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We report on earthquake and temperature-related velocity changes in high-frequency autocorrelations of ambient noise data from seismic stations of the Integrated Plate Boundary Observatory Chile project in northern Chile. Daily autocorrelation functions are analyzed over a period of 5 years with passive image interferometry. A short-term velocity drop recovering after several days to weeks is observed for the Mw 7.7 Tocopilla earthquake at most stations. At the two stations PB05 and PATCX, we observe a long-term velocity decrease recovering over the course of around 2 years. While station PB05 is located in the rupture area of the Tocopilla earthquake, this is not the case for station PATCX. Station PATCX is situated in an area influenced by salt sediment in the vicinity of Salar Grande and presents a superior sensitivity to ground acceleration and periodic surface-induced changes. Due to this high sensitivity, we observe a velocity response of several regional earthquakes at PATCX, and we can show for the first time a linear relationship between the amplitude of velocity drops and peak ground acceleration for data from a single station. This relationship does not hold true when comparing different stations due to the different sensitivity of the station environments. Furthermore, we observe periodic annual velocity changes at PATCX. Analyzing data at a temporal resolution below 1 day, we are able to identify changes with a period of 24 h, too. The characteristics of the seismic velocity with annual and daily periods indicate an atmospheric origin of the velocity changes that we confirm with a model based on thermally induced stress. This comprehensive model explains the lag time dependence of the temperature-related seismic velocity changes involving the distribution of temperature fluctuations, the relationship between temperature, stress and velocity change, plus autocorrelation sensitivity kernels.

A method is described for identifying tumor tissue by means of FTIR microspectroscopy and positron emission tomography (PET). Thin tissue sections of human squamous carcinoma from hypopharynx (FaDu) and human colon adenocarcinoma (HT-29) grown in nude mice were investigated. FTIR spectroscopic maps of the thin tissue sections were generated and evaluated by Fuzzy C-Means (FCM) clustering and principal component analysis (PCA). The processed data were reassembled into images and compared to stained tissue samples and to PET. Tumor tissue could successfully be identified by this FTIR microspectroscopic method, while it was not possible to accomplish this with PET alone. On the other hand, PET permitted the non-invasive screening for suspicious tissue inside the body, which could not be achieved by FTIR.