A new framework for assessment of park management in smart cities: a study based on social media data and deep learning.

Urban park management assessment is critical to park operation and service quality. Traditional assessment methods cannot comprehensively assess park use and environmental conditions. Besides, although social media and big data have shown significant advantages in understanding public behavior or preference and park features or values, there has been little relevant research on park management assessment. This study proposes a deep learning-based framework for assessing urban park intelligent management from macro to micro levels with comment data from social media. By taking seven parks in Wuhan City as the objects, this study quantitatively assesses their overall state and performance in facilities, safety, environment, activities, and services, and reveals their main problems in management. The results demonstrate the impacts of various factors, including park type, season, and specific events such as remodeling and refurbishment, on visitor satisfaction and the characteristics of individual parks and their management. Compared with traditional methods, this framework enables real-time intelligent assessment of park management, which can accurately reflect park use and visitor feedback, and improve park service quality and management efficiency. Overall, this study provides important reference for intelligent park management assessment based on big data and artificial intelligence, which can facilitate the future development of smart cities.

Multi source translation based projection completion for interior region of interest tomography with CBCT.

Interior tomography by rotary computed tomography (RCT) is an effective method to improve the detection efficiency and achieve high-resolution imaging for the region of interest (ROI) within a large-scale object. However, because only the X-rays through the ROI can be received by detector, the projection data is inevitably truncated, resulting in truncation artifacts in the reconstructed image. When the ROI is totally within the object, the solution of the problem is not unique, which is named interior problem. Fortunately, projection completion (PC) is an effective technique to solve the interior problem. In this study, we proposed a multi source translation CT based PC method (mSTCT-PC) to cope with the interior problem. Firstly, mSTCT-PC employs multi-source translation to sparsely obtain the global projection which covered the whole object. Secondly, the sparse global projection is utilized to fill up the truncated projection of ROI. The global projection and truncated projection are obtained under the same geometric parameters. Therefore, it omits the registration of projection. To verify the feasibility of this method, simulation and practical experiments were implemented. Compared with the results of ROI reconstructed by filtered back-projection (FBP), simultaneous iterative reconstruction technique-total variation (SIRT-TV) and the multi-resolution based method (mR-PC), the proposed mSTCT-PC is good at mitigating truncation artifacts, preserving details and improving the accuracy of ROI images.

X-ray source translation based computed tomography (STCT).

Micro computed tomography (µCT) allows the noninvasive visualization and 3D reconstruction of internal structures of objects with high resolution. However, the current commercial µCT system relatively rotates the source-detector or objects to collect projections, referred as RCT in this paper, and has difficulties in imaging large objects with high resolutions because fabrication of large-area, inexpensive flat-panel detectors remains a challenge. In this paper, we proposed a source translation based CT (STCT) for imaging large objects with high resolution to get rid of the limitation of the detector size, where the field of view is primarily determined by the source translation distance. To compensate for the deficiency of incomplete data in STCT, we introduced multi-scanning STCT (mSTCT), from which the projections theoretically meet the conditions required for accurate reconstructions. Theoretical and numerical studies showed that mSTCT has the ability to accurately image large objects without any visible artifacts. Numerical simulations also indicated that mSTCT has a potential capability to precisely image the region of interest (ROI) inside objects, which remains a challenge in RCT due to truncated projections. In addition, an experimental platform for mSTCT has been established, from which the 2D and 3D reconstructed results demonstrated its feasibility for µCT applications. Moreover, STCT also has a great potential for security inspection and product screening by using two perpendicular STCTs, with advantages of low-cost equipment and high-speed examination.

Evaluation of the Equity of Urban Park Green Space Based on Population Data Spatialization: A Case Study of a Central Area of Wuhan, China.

To measure the equity of urban park green space, spatial matching between service supply and user group demand should be taken into consideration. However, if the demographic data, with the administrative division as the basic unit, are directly applied to characterize the spatial distribution of a user group, it may introduce inevitable deviation into the evaluation results due to the low-resolution nature and modifiable areal unit problem of such data. Taking the central area of Wuhan as an example, the population data spatialization method based on land use modeling was used to build a geographically weighted regression (GWR) model of land cover type and demographic data, and the spatial distribution of the population of the 150 m grid was obtained by inversion. Then, the equity of park green space in Wuhan central city was evaluated by population spatial data and network accessibility. The results showed that (1) the range of park green space in the central urban area of Wuhan was within a walking distance of 15 min, accounting for 25.8% of the total study area and covering 54.2% of the population in the study area; (2) the equity of park green space in Hongshan District was the worst; (3) and the use of population spatial data can measure equity on a more precise scale.

Genome-Wide Association Study Reveals Both Overlapping and Independent Genetic Loci to Control Seed Weight and Silique Length in Brassica napus.

Seed weight (SW) is one of three determinants of seed yield, which positively correlates with silique length (SL) in Brassica napus (rapeseed). However, the genetic mechanism underlying the relationship between seed weight (SW) and silique length (SL) is largely unknown at present. A natural population comprising 157 inbred lines in rapeseed was genotyped by whole-genome re-sequencing and investigated for SW and SL over four years. The genome-wide association study identified 20 SNPs in significant association with SW on A01, A04, A09, C02, and C06 chromosomes and the phenotypic variation explained by a single locus ranged from 11.85% to 34.58% with an average of 25.43%. Meanwhile, 742 SNPs significantly associated with SL on A02, A03, A04, A07, A08, A09, C01, C03, C04, C06, C07, and C08 chromosomes were also detected and the phenotypic variation explained by a single locus ranged from 4.01 to 48.02% with an average of 33.33%, out of which, more than half of the loci had not been reported in the previous studies. There were 320 overlapping or linked SNPs for both SW and SL on A04, A09, and C06 chromosomes. It indicated that both overlapping and independent genetic loci controlled both SW and SL in B. napus. On the haplotype block on A09 chromosome, the allele variants of a known gene BnaA.ARF18.a controlling both SW and SL were identified in the natural population by developing derived cleaved amplified polymorphic sequence (dCAPS) markers. These findings are valuable for understanding the genetic mechanism of SW and SL and also for rapeseed molecular breeding programs.

GWAS, QTL mapping and gene expression analyses in Brassica napus reveal genetic control of branching morphogenesis.

Branch number is an important trait in plant architecture that can influence crop yield and quality in Brassica napus. Here, we detected the QTLs responsible for branch number in a DH population and its reconstructed F2 population over two years. Further, a GWAS research on branch number was performed using a panel of 327 accessions with 33186 genomic SNPs from the 60 K Brassica Illumina® Infinium SNP array. Through combining linkage analysis and association mapping, a new QTL was fine mapped onto C03. Subsequently, we tested the correlations between the SNP polymorphisms and mRNA expression levels of genes in the target interval to identify potential loci or genes that control branch number through expression. The results show that 4 SNP loci are associated with the corresponding gene expression levels, and one locus (BnaC03g63480D) exhibited a significant correlation between the phenotype variation and gene expression levels. Our results provide insights into the genetic basis for branching morphogenesis and may be valuable for optimizing architecture in rapeseed breeding.