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This interpretation is supported by the data for longer times showed in the inset.
The final isothermal discharging current at 523 K (data not presented here) can be fitted to an exponential decay function to determine the relaxation time as 3x10 6 s.
The data for different fields (not showed here) show the so called "cross-over" effect, meaning that if the charging field is higher the charge relaxes faster.
This is the case for long times in Fig. 2, for higher fields in Figs. 4 and 5 or for higher voltage to observe the cross-over effect (data not presented here).
Conclusions Experimental data demonstrate a dependence of specific conductivity of low-conducting materials on the charge stored in the polymer.

TGA/DTA thermograms for and acid functionalized CNTs untreated and thermally oxidized MWCNTs Characteristic thermal data such as the onset temperature To, and the glass transition temperature Tg, were determined from DSC curves and the results are shown in Table 1.
Characteristic thermal data for PMMA/MWCNT nanocomposites SAMPLE TG[OC] TONSET [OC] DCP [J/GK] PMMA 116,8 110,9 0,288 PMMA/0,2% MWCNT 114,8 110,5 0,233 PMMA/0,5% MWCNT 113,9 109,5 0,295 PMMA/1,0% MWCNT 112,6 108,7 0,296 Using the DSC technique, characteristic non-isothermal crystallization data such as To-the onset crystallization temperature, Tc-the end temperature of crystallization and Tp- the exothermic peak temperature of the crystallization were determined.
A higher content of MWCNTs means more steric hindrance and a reduction of the transportation ability of the polymer chains (higher DEa).
The obtained results are in agreement with the literature data [5].
Elastic behaviour was exhibited by DSC data for changes of Tg temperature.

The strain gauges were connected by wires to the collecting instrument of strain data that connected to the computer.
The erosion resistance performances of different test specimens were compared based on the quantities of their sediments. 6 specimens were measured for each data point [8].
The data demonstrated that in order to enhance the UCS of cement treated aggregate, coarse aggregate content of mixture can be increased reasonably, but too much coarse aggregate will increase the void of cement treated aggregate after compaction and lead to lower UCS.
The data show that the thermal shrinkage coefficient value of A aggregate is biggest and the thermal shrink coefficient value of F is smallest.
The data shows that the erosion quantity in 30 min decreases along with the increase of coarse aggregate content of mixture. 30 min erosion quantity value of A aggregate is biggest by up to 18.5g, and erosion quantity value of F aggregate is smallest, only 11.3g .

Mathematical treatment of the kinetic data can be carried out in two ways: 1) Finding of equation that best describes experiment and parameters which do not have a specific physical meaning; 2) Using of kinetic equations based on certain models of the interaction of solids.
From the technical aspect, the kinetic analysis will be examined as a tool for data reduction.
The information will be extracted from a series of measurements with many data points in the form of one model with few parameters.
The Netzsch Proteus software packages were used for TG/DSC data analysis.
Fit for the non-linear regression of the TG kinetic data.

The SPS method combines the simplicity of powder compaction in closed dies with the advantages of the hot pressing method at a substantial reduction in the duration and temperature of the powder consolidation to a non-porous state.
The calculated data and the data obtained by laser particle size analyzer are different, as the calculation of the average particle size by the BET method is based on the assumption that all particles are spherical.
Dispersivity of powders determined by laser diffraction and calculated on the values of specific surface Sample Dispersivity, µm Laser diffraction method Calculated data Initial В4С powder 4.7 4.329 Dispersed В4С powder 0.88 0.564 The sintering temperature of the ceramic В4Сmix samples Тsin was chosen relativety to the melting temperature Тmel of В4С in the range of 0.7 – 0.9, respectively, the sintering temperature Тsin.max was 90 % of Тmel and was not more than 2100 ºC.
The initial data for analysis of the processes during sintering were obtained in text format and then processed into graphical format for being presented.
Figure 2 presents the obtained data as a plot of the change of green compact height versus temperature change during sintering of the B4C sample at Тsin2, Рpr.max.

Today, with the development of advanced PCMs preparation methods and consequent cost reduction, phase PCMs became useful in many areas of application [2].
Here, the data measured for plasters cured 28 days in highly humid environment is presented.
Contrary to the total open porosity data presented above, one can observe significant decrease in both thermal conductivity and thermal diffusivity with increasing amount of applied PCM admixture.
Material Thermal conductivity Thermal diffusivity [W/mK] [m2s] RP 0.54 0.36 x 10-6 RT 21 4% 0.50 0.32 x 10-6 RT 21 8% 0.46 0.30 x 10-6 RT 21 12% 0.37 0.26 x 10-6 The data on mechanical parameters are presented in Table 4.
Identified temperatures of phase change during the cooling process (approx. 21°C) correspond with data provided by Rubitherm Ltd.

All signals were collected using a National InstrumentsTM data acquisition system (NI USB 6211) and the pressure signals were acquired and processed by the LabView 10.0 TM software.
The sampling rate was 400 Hz with 2,048 pressure data points.
For this, the 2,048 data points of pressure acquired in the plenum chamber at a sampling frequency of 400 Hz were filtered by a digital filter (IRR- infinite impulse response- Butterworth type) and then distributed following a mean centring procedure.
The Fast Fourier Transform algorithm (FFT) was applied on the mean centring pressure data, producing a pressure spectrum.
In Fig. 3 (a), with water flow rate of 10.5 mL/min, it was verified that, before of 600 s of the atomization, a gradual reduction in bubble amount as well as in the bed movement occurred due to the high presence of moisture.

Modal analysis was used to confirm the frequencies values as well as the mode shapes (nine low-weight accelerometers, a small electrodynamics shaker and a force transducer were attached to the structure; a digital data acquisition system recorded the dynamic signals).
Basically, the test procedure was the following: with the motor stopped, a certain voltage was set to the electric power supply and, at the same time, data acquisition was started.
The characteristics of the instrumentation used during the tests played an important role in the acquisition of useful dynamic data.
A low noise, fast, simultaneous multi-channel data acquisition was fundamental to get reliable dynamic data.
We also remarked that, in the general, the success of the kind of analysis presented here is due to three factors: to the judicious choices of the structural parameters, which allowed only two natural vibration modes to characterize the dynamic response of the system; to the constructive characteristics, which contributed to the reduction of the structural damping; to the instrumentation, which made it possible to record low amplitude transients and time-consuming phenomena.

Arrhenius plots calculated from output admittance, gate contact conductance and capacitance spectroscopy data for devices without the buffer layer are presented in Fig. 4.
For the data presented on the plots the gate contact measurements were taken at Vgs = -25 V to ensure full depletion of the device channel.
Since gate contact measurements were done at relatively large reverse bias voltages, time constants extracted from the data were corrected for the Poole-Frenkel effect [9].
RF data were obtained on transistors biased with Vgs = - 15 V and Vds = 15 V.
In order to de-embed those parasitics and find the equivalent circuit elements at higher frequencies, more elaborate data processing would be required.

However, the high cycle fatigue data of the alloy can only be found sparsely in the literature.
Uniaxial tensile test was carried out at an initial strain rate of 1×10-4/s using cylindrical specimens with 6mm gauge diameter, 20mm gauge length and 84mm total length on a MTS-810 machine equipped with a computer data acquisition system.
The data before No.1 couple reverse result appears are given up when the fatigue strength is calculated by the up-and-down method.
All adjacent reverse data are coupled.
The accurate fatigue strength is get by calculating the mean value of all adjacent reverse data mean value.