Analysis of exhaled VOCs from health and patients may help building association between VOCs and different diseases condition, which could offer a possibility of noninvasive monitoring of disease. VOCs were collected in 30 healthy subjects and 60 patients with upper respiratory tract infection. Analysis of 97 VOCs was
performed by gas chromatography and mass spectrometry (GC-MS). The concentration of alkanes, alkenes, halogenated hydrocarbon, oxygenated hydrocarbons and aromatic hydrocarbons in health and patients breath was analyzed. Analysis of variance (ANOVA), principal component analysis (PCA) were used to analyze the VOC differences from patients and healthy ones. The results show that the concentration of isoprene differ among patients, healthy ones and indoor air (P<0.05). Patients show higher concentration of n-pentane compared to healthy ones (P<0.05). Patients with bacterial upper respiratory tract infection show higher concentration of propanal compared to healthy ones. The results of PCA show that there were significant VOC differences between patients with upper respiratory tract infection and healthy ones (P=0.019), but no differences between bacterial and non-bacterial upper respiratory tract infection.

Taking erectophile type continuous vegetation as a example, authors had done many Monte Carlo simulations, and established empirical analytic expressions of radiances with component temperature, soil emissivity and leaf area index. Empirical analytic expressions were used to construct objective function and genetic algorithm was employed to synchronously retrieve 5 parameters, such as component temperature, soil emissivity and LAI, from thermal infrared 2 channels and 2 angles data. Many experiments of genetic algorithm inversion from simulated data were conducted, results show that it is very robust to retrieve component temperature using genetic algorithm；genetic algorithm can cope with uncertainty inversion problem pretty well if full advantage of priori knowledge was taken.Comparison between inversion results and ground-truth data has been done. This paper offers a new example to retrieve component temperature from multi-channel, multi-angle thermal infrared data based on the model of directionality of thermal radiance.

A new method was offered to retrieve component temperature of mixed pixel with multi-angle thermal infrared data based on the law of directionality of thermal radiance of mixed pixel. To take continuous vegetation canopy as an example, the correlation coefficients among multi-angle thermal infrared data are less than their counterpart of multi-channel which mainly depend on the distribution function of leaf angle(LAD), therefore, it is easier to keep accuracy of retrieved component temperature within 1K than its counterpart.