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Fallopia multiflora (Thunb.) Harald, a traditional Chinese medicinal plant, is used in treating dizziness. In this study, the samples of F. multiflora from ten different locations were collected, and five bioactive components (2, 3, 5, 4′-tetrahydroxystilbene-2-O-β-D-glucoside, emodin, emodin-8-O-β-D-glucoside, physcion and physcion-8-O-β-D-glucoside) were quantified by high performance liquid chromatography. The correlations between 17 environmental factors and 5 bioactive components were analyzed. The results showed that the highest contents of bioactive components were in samples from Deqing, and the lowest in samples from Tianyang, which indicated that the quality of F. multiflora grown in Deqing was superior, while that grown in Tianyang was inferior. Emodin content was negatively correlated with the average temperature in January (p < 0.01) and the accumulated temperature (p < 0.01). Physician content was also negatively correlated with the average temperature in January (P < 0.01), the accumulated temperature (p < 0.05) and the organic matter (p < 0.05). However, emodin was positively correlated with the soil available K (p < 0.05) and Zn (p < 0.01). The results of stepwise regression showed that the accumulated temperature was the main factor influencing the contents of emodin and physcion. However, none of the environmental factors had significant correlation with 2, 3, 5, 4′-tetrahydroxystilbene-2-O-β-D-glucoside, emodin-8- O-β-D-glucoside and physcion-8-O-β-D-glucoside. In conclusion, some environmental factors have significant influence on the content of dissociated anthraquinones, while some have no influence on that of combined anthraquinones.

We propose a model selection method to estimate the relation of multiple SNPs, environmental factors and the binary disease trait. We applied the combination of logistic regression and genetic algorithm for this study. The logistic regression model can capture the continuous effects of environments without categorization, which causes the loss of the information. To construct an accurate prediction rule for binary trait, we adopted Akaike's information criterion (AIC) to find the most effective set of SNPs and environments. That is, the set of SNPs and environments that gives the smallest AIC is chosen as the optimal set. Since the number of combinations of SNPs and environments is usually huge, we propose the use of the genetic algorithm for choosing the optimal SNPs and environments in the sense of AIC. We show the effectiveness of the proposed method through the analysis of the case/control populations of diabetes, Alzheimer's disease and obesity patients. We succeeded in finding an efficient set to predict types of diabetes and some SNPs which have strong interactions to age while it is not significant as a single locus.

Lighting policies and the influence of light colour parameters on humans and the environment are complex. The opinions of experts and the optimisation of night-time lighting policies create a suitable nightscape that satisfies users’ needs and minimises environmental impacts. This study aims to provide a nightscape design policy for outdoor spaces considering environmental factors. This evaluation can provide multidisciplinary policy recommendations and evaluate the position of environmental considerations in human-centred lighting design. Initially, the factors affecting the night landscape are identified and priorities are subsequently determined on a smaller scale based on the typology of Tehran’s nightscape. The data output from these prioritisations is used to develop how the lights in the night landscape can be improved for various spatial typologies. Finally, a human and environment-friendly conceptual model is developed.