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As the most basic travel mode of residents, walking trip takes place more frequently in residential districts. It is of great significance to study the land use characteristics of the residential district suitable for walking in order to create a good walking environment and land use model. In this paper, 18 residential blocks in Xi'an are taken as the research object, based on the relevant data of the pedestrian flow rate and land use of residential blocks, this paper analyzes the interactive relationship between the non-commuting hours during the week, the commuting hours during the week and the weekends by using the multiple linear regression model, and the land use characteristics of residential blocks under the guidance of walking trip are revealed. The results show that the land use factors related to pedestrian flow rate are mainly 9 factors, such as building density, buildings mixing degree, mixing degree of business functions and density of functional formats. In different hours, walking trips have different demands on various elements of land use. During the non-commuting hours during the week, the demand for walking trips for building density, mixing degree of business functions, density of functional formats and footpath area ratio is large. During the commuting hours during the week, the demand for walking trips for buildings mixing degree, density of functional formats, road network connectivity, and green area ratio of footpath is large. During the weekends, the demand for building density, density of functional formats, road network density, and footpath density is large. Through the above analysis, the optimization strategy is proposed for residential blocks in Xi 'an, which provides a theoretical basis for the optimization and transformation of the space environment of residential blocks to promote walking trip.

In recent advances, deep learning-based methods have been broadly applied in fault diagnosis, while most existing studies assume that source domain and target domain data follow the same distribution. As differences in operating conditions lead to the deterioration of diagnosis performance, domain adaptation technology has been introduced to bridge the distribution gap. However, most existing approaches generally assume that source domain labels are available under all health conditions during training, which is incompatible with the actual industrial situation. To this end, this paper proposes a semi-supervised adversarial transfer networks for cross-domain intelligent fault diagnosis of rolling bearings. Firstly, the Gramian Angular Field method is introduced to convert time domain vibration signals into images. Secondly, a semi-supervised learning-based label generating module is designed to generate artificial labels for unlabeled images. Finally, the dynamic adversarial transfer network is proposed to extract the domain-invariant features of all signal images and provide reliable diagnosis results. Two case studies were conducted on public rolling bearing datasets to evaluate the diagnostic performance. An experiment under variable operating conditions and an experiment with different numbers of source domain labels were carried out to verify the generalization and robustness of the proposed approach, respectively. Experiment results demonstrate that the proposed method can achieve high diagnosis accuracy when dealing with cross-domain tasks with deficient source domain labels, which may be more feasible in engineering applications than conventional methodologies.

Cassava (Manihot esculenta Crantz) is a root crop used as a foodstuff and as a starch source in industry. Starch functional properties are influenced by many structural features including the relative amounts of the two glucan polymers amylopectin and amylose, the branched structure of amylopectin, starch granule size and the presence of covalent modifications. Starch phosphorylation, where phosphates are linked either to the C3 or C6 carbon atoms of amylopectin glucosyl residues, is a naturally occurring modification known to be important for starch remobilization. The degree of phosphorylation has been altered in several crops using biotechnological approaches to change expression of the starch-phosphorylating enzyme GLUCAN WATER DIKINASE (GWD). Interestingly, this frequently alters other structural features of starch beside its phosphate content. Here, we aimed to alter starch phosphorylation in cassava storage roots either by manipulating the expression of the starch phosphorylating or dephosphorylating enzymes. Therefore, we generated transgenic plants in which either the wild-type potato GWD (StGWD) or a redox-insensitive version of it were overexpressed. Further plants were created in which we used RNAi to silence each of the endogenous phosphoglucan phosphatase genes STARCH EXCESS 4 (MeSEX4) and LIKE SEX4 2 (MeLSF), previously discovered by analyzing leaf starch metabolism in the model species Arabidopsis thaliana. Overexpressing the potato GWD gene (StGWD), which specifically phosphorylates the C6 position, increased the total starch-bound phosphate content at both the C6 and the C3 positions. Silencing endogenous LSF2 gene (MeLSF2), which specifically dephosphorylates the C3 position, increased the ratio of C3:C6 phosphorylation, showing that its function is conserved in storage tissues. In both cases, other structural features of starch (amylopectin structure, amylose content and starch granule size) were unaltered. This allowed us to directly relate the physicochemical properties of the starch to its phosphate content or phosphorylation pattern. Starch swelling power and paste clarity were specifically influenced by total phosphate content. However, phosphate position did not significantly influence starch functional properties. In conclusion, biotechnological manipulation of starch phosphorylation can specifically alter certain cassava storage root starch properties, potentially increasing its value in food and non-food industries.

Background Plant GSK-3/Shaggy-like kinases are key players in brassinosteroid (BR) signalling which impact on plant development and participate in response to wounding, pathogens and salt stress. Bikinin was previously identified in a chemical genetics screen as an inhibitor targeting these kinases. To dissect the structural elements crucial for inhibition of GSK- 3/Shaggy-like kinases by bikinin and to isolate more potent compounds we synthesised a number of related substances and tested their inhibitory activity in vitro and in vivo using Arabidopsis thaliana. Results A pyridine ring with an amido succinic acid residue in position 2 and a halogen in position 5 were crucial for inhibitory activity. The compound with an iodine substituent in position 5, denoted iodobikinin, was most active in inhibiting BIN2 activity in vitro and efficiently induced brassinosteroid-like responses in vivo. Its methyl ester, methyliodobikinin, showed improved cell permeability, making it highly potent in vivo although it had lower activity in vitro. HPLC analysis revealed that the methyl residue was rapidly cleaved off in planta liberating active iodobikinin. In addition, we provide evidence that iodobikinin and bikinin are inactivated in planta by conjugation with glutamic acid or malic acid and that the latter process is catalysed by the malate transferase SNG1. Conclusion Brassinosteroids participate in regulation of many aspects of plant development and in responses to environmental cues. Thus compounds modulating their action are valuable tools to study such processes and may be an interesting opportunity to modify plant growth and performance in horticulture and agronomy. Here we report the development of bikinin derivatives with increased potency that can activate BR signalling and mimic BR action. Methyliodobikinin was 3.4 times more active in vivo than bikinin. The main reason for the superior activity of methyliodobikinin, the most potent compound, is its enhanced plant tissue permeability. Inactivation of bikinin and its derivatives in planta involves SNG1, which constitutes a novel pathway for modification of xenobiotic compounds. [ABSTRACT FROM AUTHOR]