The load type imposed on the structures is one of the important issues of the modal identification Experimental methods. Generally the loads applied to a structure for dynamic testing are divided into two categories: artificial stimulation and ambient loads. Applying artificial loads to large structures such as bridges and tall buildings is difficult, costly and in some cases impossible. For this reason, modal identification of such structures is generally done by ambient vibration tests. However this experimental methods, also include problems such as large noise amplitude relative to the measured responses that this causes errors in the results and in some cases leads to unrealistic modes. As a solution, modal information can be calculated from several different methods and compared with each other to ensure the accuracy of the results. In this paper, a new scheme for natural frequencies extraction of structures from their ambient vibration is presented. For this purpose, the combination of two mathematical techniques of random decrement (RD) and proper orthogonal decomposition (POD) methods were used. The reason for using these two methods, is their ability to reduce the noise effects. In other words, combining of these two methods can lead to a very powerful tool for extracting structural frequencies from its ambient vibration under high amplitude noise conditions. The proposed algorithm consists of three steps: In the first step, after measuring the acceleration response of the structure at the appropriate points, the effects of random vibration are eliminated from the response by RD method and only dynamic properties of the structure remain in the acceleration records. Secondly, the acceleration records are separated into several structural modes using the proper orthogonal decomposition technique and finally, at the last step, the proceeded responses are transformed by the fast Fourier transform into the frequency domain to extract the natural frequencies of the structure. The strength of the proposed method is its robustness to the use of very high amplitude noise data, which is one of the challenges in the ambient vibration experiments. The accuracy of the proposed algorithm was evaluated by numerical modeling and experimental study. To investigate the efficiency of the new method, the numerical and experimental results were compared with the frequencies obtained from commonly modal identification methods such as extended frequency domain decomposition (EFDD) and stochastic subspace identification (SSI). A very good agreement was observed between the results of methods. Furthermore, Studying the effect of noise on the new algorithm results shows that increasing the ratio of noise to acceleration amplitude up to 250, did not affect the results precision and the main frequencies of the structure can be obtained with good accuracy. In this study, the effect of the number of sensors used in the ambient vibration test also was investigated on the accuracy of the new algorithm results. It was concluded that the minimum number of sensors (even one number) and repetition of the experiment can be used to extract structural frequencies from its ambient vibration with high accuracy. The results of this study showed that the new method can be used as a suitable tool to determine the natural frequencies of structures from its ambient vibration under severe noise conditions and to control the results obtained from other methods.

Aims: Melanoma is one of the most dangerous forms of skin cancer, which is unresponsive to the current chemotherapy drugs. As a natural product purified from spirulina, phycocyanin can inhibit the angiogenesis. The aim of this study was to investigate the anti-angiogenesis effect of C-phycocyanin of spirulina platensis on B16-F10 melanoma tumors in C57BL/6 mouse.
Materials and Methods: In this experimental study, 16 C57BL/6 mice with the age range of 6-8 weeks were randomly divided into two groups, including control and phycocyanin groups. On the day 0 of the study, melanoma cells were injected and all the mice were treated for 20 days. Phycocyanin group received 40mg/kg phycocyanin every day. The tumors were extracted on the day 21 and the effect of phycocyanin on the angiogenesis and proliferation of cancer cells was investigated, using immunohistochemical staining with CD31 and Ki-67, respectively. The data were analyzed, using JMP 11 software by one way ANOVA test.
Findings: In the phycocyanin group, angiogenesis was significantly lower than that of the control group (p<0.01), while the mitotic index was not significantly lower than that of the control group in the mice treated with phycocyanin.
Conclusion: Phycocyanin has ability to inhibit angiogenesis in the B16-F10 melanoma tumors in C57BL/6 mouse, but it is not able to reduce the proliferation of melanoma cells.