Ulcerative colitis(UC) is a chronic inflammatory bowel condition characterised by a relapsing and remitting course. Symptom control has been the traditional mainstay of medical treatment. It is well known that histolo...Ulcerative colitis(UC) is a chronic inflammatory bowel condition characterised by a relapsing and remitting course. Symptom control has been the traditional mainstay of medical treatment. It is well known that histological inflammatory activity persists despite adequate symptom control and absence of endoscopic inflammation. Current evidence suggests that presence of histological inflammation poses a greater risk of disease relapse and subsequent colorectal cancer risk. New endoscopic technologies hold promise for developing endoscopic markers of mucosal inflammation. Achieving endoscopic and histological remission appears be the future aim of medical treatments for UC. This review article aims to evaluate the use of endoscopy as a tool in assessment of mucosal inflammation UC and its correlation with disease outcomes.展开更多
It is more difficult to retrieve land surface temperature(LST) from passive microwave remote sensing data than from thermal remote sensing data, because the emissivities in the passive microwave band can change more e...It is more difficult to retrieve land surface temperature(LST) from passive microwave remote sensing data than from thermal remote sensing data, because the emissivities in the passive microwave band can change more easily than those in the thermal infrared band. Thus, it is very difficult to build a stable relationship. Passive microwave band emissivities are greatly influenced by the soil moisture, which varies with time. This makes it difficult to develop a general physical algorithm. This paper proposes a method to utilize multiple-satellite, sensors and resolution coupled with a deep dynamic learning neural network to retrieve the land surface temperature from images acquired by the Advanced Microwave Scanning Radiometer 2(AMSR2), a sensor that is similar to the Advanced Microwave Scanning Radiometer Earth Observing System(AMSR-E). The AMSR-E and MODIS sensors are located aboard the Aqua satellite. The MODIS LST product is used as the ground truth data to overcome the difficulties in obtaining large scale land surface temperature data. The mean and standard deviation of the retrieval error are approximately 1.4° and 1.9° when five frequencies(ten channels, 10.7, 18.7, 23.8, 36.5, 89 V/H GHz) are used. This method can effectively eliminate the influences of the soil moisture, roughness, atmosphere and various other factors. An analysis of the application of this method to the retrieval of land surface temperature from AMSR2 data indicates that the method is feasible. The accuracy is approximately 1.8° through a comparison between the retrieval results with ground measurement data from meteorological stations.展开更多
文摘Ulcerative colitis(UC) is a chronic inflammatory bowel condition characterised by a relapsing and remitting course. Symptom control has been the traditional mainstay of medical treatment. It is well known that histological inflammatory activity persists despite adequate symptom control and absence of endoscopic inflammation. Current evidence suggests that presence of histological inflammation poses a greater risk of disease relapse and subsequent colorectal cancer risk. New endoscopic technologies hold promise for developing endoscopic markers of mucosal inflammation. Achieving endoscopic and histological remission appears be the future aim of medical treatments for UC. This review article aims to evaluate the use of endoscopy as a tool in assessment of mucosal inflammation UC and its correlation with disease outcomes.
基金Under the auspices of National Natural Science Foundation of China(No.41571427)National Key Project of China(No.2016YFC0500203)Open Fund of State Key Laboratory of Remote Sensing Science(No.OFSLRSS 201515)
文摘It is more difficult to retrieve land surface temperature(LST) from passive microwave remote sensing data than from thermal remote sensing data, because the emissivities in the passive microwave band can change more easily than those in the thermal infrared band. Thus, it is very difficult to build a stable relationship. Passive microwave band emissivities are greatly influenced by the soil moisture, which varies with time. This makes it difficult to develop a general physical algorithm. This paper proposes a method to utilize multiple-satellite, sensors and resolution coupled with a deep dynamic learning neural network to retrieve the land surface temperature from images acquired by the Advanced Microwave Scanning Radiometer 2(AMSR2), a sensor that is similar to the Advanced Microwave Scanning Radiometer Earth Observing System(AMSR-E). The AMSR-E and MODIS sensors are located aboard the Aqua satellite. The MODIS LST product is used as the ground truth data to overcome the difficulties in obtaining large scale land surface temperature data. The mean and standard deviation of the retrieval error are approximately 1.4° and 1.9° when five frequencies(ten channels, 10.7, 18.7, 23.8, 36.5, 89 V/H GHz) are used. This method can effectively eliminate the influences of the soil moisture, roughness, atmosphere and various other factors. An analysis of the application of this method to the retrieval of land surface temperature from AMSR2 data indicates that the method is feasible. The accuracy is approximately 1.8° through a comparison between the retrieval results with ground measurement data from meteorological stations.
