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Except the high resolution imaging capacity, AFM was used to research the physical properties of various biological materials [3, 4].
Therefore, individual red blood cells for AFM measurements would be able to provide a variety of factors on the impact of red blood cells.
Since cells had both viscoelastic and fluid nature, the force-displacement curves were depended on the probe speed, also affected the young’s modulus.
AFM showed the possibility of the measurements of mechanical properties of biological samples under micro-conditions; it associated the flexible data with morphology to get a better understanding of the sample and its structure in biological systems.

And its adsorption properties of arsenic in aqueous solution were studied by static adsorption experiments.
Activated carbon has unique pore structure, abundant surface active functional groups, along with chemical stability, high mechanical strength, acid, alkali and heat resistance, insolubility in water and organic solvents, it is an excellent adsorbent.
So it is speculated that under the same concentration of impreganated Fe(Ⅲ) salt, the stronger the oxidation of Fe(Ⅲ) salt is, the larger improvement the surface chemical properties of activated carbon can obtain.
So the impregnatin time will affect the adsorption properties of adsorbent.
Fig.3 Effect of impregnation time on adsorption capacity Fig.4 Effect of curing temperature on adsorption capacity The effect of curing temperature on adsorption The loading of ferric oxide hydrate on activated carbon relys on the adsorption and transformation of Fe3+ , this two processes occur during the evaporation or chemical precipition of the cure, so curing temperature is one of the key factors that determine the adsorption properties of Fe-AC.

Intorduction Nano-composites, such as nano TiO2/polypropylene, polyethylene/montmorillonoid, etc., are widely used because of their satisfactory physical and functional properties.
However, experiments have shown that the practical dispersion ratio of this method is much lower than expected because the migration rate of particles onto the bubble wall is low, seriously affecting the dispersion of nano-particles.
In order to improve dispersion effectiveness of the bubble sketching-based method, we need to analyze the particle migration process theoretically and find the mainly factors which impact on the migration ratio of particles.
In such a process, particle motion is also affected by gravity and lift force.
Ren, Mechanical properties of low-density polyethylene/nano-magnesium hydroxide composites prepared by an in situ bubble stretching method, J.

The dynamic response of the clamped beam under low velocity impact Wengui.Long1,a, Zhuhua.Tan1,b, Yang.Liu1,c, Furui.Wang1,d 1State key laboratory of advanced design and manufacturing for vehicle body, College of mechanical and vehicle engineering, Hunan University, Hunan, 410082, China.
Jacob [3] conducted many experiments on clamped beams subjected to localized loading, study focuses on the final deformation affected by geometry of the beam.
However, theoretical analysis ignores these factors, and the theoretical model is based on the quasi-static loading condition. (2) The empirical equation about the dynamic yield stress may not apply.
It is found from the figure Fig. 8(a) that in the early-time elastic response, the variation of the stress indicates the dispersive property of the elastic flexural waves: the wave peak in the rear are more intense in magnitude than that at the front of the wave packet .
The dynamic response of the clamped beam is divided into four stages: elastic fluctuation, the overall structural response, unloading response and free vibration, plastic hinge forms in the overall structural response stage, the hinge also affects the variation of the stress, the stress displays a platform on the stress-time curve.

Artificial neural networks model was studied for simulating the property and function of human brain.
Table 1 Measured Data and the Rredictive Value of Neural Network Model Monitoring Time /day Real Settlement /mm Model Prediction /mm Error 0 0 28 -6.87 92 -26.62 183 -49.05 218 -54.30 243 -62.24 280 -68.66 309 -77.86 348 -85.84 375 -91.13 471 -112.30 559 -128.24 658 -146.73 -148.93 1.5 731 -160.70 -164.39 2.3 968 -200.26 -206.66 3.2 1108 -221.10 -225.74 2.1 1287 -245.19 -238.56 2.7 1443 -269.99 -260.27 3.6 Fig.5 Comparison diagram of real data and model prediction Conclusion Embankment settlement of expressway is essentially a nonlinear behavior, and it is affected by many factors.
Not only the external load and the natural environment has a great influence on the embankment deformation, but also the complex nature of the soil itself seriously affects the calculation of the authenticity of embankment settlement.
Beale, Design of neural networks, Beijing: Mechanical Industry Press, September 2002, pp.89–91

This paper is dedicated to on the basis of previous, study on relationship between bolt shape and bolt properties.
Under the same conditions of surrounding rock and resin anchoring agent, the main factors influencing the anchor performance is the bond strength between resin anchoring agent and bolt rod [4].
The three main factors of cohesive force have a great relationship with the anchor shape and the surface condition [5].
Therefore, the bolt shape directly affects the anchor performance.
The main factors influence the bolt shape include if there are ribs, the rib type, the rib height and the rib spacing and so on [6][7].

It is due to their admirable material properties such as high strength, high hardness, high melting temperature, low density, high chemical inertness, and biocompatibility [1].
Surface quality such as tensile stress, strain, intensity, stiffness, and residual stress can also be affected by the formation of recast layer.
Experiment and Measurement The experiment was designed using general factorial of two factors with four levels (42) statistical model, where the two controlled parameters were gap voltage and rotational speed.
The value of Prob > F less than 0.05 indicates the factors n, n2, n3, v, nv are significant
Lee, Mechanical properties and wear behaviour of the white layer, Tribol.

Although some attempts have been made to develop machining models to simulate the surface topography of a machined surface, most have failed to take into account the effect of various factors such as tool geometry, the synchronization of the machine tool path with the vibration motion of the FTS, the dynamic condition of the cutting systems, the cutting mechanics, and material science.
Surface Generation in Fast Tool Servo Machining As shown in Fig. 1, the material removal process in FTS machining is not only governed by the cutting tool, machine design, the band width and stroke of the FTS, the synchronization of the cutting tool vibration with the spindle rotation (see Fig. 2), and cutting conditions; but also critically affected by the properties of materials, the tool geometry, and the geometry of the optical microstructures that are being cut.
The surface topography model takes into account the cutting mechanics, material factors, kinematics, and dynamic characteristics of the cutting processes.
Lee: Proceedings of The Institute of Mechanical Engineers, Part B, Journal of Engineering Manufacture, Vol.214 (2000) No.B6, pp.463-480
Lee: JSME International Journal-Series C: Mechanical Systems, Machine Elements and Manufacturing, Vol. 43 (2000) No.1, pp.116-126.

In a second stage, a representative sample of the affected area was analyzed and thoroughly evaluated.
This radiation, defined by the Stefan-Boltzmann law [17], is proportional to body temperature and the thermal properties of the material.
Ultrasonics is based on the acoustic properties of the material.
Sound wood: From the dynamic elasticity modulus (Ed) a correlation (eq. 3) with elastic properties determined by bending tests (MOE) is obtained.
“Timber in buildings: Estimation of some properties using Pilodyn® and Resistograph®” Proceedings of the XII DBMC, International Conference on Durability of Building Materials and Components, Porto, Portugal, April 2011

The small particle size distributions in nanoemulsion resulted the good properties of nanoemulsion in term of large surface area.
Surfactant can produce, modify or control the foam, compatibilize the formulation components and modifying the viscosity of the fluid properties.
Graves, “Nanoemulsion:formation, structure and physical properties”, Journal of Physic: Condensed Matter, vol 18, pp.
Do, “Determination of factors controlling the particle size in nanoemulsions using artificial neural networks”, Eur.J.Pharm.Sci. vol. 35, pp. 42-51, 2008
Fahmy, "Factors influencing the recovery of petroleum from unconsolidated sands by waterflooding, SPE 927318-G Transactions of the American Institute of Mining, Metallurgical and Petroleum engineers, pp. 318-335, 1927