The mitigation effects of park green space on Urban Heat Island (UHI) have been extensively documented. However, the relative effects of the configuration of park components on land surface temperature (LST) inside the park and indicators (i.e., park cooling intensity and distance) surrounding the park is largely unknown. Therefore, the main objective of this study is to explore the quantitative impacts of configuration and morphology features under different urban park scales on the cooling effect. In this study, based on Landsat-8 OLI/TIRS images on 3 August 2015 and 16 August 2020 during summer daytime, the LSTs of Shanghai City were retrieved by atmospheric correction method. Then, the relationships of park landscape features with LSTs in the park and typical indicators representing cooling efficiency of 24 parks on different grades were analyzed. The results showed that the average temperature in urban parks was, respectively, 1.46 °C and 1.66 °C lower than that in the main city of Shanghai in 2015 and 2020, suggesting that urban parks form cold islands in the city. The landscape metrics of park area (PA), park perimeter (PP), green area (GA) and water area (WA), were key characteristics that strong negatively affect the internal park LSTs. However, the park perimeter-to-area ratio (PPAR) had a significant positive power correlation with the park LSTs. Buffer zone analysis showed that LST cools down by about 0.67 °C when the distance from the park increases by 100 m. The Maximum Cooling Distance (MCD) for 2015 and 2020 had a significant correlation with PA, PC, PPAR, GA and WA, and increased sharply within the park area of 20 ha. However, the medium park group had the largest Maximum Cooling Intensity (MCI) in both periods, followed by the small park group. There could be a trade-off relationship between the MCD and MCI in urban parks, which is worth pondering to research. This study could be of great significance for planning and constructing park landscapes, alleviating Urban Heat Island effect and improving urban livability.

Accurately detecting and locating the center of the tropical cyclone is critical for the trajectory forecasting. This study proposed an automatic method for centers’ location of the tropical cyclones based on the visible or the infrared satellite images. The morphological structure of the tropical cyclone is modeled using the circular pattern. The tropical cyclone center is located based on regional pixels instead of skeleton points. All pixels in a segmented cloud cluster vote for a 2-dimensional accumulator. The center of the cloud cluster is computed by the mean voting distances, which are calculated by fitting quadratic functions in every column of the two-dimensional (2D) accumulator. Then, a linear function is fitted according to the functional relationship between the mean voting distance and voting angle. The fitted coefficients of the linear function are the center coordinates of the tropical cyclone. The proposed method for centers location of the tropical cyclones is tested using visible and infrared satellite images. The results of center location are compared with the best track provided in JMA datasets.

Capillary electrophoresis (CE) is a versatile analytical separation method in the field of biochemistry. Although it has been proved that the relative molecular mass (M_r) of the polymers determines the threshold concentration of the entangled polymer solution, which will affect the separation performance of DNA molecules, there is still no report on the effect of M_r on the separation performance of proteins. Herein, we have thoroughly performed the CE of proteins ranged from 14.3 kDa to 116 kDa in a mixed hydroxyethyl cellulose (HEC) solution. The mixed solution was obtained with various M_r including 90,000, 250,000, 720,000, and 1,300,000. Then, we found that the mixed polymer provided a high resolution for small protein molecules while increasing the efficiency of large ones. Results demonstrated that the migration time decreased if HEC (1,300,000) was mixed with the lower M_r one, and the mixed solution (1,300,000/250,000) offered the highest resolution. The resolution was negatively correlated with the electric field strength. Finally, we have employed the optimal electrophoretic conditions to separate proteins in human tears, and it showed that lysozyme, lipocalin, and lactoferrin from human tears were successfully resolved in the mixed HEC. Such work indicates that CE has the potential to be developed as a tool for the diagnosis of xerophthalmia, meibomian gland dysfunction, or other eye diseases.

The Tropical cyclones usually refer to low-pressure eddies that rotate rapidly in the tropics. It seriously threatens the life and property safety,Therefore, the prediction of both the accurate location of the tropical cyclone center and the tropical cyclone path is the key to preventing tropical cyclone disasters. In this paper, a fast method for calculating the center of tropical cyclone using infrared satellite image or visible satellite image is proposed. A two-dimensional Gaussian normal distribution model is used to simulate the gray characteristics of tropical cyclone images. The gray distribution of tropical cyclone satellite image approximates to a two-dimensional Gaussian distribution. In multiple directions, the pixel gray values of tropical cyclone are accumulated, and a set of one-dimensional Gaussian normal distribution functions are used to fit these accumulated values. The peak positions of these one-dimensional Gaussian functions are calculated by derivation. Then, a linear function is fitted according to the relationship between the peak position of the group of Gaussian functions and the selected angle. The coefficient of the fitting linear function is exactly the central coordinate of the tropical cyclone. The proposed method for locating the center of tropical cyclone is tested using visible and infrared satellite images. The results are compared with the best trajectory provided by the Japan Meteorological Agency.