Measurement and Analysis of the Swarm Social Network With Tens of Millions of Nodes

Social graphs have been widely used for representing the relationship among users in online social networks (OSNs). As crawling an entire OSN is resource-and time-consuming, most of the existing works only pick a sampled subgraph for study. However, this may introduce serious inaccuracy into the analytic results, not to mention that some important metrics cannot even be calculated. In this paper, we crawl the entire social network of Swarm, a leading mobile social app with more than 60 million users, using a distributed approach. Based on the crawled massive user data, we conduct a data-driven study to get a comprehensive picture of the whole Swarm social network. This paper provides a deep analysis of social interactions between Swarm users, and reveals the relationship between social connectivity and check-in activities.Peer reviewe

Inferring Fluid Dynamics via Inverse Rendering

Humans have a strong intuitive understanding of physical processes such as fluid falling by just a glimpse of such a scene picture, i.e., quickly derived from our immersive visual experiences in memory. This work achieves such a photo-to-fluid-dynamics reconstruction functionality learned from unannotated videos, without any supervision of ground-truth fluid dynamics. In a nutshell, a differentiable Euler simulator modeled with a ConvNet-based pressure projection solver, is integrated with a volumetric renderer, supporting end-to-end/coherent differentiable dynamic simulation and rendering. By endowing each sampled point with a fluid volume value, we derive a NeRF-like differentiable renderer dedicated from fluid data; and thanks to this volume-augmented representation, fluid dynamics could be inversely inferred from the error signal between the rendered result and ground-truth video frame (i.e., inverse rendering). Experiments on our generated Fluid Fall datasets and DPI Dam Break dataset are conducted to demonstrate both effectiveness and generalization ability of our method

Thundercloud induced spatial ion flow in the neighborhood of rotating wind turbine and impact mechanism on corona inception

Lightning accidents seriously threaten the safe operation of wind turbines due to the unclear initiation mechanism of the airborne lightning-induced discharges on turbine blades, in which turbine rotation is one of the principal influencing factors. To study the impact mechanism of wind turbine rotation on corona discharge inception, a numerical model with the dynamic meshing of charged ions in the neighboring space of a large-scale rotating wind turbine during a thunderstorm was established in this article, and the validity of the model was verified by long gap discharge experiments on a scaled wind turbine. Based on the proposed model, the spatial and temporal distributions of charged particles in the neighboring area of the rotating wind turbine and the space charge-caused local electric field distortion scenario were obtained. The influence mechanism of blade rotation on corona discharge inception was further analyzed and elucidated accordingly. The results indicate that the charged particles are unevenly distributed near the rotating blade tip, and the contours present a strip-like shape, the critical area of which may facilitate corona discharge inception. As the blade speed increases from 6 to 20 rpm, the E-field extremum at the blade tip increases by 38%, causing the blade tip prone to initiate corona discharge. The critical rotating speeds corresponding to corona inception probability were calculated under different thundercloud-determined field strengths, and a safe boundary was defined, by which it is recommended that wind turbines operate at a reduced speed below 8 rpm under thundercloud conditions

Integrative analysis of the metabolome and transcriptome reveals the molecular mechanism of chlorogenic acid synthesis in peach fruit

As the most abundant phenolic acid in peach fruit, chlorogenic acid (CGA) is an important entry point for the development of natural dietary supplements and functional foods. However, the metabolic and regulation mechanisms underlying its accumulation in peach fruits remain unclear. In this study, we evaluated the composition and content of CGAs in mature fruits of 205 peach cultivars. In peach fruits, three forms of CGA (52.57%), neochlorogenic acid (NCGA, 47.13%), and cryptochlorogenic acid (CCGA, 0.30%) were identified. During the growth and development of peach fruits, the content of CGAs generally showed a trend of rising first and then decreasing. Notably, the contents of quinic acid, shikimic acid, p-coumaroyl quinic acid, and caffeoyl shikimic acid all showed similar dynamic patterns to that of CGA, which might provide the precursor material basis for the accumulation of CGA in the later stage. Moreover, CGA, lignin, and anthocyanins might have a certain correlation and these compounds work together to maintain a dynamic balance. By the comparative transcriptome analysis, 8 structural genes (Pp4CL, PpCYP98A, and PpHCT) and 15 regulatory genes (PpMYB, PpWRKY, PpERF, PpbHLH, and PpWD40) were initially screened as candidate genes of CGA biosynthesis. Our findings preliminarily analyzed the metabolic and molecular regulation mechanisms of CGA biosynthesis in peach fruit, which provided a theoretical basis for developing high-CGA content peaches in future breeding programs

PubChem3D: a new resource for scientists

<p>Abstract</p> <p>Background</p> <p>PubChem is an open repository for small molecules and their experimental biological activity. PubChem integrates and provides search, retrieval, visualization, analysis, and programmatic access tools in an effort to maximize the utility of contributed information. There are many diverse chemical structures with similar biological efficacies against targets available in PubChem that are difficult to interrelate using traditional 2-D similarity methods. A new layer called PubChem3D is added to PubChem to assist in this analysis.</p> <p>Description</p> <p>PubChem generates a 3-D conformer model description for 92.3% of all records in the PubChem Compound database (when considering the parent compound of salts). Each of these conformer models is sampled to remove redundancy, guaranteeing a minimum (non-hydrogen atom pair-wise) RMSD between conformers. A diverse conformer ordering gives a maximal description of the conformational diversity of a molecule when only a subset of available conformers is used. A pre-computed search per compound record gives immediate access to a set of 3-D similar compounds (called "Similar Conformers") in PubChem and their respective superpositions. Systematic augmentation of PubChem resources to include a 3-D layer provides users with new capabilities to search, subset, visualize, analyze, and download data.</p> <p>A series of retrospective studies help to demonstrate important connections between chemical structures and their biological function that are not obvious using 2-D similarity but are readily apparent by 3-D similarity.</p> <p>Conclusions</p> <p>The addition of PubChem3D to the existing contents of PubChem is a considerable achievement, given the scope, scale, and the fact that the resource is publicly accessible and free. With the ability to uncover latent structure-activity relationships of chemical structures, while complementing 2-D similarity analysis approaches, PubChem3D represents a new resource for scientists to exploit when exploring the biological annotations in PubChem.</p