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Although the effects of phytohormones (mainly salicylic acid) on the storability of longan fruit have been reported, the relationship between postharvest hormone variation and signal transduction and storability remains unexplored. The basis of physiology, biochemistry, hormone content and signalling for the storability difference at room-temperature between ‘Shixia’ and ‘Luosanmu’ longan fruit were examined. ‘Luosanmu’ longan exhibited faster pericarp browning, aril breakdown and rotting during storage. ‘Luosanmu’ pericarp exhibited higher malondialdehyde but faster decreased total phenolics, flavonoid, glutathione, vitamin C, catalase activity and gene expression. Higher H2O2 and malondialdehyde but lower glutathione, glutathione-reductase and peroxidase activities, while higher activities and gene expressions of polygalacturonase, β-galactosidase and cellulose, lower covalent-soluble pectin, cellulose and hemicellulose but higher water-soluble pectin were observed in ‘Luosanmu’ aril. Lower abscisic acid and methyl jasmonate but higher expressions of LOX2, JAZ and NPR1 in pericarp, while higher abscisic acid, methyl jasmonate and salicylic acid together with higher expressions of ABF, JAZ, NPR1 and PR-1 in ‘Luosanmu’ aril were observed. In conclusion, the imbalance between the accumulation and scavenging of active oxygen in ‘Luosanmu’ longan might induce faster lipid peroxidation and senescence-related hormone signalling and further the polymerization of phenolics in pericarp and polysaccharide degradation in aril.

Rapid deduction based on environmental data has become a key factor influencing the early stages of conceptual design decisions. Traditional wind tunnels and CFD computational tools are time-consuming and number-limited of assumptions in iterative design, hence both are more commonly used in post-evaluation. With the development of artificial intelligence, this paper presented a new cyborg-physical wind tunnel (CPWT) design platform. By combining a customized physical wind tunnel with an optimization algorithm, a large amount of physical data can be quickly derived, and evaluations and predictions can be made. This paper first introduces the concepts of wind environment performance-based design including the physical platform design and the sensing system. The design methodology is reviewed in three sections: deduction framework, optimization goal, and evaluation indicator. Then, the paper proposed a new wind tunnel device, the CPWT, which incorporates 120 dynamic lifting units equipped with sensor, Arduino, and servomotor to capture wind data and generate real-time responses. Artificial neural network is integrated in the experiment to train on data like the windward area index and staggering index for the morphology generation. The result demonstrated that the mean square error is able to quickly stabilize to the range of [-0.02783, 0.02892] and [-2.324, 2.845], which achieved a lower data error and a better result predictability. The enhanced sensibility and real-time feedback are able to provide a more rapid method for the wind environment performance-based design in this digital age.

Along with the development of the landscape design and robotic technology, the traditional methods of the earthwork for the landscape can no longer adapt to highly artistic and customized landscape due to the overwhelming in term of time, effort and cost, as well as the low precision to conduct micro-level earthwork. Thus, the automation of the earthwork operations has been widely studied. This paper introduces an autonomous earthwork system which takes one or several robot agents to detect the difference between the initial terrain and the target terrain, and gradually shape the initial terrain toward the target terrain so that in the end the target terrain is formed from the initial terrain automatically. Different levels of intelligence are added to the system including path-optimizing with mathematic calculation, so that the robot agents are able to consider the factors of efficiency and time when they perform their function, and makes the system more precise and adaptable.

In the urbanization process, high-rise is favored and popularized, while results to the high-density urban space which aggravated the deterioration of urban wind environment. Using quantifiable environmental factors to control the building, is promoting a more meaningful group formation of the sustainable high-rise buildings. Thus, taking wind performance into account in high-rise design infancy is essential. According to the achievement of CAADRIA2018 “SELF-FORM-FINDING WIND TUNNEL TO ENVIRONMENTAL-PERFORMANCE URBAN AND BUILDING DESIGN” workshop, a preliminary set related to the environmental performance urban morphology generation system and method was constructed. In this study, various of high-rise building forms that might be conducive to urban ventilation were selected, such as “hollow-out”, “twisting”, “facade retracting” and “lift-up”, to design the Dynamic Model System with multi-dimensional motion.