Conflating point of interest (POI) data: A systematic review of matching methods

Point of interest (POI) data provide digital representations of places in the real world, and have been increasingly used to understand human-place interactions, support urban management, and build smart cities. Many POI datasets have been developed, which often have different geographic coverages, attribute focuses, and data quality. From time to time, researchers may need to conflate two or more POI datasets in order to build a better representation of the places in the study areas. While various POI conflation methods have been developed, there lacks a systematic review, and consequently, it is difficult for researchers new to POI conflation to quickly grasp and use these existing methods. This paper fills such a gap. Following the protocol of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), we conduct a systematic review by searching through three bibliographic databases using reproducible syntax to identify related studies. We then focus on a main step of POI conflation, i.e., POI matching, and systematically summarize and categorize the identified methods. Current limitations and future opportunities are discussed afterwards. We hope that this review can provide some guidance for researchers interested in conflating POI datasets for their research

Exercise and Esr1 Control Mitochondrial Content and Function to Regulate Adiposity

Mechanisms that underlie adipose tissue remodeling to enhance metabolic health in response to exercise training remain inadequately understood. PURPOSE: We utilized mouse genetics and human GWAS to determine the impact of exercise training on mitochondrial DNA copy number, and interrogate the relationship between Esr1 and adipose tissue health. METHODS: We performed RNAseq on adipose tissue from 100 strains of inbred mice following exercise training and determined mitochondrial content by qPCR. We performed deep phenotyping of mice harboring conditional Esr1 overexpression selectively in adipose tissue. Adipose specific Esr1 overexpression and control mice were fed a high fat diet and placed in metabolic chambers to interrogate the effects of Esr1 on whole body metabolism. RESULTS: We determined that exercise training significantly increased adipose tissue mtDNA content in mouse and man and that increased mitochondrial content correlated with reduced adiposity. Adipocyte health was associated with increased expression of transcripts involved in mitochondrial cristae formation including OPA1, Polg1, and Dnm1l. Since Esr1 is a transcription factor negatively associated with adipose tissue mass, and since deletion of Esr1 disrupts mitochondrial function and reduces expression of Polg1, OPA1, and Dnm1l, we interrogated in impact of conditional Esr1 overexpression on mitochondrial function and adipose tissue health. Adipocyte-specific Esr1 overexpression increased expression of mitochondrial gene targets, increased mtDNA copy number and mitochondrial respiration, and enhanced whole body energy expenditure of animals challenged by high fat diet feeding. Adipocyte-specific Esr1 overexpression protected mice against HFD-induced obesity. CONCLUSION: Exercise promotes remodeling of adipose tissue mitochondria and is associated with fat mass reduction. Overexpression of Esr1 drives a similar adipose tissue remodeling and weight loss as exercise training, and protects against adipose tissue weight gain in the context of overnutrition. These data suggest that exercise responsive transcripts in adipose tissue can be selectively targeted to enhance weight loss and improve metabolic health

Classification of coal gangue pile vegetation based on UAV remote sensing

The accurate classification of vegetation species is the basis for the evaluation of vegetation restoration effect of coal gangue pile. In this paper, the visible image of coal gangue pile in different seasons was obtained by UAV remote sensing technology. The color space conversion and texture filtering were used to adequately explore the rich features of color, structure and texture in the visible image. Then, the traditional artificial feature selection method was improved, which could quickly, simply and efficiently screen features information to obtain the optimal classification features, and the optimized results were fused with RGB images to obtain multi-feature fusion images. Finally, based on two stages of RGB images and multi-feature fusion images, the vegetation of coal gangue pile was classified by three supervised classification methods, including support vector machine (SVM), maximum likelihood (ML) and neural network (NN). Meanwhile, the accuracy of classification results was evaluated by confusion matrix and the dynamic changes of vegetation were analyzed. The results showed that the improved artificial feature selection method could screen out the optimal classification features of coal gangue pile vegetation in different seasons. The selected classification features can not only effectively reflect the differences of various ground features, but also reduce the redundancy of feature information to improve the accuracy and efficiency of image classification. The classification result based on Support Vector Machine Classification (SVM) combined with multi-feature fusion image had highest classification accuracy, and the overall classification accuracy could reach 90.60%, and the corresponding Kappa coefficient is 0.8780, which was 9.74% and 0.1265 higher than that of RGB image of the same period, respectively. And, the accuracy of MLC and NNC classification methods was less improved. Compared with the RGB images of the same period, the overall classification accuracy could be improved by 6.95% and 3.93%, respectively, and the corresponding Kappa coefficient could be improved by 0.0845 and 0.0541, respectively. At the same time, based on the result of optimal classification, this paper evaluated the vegetation restoration effect of coal gangue pile in Changcun from the perspectives of vegetation coverage and vegetation allocation pattern. The results showed that a variety of different vegetation allocation patterns were adopted by the coal gangue pile, and the vegetation coverage in autumn and summer is higher than 75%. The overall effect of vegetation restoration was better. This study could provide reference for the identification and classification of coal gangue piles vegetation information based on UAV visible light image, and meanwhile provide opinions or suggestions for the later management and maintenance of coal gangue piles vegetation restoration

Feeding on rapid cold hardening Ambrosia artemisiifolia enhances cold tolerance of Ophraella communa

Low temperatures greatly influence newly introduced species, and increased cold tolerance can facilitate their establishment in new environments. The invasive alien species Ambrosia artemisiifolia is distributed at high latitudes and altitudes, where it suffers more from cold stress than it would at low latitudes or altitudes. Whether cold stress influences the accumulation of cryoprotectants and cold tolerance in A. artemisiifolia, and further influences the cold tolerance of its biological control agent, Ophraella communa, through feeding remain unknown. We investigated the levels of cryoprotectants and metabolic changes in A. artemisiifolia. We found that the level of total sugar, trehalose, proline, and other cold responsible metabolites increased in A. artemisiifolia after rapid cold-hardening (RCH) treatment, when compared to normal plants. These indicated that RCH treatment could improve the cold-hardiness of A. artemisiifolia. We then investigated the levels of cryoprotectants and metabolic changes in O. communa. We found that O. communa fed on RCH-treated A. artemisiifolia had higher levels of total sugar, trehalose, proline, glycerol, lipid, lower water content, lower super-cooling point, and increased cold tolerance compared to O. communa fed on normal A. artemisiifolia. This suggested that O. communa fed on cold-hardened A. artemisiifolia could increase its cold tolerance. Results showed a trophic transmission in insect cold tolerance. Our study enriches the theoretical basis for the co-evolution of cold tolerance in invasive and herbivorous insects