ALICE is the heavy-ion experiment at the CERN Large Hadron Collider. The experiment continuously took data during the first physics campaign of the machine from fall 2009 until early 2013, using proton and lead-ion beams. In this paper we describe the running environment and the data handling procedures, and discuss the performance of the ALICE detectors and analysis methods for various physics observables.

Thermal properties of ex vivo bovine liver were measured as a function of temperature, by heating tissue samples in a temperature-controlled oil bath over a temperature range from about 21 °C to about 113 °C. Results evidenced temperature-dependent non-linear changes of the thermal properties, with the temperature of 100 °C representing a break point: the thermal properties increased with temperature up to 99 °C and then decreased above 100 °C. The rate of increase appeared dramatic between 90 °C and 99 °C, owing to the onset of vaporisation of water contained in the tissue. In particular, at 99 °C, the thermal conductivity reported an increase of about four times with respect to the value measured at 90 °C, whilst about a two-fold increase was reported for both the volumetric heat capacity and the thermal diffusivity. Temperatures higher than 100 °C were reached only after complete vaporisation of water contained in the tissue, resulting in about 70% loss of weight from the tissue. An overall decrease of about 71% and 63% was reported for the thermal conductivity and volumetric heat capacity, respectively, in the temperature range 101 °C–113 °C. A decrease of about 25% was reported in the measured values of the thermal diffusivity in the temperature range 101 °C–108 °C, whilst a slight increase of measured values, not statistically significant, was observed in the temperature range 108 °C–113 °C. The temperature dependent changes of the thermal parameters were modelled with non-linear regression analysis to calculate the best-fit curves interpolating measured data. The proposed regression models could be used to numerically assess the changes in the thermal properties of biological tissues at supra-physiological temperatures relevant in thermal ablation procedures, as well as their effect on the prediction of the ablation zone dimensions in computational models for treatment planning.

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