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Abstract:Irrigation is crucial to agriculture in arid and semi-arid areas and significantly contributes to crop development, food diversity and the sustainability of agro-ecosystems. For a specific crop, the separation of its irrigated and rainfed areas is difficult, because their phenology is similar and therefore less distinguishable, especially when there are phenology shifts due to various factors, such as elevation and latitude. In this study, we present a simple, but robust method to map irrigated and rainfed wheat areas in a semi-arid region of China. We used the Normalized Difference Vegetation Index (NDVI) at a 30ˆ30 m spatial resolution derived from the Chinese HJ-1A/B (HuanJing(HJ) means environment in Chinese) satellite to create a time series spanning the whole growth period of wheat from September 2010 to July 2011. The maximum NDVI and time-integrated NDVI (TIN) that usually exhibit significant differences between irrigated and rainfed wheat were selected to establish a classification model using a support vector machine (SVM) algorithm. The overall accuracy of the Google-Earth testing samples was 96.0%, indicating that the classification results are accurate. The estimated irrigated-to-rainfed ratio was 4.4:5.6, close to the estimates provided by the agricultural sector in Shanxi Province. Our results illustrate that the SVM classification model can effectively avoid empirical thresholds in supervised classification and realistically capture the magnitude and spatial patterns of rainfed and irrigated wheat areas. The approach in this study can be applied to map irrigated/rainfed areas in other regions when field observational data are available.

Cerebral hemorrhage, a difficult issue in clinical practice, is often detected and studied with computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). However, these expensive devices are not readily available in economically underdeveloped regions, and hence are unable to provide bedside and emergency on-site monitoring. The magnetic inductive phase shift (MIPS) is an emerging technology that may become a new tool to detect cerebral hemorrhage and to serve as an inexpensive partial substitute to medical imaging. In order to study a wider band of cerebral hemorrhage MIPS and to provide more useful information for measuring cerebral hemorrhage, we established a cerebral hemorrhage magnetic induction phase shift spectroscopy (MIPSS) detection system. Thirteen rabbits with five cerebral hemorrhage states were studied using a single coil-coil within a 1 MHz-200 MHz frequency range in linear sweep. A feature band (FB) with the highest detection sensitivity and the greatest stability was selected for further analysis and processing. In addition, a maximum conductivity cerebrospinal fluid (CSF) MRI was performed to verify and interpret the MIPSS result. The average phase shift change induced by a 3 ml injection of autologous blood under FB was -7.7503° ± 1.4204°, which was considerably larger than our previous work. Data analysis with a non-parametric statistical Friedman M test showed that in the FB, MIPSS could distinguish the five states of cerebral hemorrhage in rabbits, with a statistical significance of p<0.05. A B-F distribution profile was designed according to the MIPSS under FB that can provide instantaneous diagnostic information about the cerebral hemorrhage severity from a single set of measurements. The results illustrate that the MIPSS detection method is able to provide a new possibility for real-time monitoring and diagnosis of the severity of cerebral hemorrhage.

Obstructive sleep apnea (OSA), manifested by exposure to chronic intermittent hypoxia (CIH) and excess production of reactive oxygen species (ROS) in the airways, is associated with hyperreactive airway diseases. ROS, particularly when created by NADPH oxidase, are known to sensitize lung vagal C fibers (LVCFs), which may contribute to airway hypersensitivity pathogenesis. We investigated whether CIH augments the reflex and afferent responses of LVCFs to chemical stimulants and the roles of ROS and NADPH oxidase in such airway hypersensitivity. Rats were exposed to room air (RA) or CIH with/without daily treatment with MnTMPyP (a superoxide anion scavenger), apocynin (an NADPH oxidase inhibitor), or vehicle. At 16 h after their last exposure, intravenous capsaicin, adenosine, or α,β-methylene-ATP evoked an augmented apneic response in anesthetized rats with 14-days CIH exposure, compared to anesthetized rats with 14-days RA exposure. The augmented apneic responses to these LVCF stimulants were abolished by bilateral vagotomy or perivagal capsaicin treatment, which block LVCFs neural conduction and were significantly suppressed by treatment with MnTMPyP or apocynin, but not vehicle. Electrophysiological studies revealed that 14-days CIH exposure potentiated the responses of LVCFs to these stimulants. This effect was inhibited by treatment with MnTMPyP or apocynin treatment and was not seen in rats who received 7-days of CIH exposure. Biochemical analysis indicated that 14-days CIH exposure increased both lung lipid peroxidation, which is indicative of oxidative stress, and expression of the p47phox subunit in the membrane fraction of lung tissue, which is an index of NADPH oxidase activation. The former was prevented by treatment with either MnTMPyP or apocynin, while the later was prevented by treatment with apocynin only. These results suggest that 14-days CIH exposure sensitizes LVCFs in rats, leading to an exaggerated reflex and afferent responses to stimulants and that this sensitization is mediated via ROS generated by NADPH oxidase.

The negative impact of rapid urbanization in developing countries has led to a deterioration of urban and regional air quality. Much attention has been given to the impact of fine particulate pollution on urban public health. However, very little attention has been given to its impact on the regional ecosystem such as the agricultural ecosystem. Thus, we evaluate the direct impact of air pollution on the reduction of wheat photosynthesis by fine particulate matter (PM) pollution in the world's most heavily polluted area, the North China Plain, using remote sensing observations and ground measurements. We found the following to be true: (1) Heavy PM pollution could significantly reduce wheat photosynthesis and cause an expositional relationship between the PM concentration and wheat photosynthesis (R = 0.9824, P < 0.05); (2) Heavy PM pollution makes up 2% for the reduction in wheat photosynthesis at all wheat-plant farmlands in the North China Plain, approximately covering an area of 354,400 km; (3) Increasing heavy PM pollution significantly reduced wheat photosynthesis by 87% in wheat-planted farmland during 1999-2011. We hope the results presented here could draw attention to the effect of PM pollution on the agricultural ecosystem and encourage further studies to evaluate the feedback of atmospheric pollution on the agricultural ecosystem using remote sensing. Abbreviation: Northern China Plain (NCP); normalized difference vegetation index (NDVI); The Moderate Resolution Imaging Spectroradiometer (MODIS); fine particulate matter (PM).