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The new production process and the use of new materials introduce improvements such as 55% reduction in the actuator's weight, a higher reliability, a 75% reduction in the production time and PPAMs can now be produced in all sizes from 4 to 50 cm.
Modeling of static characteristics of such complex systems is realized on the basis of data from producer, by using simulation programs, or empirically based on measured data on a real actuator.
These springs produce restoring forces, which tend to return the muscle to its original length. [24, 27, 28] Spring in serial connection with the contractile element causes muscle length reduction and force decreasing, while the parallel spring causes slow progressive muscle length reduction without further force decreasing. [29] Considering second Newton law we can write for Hill´s model: (1) kde: m – mass of moving load, y – muscle motion, FD – force of damper, FPC – forces of parallel element, FCE – force of contractile element, FE – external force.

The interpretations of information presented in this article are based on the combined data set of many papers published recently.
Primary data were obtained through mapping of different reports and analysis of the studies and relevant documents that were publish from reputable institutions, mainly carried in online version. 1.
The solution is available for many applications to manual and automatized production system and makes it possible to [14]: · Reduced costs Thanks to consistent standardization and a reduction in complexity, investment costs can be lowered by up to 15% compared to more traditional concepts.
A reduction to one process step per module results in high transparency and availability
They declared significant reductions in the design effort by using pre-built components - modules.

Conversely, pseudocapacitors involve the transfer of faradic charge across porous electrodes through electrochemical reduction-oxidation (redox) reactions [5].
In Fig. 1b, the data illustrates distinct patterns of N-doped rGO synthesized via a microwave-assisted solvothermal.
Additionally, the XRD data exposes the presence of peaks originating from other compounds, specifically CuO (monoclinic) (ICDD PDF 065-2309) and Cr2O5 (monoclinic) (ICDD PDF 00-036-1329).
Consequently, this alteration leads to a reduction in lattice spacing, which becomes more closely aligned with the lattice spacing of graphite at 3.36757 Å.
Conversely, as a result of the doping and microwave irradiation processes, the crystallite size of N-doped rGO experiences a reduction.

The acquired load-displacement data was subsequently converted into stress-strain data.
Upon exposure to UV light, the AgNO₃ receives sufficient energy to allow for the reduction of Ag+ within the solution.
This reduction process is termed as a photochemical reaction, which forms a metallic black or gray silver coating [20].
Similarly, the 50 mm specimens experienced only a minor reduction in strength.
Both the slenderness ratio and AgNO₃ addition influence the reduction in strength.

For example, metallic nanoparticles may demonstrate enhanced strength due to a reduction in defects within their crystalline lattice [16].
The authors demonstrated that reducing particle size increases their hardness, which is explained by the reduction of defects in the crystal lattice.
Initial data: · The hardness (average) for any material is equal to for large particles
The data will provide insights into optimizing processes like sedimentation and filtration.
For particles smaller than 10 µm, additional methods such as centrifugation or electrostatic precipitation must be considered. 2) hardness (H), the hardness of particles decreases with a reduction in their size .

The results show, that the shape accuracy is affected by the CAD data and the macro-geometry of the grinding wheel.
Therefore, specialized requirements on the CAD data were defined in order to increase the shape accuracy.
Firstly, the influence of the CAD model on the workpiece shape and the requirements on the used CAD data is defined.
Influence of the CAD data on the shape accuracy The complexity of the structuring process of free formed surfaces requires CAD/CAM systems to generate the tool paths.
-F.: Loss Reduction Using Riblets on a Supersonic Through-flow Fan Blade Cascade.

Because of the data dependences or interactions among LPs, synchronization protocols have to be introduced to PDES to guarantee the so-called local causality constraint (LCC) [26].
However, the NSM is inherently combined with the sequential semantics, and all sub-volumes share one common data structure for events or messages.
Thus, directly parallelization of the NSM may be confronted with the so-called boundary problem and high costs of synchronously accessing the common data structure [29].
In order to obtain higher efficiency of parallel simulation, parallelization of NSM has to firstly free the NSM from the sequential semantics and secondly partition the shared data structure into many “parallel” ones.
Several challenges have been overcome, such as state saving, roll back and especially GVT reduction in parallel execution of simulations.

Suspensions of composite binders are characterized by a typical thixotropic character of the flow (Fig. 5), however, the kinetics of viscosity reduction of suspensions of different composition differs significantly from each other.
After static computer processing of experimental data, mathematical models of changes in the strength and density of the solidified mortar from the amount of plasticizer and the fraction of the volume of the fine filler were obtained (Fig. 7).
The rational dosage of the plasticizer using VNV-50 based on quartz of metamorphogenic origin is 0.3 % by weight of cement in the composition KV, using VNV–50 on the basis of Intrusive-magmatic origin – 0.6 %, which confirms the previous data.
The analysis of the data obtained for the Flexural strength showed that the introduction of the optimal amount of the additive in the composition of KV on the basis of quartz and metamorphic Genesis in the early stages of hardening (3 and 7 days) provided an increase of strength by 40% and 20%, respectively, compared to the strength of the hardened mortar on the basis of quartz of igneous origin.
Thus, a reduction in viscosity in a series: TMC-50 → VNV-50 on the basis of Intrusive-magmatic quartz and melamineformaldehyde of the plasticizer → VNV-50 on the basis of metamorphic quartz and a polycarboxylate plasticizer.

This data are of important to the model.
Normally, this data was explored and collected by various organizations.
In this paper, the data collected by the Office of Nation Resources and Environmental Policy and Planning of Thailand is utilized and can be shown in Table 2 [10].
Table 3 The input data to the model Legend Tree Absorption CO2 (Ton per year) Expense ($) Trading price ($) Area Si (m2) L (MTonCO2 ~) a Nutmeg 98.62 600.00 11.00 16 16.05 b Bermese 68.04 588.43 c Bengal Almond 89.162 595.34 d Copper pod 107.39 564.67 e Iron Wood 1 83.25 608.50 f Cananga 166.50 614.00 g Afzelia xylocarpa 126.15 598.44 h Iron wood 2 138.75 615.10 i Lagerstroemia loudonii 101.51 598.84 j Bullet wood 121.34 598.50 k Mesawa 91.39 621.34 l Alexandrian Laurel 90.01 600.34 m Java Plum 77.26 615.07 n Kayu 88.32 591.77 Result Using data in Table 3, the optimal solution is obtained and shown in Table 4.
Prombanpong(2010).”The Research Framework for a Reduction of Global Warming Through Efficient Afforestation and Reforestation in Thailand”, 11th Asia Pacific Industrial Engineering and Management Systems Conference 2010, 6-9 December, 2010, pp. 115-119

Fig. 1 Fuselage panel model Generally, thin-walled components such as frames are fixed based on the ‘N-2-1’ locating principle [11] that the number of locators required is N (N > 3), 2 and 1 on the primary datum, secondary datum and tertiary datum, respectively.
Given the sample matrix of is , where n is the number of sample data, then Δ can be decomposed by PCA as follow: (2) where Br×r is the eigenvector matrix of the geometrical covariance matrix cov(Δ) whose eigenvalue matrix is V.
Supposing that all frame positioning errors follow Gaussian distribution ～N(0.5mm, 1.0), the sample data Δ10000×42 and its covariance matrix B can be obtained by 10000-cycle Monte Carlo simulations, then the procedures of the optimum selection are as follows: 1.
Through Eq. 8, all pose parameters are obtained and their error distributions are plotted in Fig. 4 (there just plots the error data of Frames Ⅰ, Ⅲ and Ⅶ).
Contrarily, with the reductions of measurement point number on other frames, both μρ and σρ also become smaller.