(n)) , Where, if q (k)< l，add a proper constant to each data of the sequence to let q (k)>1 and the constant should be substracted after reduction.
After that, predict the flow by traditional GM(1,1) model and improved GM(1,1) model respectively based on this data sequence, the prediction data curves and the actural data curves are shown as Fig.3 (a) Improved GM（1,1）prediction (b) Traditional GM(1,1) prediction Fig. 3 Comparision of predict data curve and actural data curve According to Fig.3, the fitting effect of Improved GM(1,1)model is much better than traditional GM(1,1) model ，esperically for the Steep transision domain.

There are also the data of this method application for covering inspection of the Kurskiy station in Moscow.
Decrease load carrying capacity due to the cross sectional reduction of reinforcement and concrete (by protective layer spalling); 4.
In the basis of reinforcement corrosion is cathodic process of oxygen reduction.
Available abroad experimental data found it impossible to introduce a single-valued criterion for resistivity, indicating the occurrence or loss of the protective concrete features in relation to the reinforcement.

After setting appropriate conditions, we can get analysis data.A software is made to simulate the flow process dynamically based on the data of every static analysis.
Figure 1.The position data and vector data 2.
Adding vector data to the corresponding node.
Figure 1 shows the analysis result of one static state, the position data and vector data are key point in the analysis.
Figure 7 shows the curve fitted by ten sets of data.

The testing data will be marked by the feeding cutting depth L; upon each feeding of 10mm, the data of the sensors X and Y will be saved, which are named as the sensor X01, Y01~X09,Y09.
During each test, 18 data sets will be recorded.
Data comparison and test conclusion.
As is shown in Fig. 11-14, we can draw following conclusions: Fig. 11 Test data comparison of cutters 1, 2, 3 Fig. 12 Test data comparison of the cutter 2 Fig. 13 Test data comparison of cutters 3, 5 Fig. 14 Test data comparison of cutters 2, 4 (1) General rules of the cutting vibration of the tap cutter.
Due to the cutter wear, the vibration data value is slightly increased.

The ultrasonic attenuation shows the rate of sound energy reduction when an ultrasonic wave is propagating in a medium which is the lithium niobate tellurite glasses.
As the sound beam propagated through the material, there will be a reduction in sound intensity known as attenuation.
Fig. 1: Schematic diagram of experimental method. 2.3 Data Analysis Fig. 2 shows the typical time domain signal of ultrasonic wave propagation in a sample.
All the data calculated and gain from experiment have proved that the attenuation coefficient increased due to absorption (UV-Vis absorption) and scattering (TEM images) phenomena in the glass system.