ALBERT

Description: Aiming to implement image segmentation precisely and efficiently, we exploit new ways to encode images and achieve the optimal thresholding on quantum state space. Firstly, the state vector and density matrix are adopted for the representation of pixel intensities and their probability distribution, respectively. Then, the method based on global quantum entropy maximization (GQEM) is proposed, which has an equivalent object function to Otsu’s, but gives a more explicit physical interpretation of image thresholding in the language of quantum mechanics. To reduce the time consumption for searching for optimal thresholds, the method of quantum lossy-encoding-based entropy maximization (QLEEM) is presented, in which the eigenvalues of density matrices can give direct clues for thresholding, and then, the process of optimal searching can be avoided. Meanwhile, the QLEEM algorithm achieves two additional effects: (1) the upper bound of the thresholding level can be implicitly determined according to the eigenvalues; and (2) the proposed approaches ensure that the local information in images is retained as much as possible, and simultaneously, the inter-class separability is maximized in the segmented images. Both of them contribute to the structural characteristics of images, which the human visual system is highly adapted to extract. Experimental results show that the proposed methods are able to achieve a competitive quality of thresholding and the fastest computation speed compared with the state-of-the-art methods.

Description: This paper carried out burst tests on the carbon and polyvinyl alcohol (PVA) fiber high-strength concrete specimens to investigate the effects of fiber type, fiber content, water content, heating rate and test specimen size on the burst, and the whole burst process of fiber-high concrete was photographed and recorded. The results indicated that fiber addition will improve the high temperature burst behavior of the high-strength concrete, and the performance of PVA is greatly different from that of carbon fiber. The water content and heating rate have little influence on the burst of the PVA test specimen, but they will greatly affect the carbon fiber test specimen. The size of the test specimen has a great influence on the burst. For the PVA concrete test specimen, the large size test specimen bursts on the surface; as for the carbon fiber test specimen, the large size test specimen delays the initial burst time, but the burst becomes fiercer.

Description: The evapotranspiration (ET) of urban hedges has been assumed to be an important component of the urban water budget and energy balance for years. However, because it is difficult to quantify the ET rate of urban hedges through conventional evapotranspiration methods, the ET rate, characteristics, and the cooling effects of urban hedges remain unclear. This study aims to measure the ET rate and quantify the cooling effects of urban hedges using the ‘three-temperature model + infrared remote sensing (3T + IR)’, a fetch-free and high-spatiotemporal-resolution method. An herb hedge and a shrub hedge were used as field experimental sites in Shenzhen, a subtropical megacity. After verification, the ‘3T + IR’ technique was proven to be a reasonable method for measuring the ET of urban hedges. The results are as follows. (1) The ET rate of urban hedges was very high. The daily average rates of the herb and shrub hedges were 0.38 mm·h−1 and 0.33 mm·h−1, respectively, on the hot summer day. (2) Urban hedges had a strong ability to reduce the air temperature. The two hedges could consume 68.44% and 60.81% of the net radiation through latent heat of ET on the summer day, while their cooling rates on air temperature were 1.29 °C min−1 m−2 and 1.13 °C min−1 m−2, respectively. (3) Hedges could also significantly cool the urban underlying surface. On the summer day, the surface temperatures of the two hedges were 19 °C lower than that of the asphalt pavement. (4) Urban hedges had markedly higher ET rates (0.19 mm·h−1 in the summer day) and cooling abilities (0.66 °C min−1 m−2 for air and 9.14 °C for underlying surface, respectively) than the lawn used for comparison. To the best of our knowledge, this is the first research to quantitatively measure the ET rate of urban hedges, and our findings provide new insight in understanding the process of ET in urban hedges. This work may also aid in understanding the ET of urban vegetation.

Description: True-color three-dimensional (3D) imaging exploits spatial and spectral information and can enable accurate feature extraction and object classification. The existing methods, however, are limited by data collection mechanisms when realizing true-color 3D imaging. We overcome this problem and present a novel true-color 3D imaging method based on a 32-channel hyperspectral LiDAR (HSL) covering a 431–751 nm spectral range. We conducted two experiments, one with nine-color card papers and the other with seven different colored objects. We used the former to investigate the effect of true-color 3D imaging and determine the optimal spectral bands for compositing true-color, and the latter to explore the classification potential based on the true-color feature using polynomial support vector machine (SVM) and Gaussian naive Bayes (NB) classifiers. Since using all bands of HSL will cause color distortions, the optimal spectral band combination for better compositing the true-color were selected by principal component analysis (PCA) and spectral correlation measure (SCM); PCA emphasizes the amount of information in band combinations, while SCM focuses on correlation between bands. The results show that the true-color 3D imaging can be realized based on HSL measurements, and three spectral bands of 466, 546, and 626 nm were determined. Comparing reflectance of the three selected bands, the overall classification accuracy of seven different colored objects was improved by 14.6% and 8.25% based on SVM and NB, respectively, classifiers after converting spectral intensities into true-color information. Overall, this study demonstrated the potential of HSL system in retrieving true-color and facilitating target recognition, and can serve as a guide in developing future three-channel or multi-channel true-color LiDAR.

Description: The ecosystem of extra-high mountain areas is very fragile. Understanding local vegetation changes is crucial for projecting ecosystem dynamics. In this paper, we make a case for Himalayan mountain areas to explore vegetation dynamics and their influencing factors. Firstly, the interannual trends of the normalized difference vegetation index (NDVI) were extracted by the Ensemble Empirical Mode Decomposition (EEMD) algorithm and linear regression method. Moreover, the influence of environmental factors on interannual NDVI trends was assessed using the Random Forests algorithm and partial dependence plots. Subsequently, the time-lag effects of seasonal NDVI on different climatic factors were discussed and the effects of these factors on seasonal NDVI changes were determined by partial correlation analysis. The results show that (1) an overall weak upward trend was observed in NDVI variations from 1982 to 2015, and 1989 is considered to be the breakpoint of the NDVI time series; (2) interannual temperature trends and the shortest distance to large lakes were the most important factors in explaining interannual NDVI trends. Temperature trends were positively correlated with NDVI trends. The relationship between the shortest distance to large lakes and the NDVI trend is an inverted U-shaped; (3) the time-lags of NDVI responses to four climatic factors were shorter in Autumn than that in Summer. The NDVI responds quickly to precipitation and downward long-wave radiation; (4) downward long-wave radiation was the main climate factor that influenced NDVI changes in Autumn and the growing season because of the warming effect at night. This study is important to improve the understanding of vegetation changes in mountainous regions.

Description: To reveal the effects of Asian dust and phosphorus (P) input on the structure and function of micro-food web in the Yellow Sea, an experiment was conducted onboard the southern Yellow Sea where P was deficient. The response of the abundance and trophic structure of planktonic protists to different concentrations of dust and P were studied. The results showed that the sand-dust deposition presented variable effects on different sizes of protists during incubation periods. At the initial stage of incubation with dust, the amount of all sizes of autotrophic protists, especially 10–20 µm, were improved; on the contrary, the heterotrophic and mixotrophic protists were inhibited. At the late period, the increase of autotrophic protists was restricted, while the 2–5 µm heterotrophic and mixotrophic protists obviously increased. Similarly, adding P demonstrated the obviously positive effect on the 10–20 µm autotrophic protists at the initial period, and then the growth was restricted at the late period. These results were consistent with that of sand-dust deposition. Hence, it could be presumed that the positive effect of sand-dust deposition on autotrophic protists in the southern Yellow Sea was achieved by the release of P from dust. P in the early stage of sand-dust deposition promotes the growth of large-size autotrophic protists, which may accelerate red tides in eutrophic ocean. The stimulation of small-size heterotrophic protists at the late period of sand-dust deposition contributed to the material cycle and food transmission in the ocean. Therefore, the effects of sand-dust deposition on the abundance and trophic structure of different sizes of planktonic protists could change the structure of micro-food web in the southern Yellow Sea and further affected the ecological function of planktonic protists.

Description: The carbon emission problem in China needs to be solved urgently. Industrial symbiosis, as an effective means to improve resource efficiency, can better alleviate the carbon emission problem. Under such a circumstance, this paper regards an industrial symbiosis system as a collection of producers, consumers and decomposers, and analyzes the strategic selections and behavioral characteristics of their carbon emission reduction activities through a tripartite evolutionary game model, and then the effects of related parameters on the evolutionary stable strategies of stakeholders are discussed. The results demonstrate that: (1) the regular return and the rate of return determine the ability of stakeholders to undertake carbon reduction activities; (2) the initial willingness of stakeholders to participate will affect the evolutionary speed of the strategies; (3) a high opportunity cost reduces the inertia of stakeholders to carry out carbon emission reductions; (4) producers, consumers and decomposers can avoid “free rides” by signing agreements or adopting punitive measures.