A multi-scale mapping approach based on a deep learning CNN model for reconstructing high-resolution urban DEMs

The scarcity of high-resolution urban digital elevation model (DEM) datasets, particularly in certain developing countries, has posed a challenge for many water-related applications such as flood risk management. A solution to address this is to develop effective approaches to reconstruct high-resolution DEMs from their low-resolution equivalents that are more widely available. However, the current high-resolution DEM reconstruction approaches mainly focus on natural topography. Few attempts have been made for urban topography, which is typically an integration of complex artificial and natural features. This study proposed a novel multi-scale mapping approach based on convolutional neural network (CNN) to deal with the complex features of urban topography and to reconstruct high-resolution urban DEMs. The proposed multi-scale CNN model was firstly trained using urban DEMs that contained topographic features at different resolutions, and then used to reconstruct the urban DEM at a specified (high) resolution from a low-resolution equivalent. A two-level accuracy assessment approach was also designed to evaluate the performance of the proposed urban DEM reconstruction method, in terms of numerical accuracy and morphological accuracy. The proposed DEM reconstruction approach was applied to a 121 km2 urbanized area in London, United Kingdom. Compared with other commonly used methods, the current CNN-based approach produced superior results, providing a cost-effective innovative method to acquire high-resolution DEMs in other data-scarce regions

Genomic Scans of Zygotic Disequilibrium and Epistatic SNPs in HapMap Phase III Populations

<div><p>Previous theory indicates that zygotic linkage disequilibrium (LD) is more informative than gametic or composite digenic LD in revealing natural population history. Further, the difference between the composite digenic and maximum zygotic LDs can be used to detect epistatic selection for fitness. Here we corroborate the theory by investigating genome-wide zygotic LDs in HapMap phase III human populations. Results show that non-Africa populations have much more significant zygotic LDs than do Africa populations. Africa populations (ASW, LWK, MKK, and YRI) possess more significant zygotic LDs for the double-homozygotes (<i>D_AABB</i>) than any other significant zygotic LDs (<i>D_AABb</i>, <i>D_AaBB</i>, and <i>D_AaBb</i>), while non-Africa populations generally have more significant <i>D_AaBb</i>’s than any other significant zygotic LDs (<i>D_AABB</i>, <i>D_AABb</i>, and <i>D_AaBB</i>). Average r-squares for any significant zygotic LDs increase generally in an order of populations YRI, MKK, CEU, CHB, LWK, JPT, CHD, TSI, GIH, ASW, and MEX. Average r-squares are greater for <i>D_AABB</i> and <i>D_AaBb</i> than for <i>D_AaBB</i> and <i>D_AABb</i> in each population. YRI and MKK can be separated from LWK and ASW in terms of the pattern of average r-squares. All population divergences in zygotic LDs can be interpreted with the model of Out of Africa for modern human origins. We have also detected 19735-95921 SNP pairs exhibiting strong signals of epistatic selection in different populations. Gene-gene interactions for some epistatic SNP pairs are evident from empirical findings, but many more epistatic SNP pairs await evidence. Common epistatic SNP pairs rarely exist among all populations, but exist in distinct regions (Africa, Europe, and East Asia), which helps to understand geographical genomic medicine.</p></div

sj-docx-1-sms-10.1177_20563051231196899 – Supplemental material for Does Social Media Use Polarize or Depolarize Political Opinion in China? Explaining Opinion Polarization Within an Extended Communication Mediation Model

Supplemental material, sj-docx-1-sms-10.1177_20563051231196899 for Does Social Media Use Polarize or Depolarize Political Opinion in China? Explaining Opinion Polarization Within an Extended Communication Mediation Model by Jing Guo and Yang Hu in Social Media + Society</p

Cluster analysis of eleven human populations.

<p>The plot is based on the total significant zygotic and composite digenic LDs (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131039#pone.0131039.t001" target="_blank">Table 1</a>), the average r-squares (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131039#pone.0131039.t002" target="_blank">Table 2</a>), the average physical distances (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131039#pone.0131039.t003" target="_blank">Table 3</a>), and Pearson’s correlations between the significant r-square and the physical distance (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131039#pone.0131039.t004" target="_blank">Table 4</a>). Information on <i>d</i> (>0 or <0) is excluded in all tables. Distance matrix is constructed using Canberra distance between any two vectors (20-dimensional). The numbers in red are the p-values (out of 100) that are approximately unbiased (AU), and the numbers in green are the p-values (out of 100) derived from bootstrapping (BP).</p

Common epistatic SNP pairs in East Asia (CHB, CHD, JPT) and in Europe (CEU and TSI) regions across all autosomes.

<p>Results are summarized from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131039#pone.0131039.s002" target="_blank">S2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131039#pone.0131039.s003" target="_blank">S3</a> Tables.</p

Pearson’s correlations between the significant r-square and physical distance (Mb) across all autosomes in each population.

<p>*: P-value = 3.2×10⁻⁶</p><p>All statistical tests have p-value<10⁻⁹ except one test in population YRI (<i>d</i>>0).</p><p>Pearson’s correlations between the significant r-square and physical distance (Mb) across all autosomes in each population.</p

Means and standard deviations over all autosomes for the r-squares of the significant zygotic LDs, the r-squares of the significant composite digenic LD, and the r-squares of the significant differences between the composite digenic and maximum zygotic LDs in each population (p-value <10⁻⁹).

<p>Means and standard deviations over all autosomes for the r-squares of the significant zygotic LDs, the r-squares of the significant composite digenic LD, and the r-squares of the significant differences between the composite digenic and maximum zygotic LDs in each population (p-value <10⁻⁹).</p

Means and coefficients of variations (standard deviation/mean) over all autosomes for the physical distance (Mb) of the significant zygotic LDs, the significant composite digenic LD, and the significant differences between the composite digenic and maximum zygotic LDs in each population (p-value <10⁻⁹).

<p>Means and coefficients of variations (standard deviation/mean) over all autosomes for the physical distance (Mb) of the significant zygotic LDs, the significant composite digenic LD, and the significant differences between the composite digenic and maximum zygotic LDs in each population (p-value <10⁻⁹).</p

Density distributions of the significant r-squares in eleven populations.

<p>(a) <i>D</i>_<i>AABB</i>; (b) <i>D</i>_<i>AABb</i>; (c) <i>D</i>_<i>AaBB</i>; (d) <i>D</i>_<i>AaBb</i>; (e) the composite digenic LD; (f) the difference <i>d</i> >0; and (g) the difference <i>d</i><0.</p

Total SNP pairs of the significant zygotic LDs, the significant composite digenic LDs, and the significant differences between the composite digenic and maximum zygotic LDs.

<p>(a) for each population over all autosomes; (b) for each autosome over all populations. The primary y-axis is used for all black lines while the secondary y-axis is used for the red solid and dashed lines.</p