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Donation-based crowdfunding, as part of impact investment, plays a vital role in promoting economic development and alleviating poverty. In order to enhance the lender's enthusiasm for lending behavior, some platforms, for example Kiva, have introduced groups to facilitate lending. This study examines how the group environment can affect the lenders’ behaviors in crowdfunding. It has been found that lenders who join groups contribute 1.2 more loans (about $30-$42) per month than those who do not, but the theoretical mechanism of these differences is unclear. To understand in depth how the group environment affects lending behaviors, we introduce and develop the Person-Organization fit theory and Free-rider theory in this study. Combining machine-learning techniques with empirical analysis, the results show that the matching degree of motivation between group and lender has a positive effect on the lender behavior, i.e., lending to loans, and this relationship is weakened by free-riding in large groups. In addition, the group openness can have different effects on lenders of different group sizes. Our research enriches the existing crowdfunding literature and fills the gap in the research on new lending models in crowdfunding, and it will also be useful for crowdfunding platforms in setting the rules for building groups.

Quantitative stability evaluation of multi-tunnel structure is an important issue related to the safety assessment and stable construction of geotechnical underground tunnels. In this work, the overall failure process of twin tunnels were exhibited by a physical simulation based on the 3D printing (3DP) sandstone analogues model, and a safety factor method was also presented for evaluating the general safety of multi-tunnel structure. For checking the 3DP material performance of physical model, uniaxial and triaxial compressions for the 3DP cylinder specimens were first tested and showed that their mechanical properties and failure characteristics were similar to natural rock in general. Then, the overloading tests for twin-tunnel model were carried out and have exposed the critical position of overall failure of twin-tunnel structure through visual observation and automatic measurement. Testing results and corresponding numerical back analysis indicated that the connectivity of plastic strain between tunnels can be deemed as the conservative instability criterion (i.e. yielding of material) and the inflection point of tunnels’ displacement can be deemed as overall failure criterion (i.e. structure failure) for twin-tunnel structure. The safety analysis for underground hydraulic caverns indicated that this method can provide a reference for quantitative and reasonable evaluation of the general safety of multi-tunnels or caverns and the local instability zone of surrounding rock.

Background: Myocardial infarction (MI) remains the leading cause of morbidity and mortality worldwide, and novel therapeutic targets still need to be investigated to alleviate myocardial injury and the ensuing maladaptive cardiac remodeling. Accumulating studies have indicated that lncRNA H19 might exert a crucial regulatory effect on cardiovascular disease. In this study, we aimed to explore the biological function and molecular mechanism of H19 in MI. Methods: To investigate the biological functions of H19, gain- and loss-of-function experiments were performed. In addition, bioinformatics analysis, dual-luciferase reporter assays, RNA immunoprecipitation (RIP) assays, RNA pull-down assays, quantitative RT-PCR and Western blot analyses as well as rescue experiments were conducted to reveal an underlying competitive endogenous RNA (ceRNA) mechanism. Results: We found that H19 was significantly downregulated after MI. Functionally, enforced H19 expression dramatically reduced infarct size, improved cardiac performance and alleviated cardiac fibrosis by mitigating myocardial apoptosis and decreasing inflammation. However, H19 knockdown resulted in the opposite effects. Bioinformatics analysis and dual-luciferase assays revealed that, mechanistically, miRNA-22-3p was a direct target of H19, which was also confirmed by RIP and RNA pull-down assays in primary cardiomyocytes. In addition, bioinformatics analysis and dual-luciferase reporter assays also demonstrated that miRNA-22-3p directly targeted the KDM3A gene. Moreover, subsequent rescue experiments further verified that H19 regulated the expression of KDM3A to ameliorate MI-induced myocardial injury in a miRNA-22-3p-dependent manner. Conclusions: the present study revealed the critical role of the lncRNAH19/miRNA-22-3p/KDM3A pathway in MI. These findings suggest that H19 may act as a potential biomarker and therapeutic target for MI. Funding Statement: This work was supported by the National Natural Science Foundation of China (81200156 and 81570331), and the Nature Science Foundation of Hubei Province (2018CFB240). Declaration of Interests: The authors declare that they have no conflict of interest. Ethics Approval Statement: All experimental procedures were approved by the Animal Care and Use Committee of Wuhan University and performed in accordance with the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health (NIH Publication, 8th Edition, 2011).

Multiphase flows exhibit a large realm of complex behaviors such as bubbling, glugging, wetting, and splashing which emerge from air-water and water-solid interactions. Current fluid solvers in graphics have demonstrated remarkable success in reproducing each of these visual effects, but none have offered a model general enough to capture all of them concurrently. In contrast, computational fluid dynamics have developed very general approaches to multiphase flows, typically based on kinetic models. Yet, in both communities, there is dearth of methods that can simulate density ratios and Reynolds numbers required for the type of challenging real-life simulations that movie productions strive to digitally create, such as air-water flows. In this article, we propose a kinetic model of the coupling of the Navier-Stokes equations with a conservative phase-field equation, and provide a series of numerical improvements over existing kinetic-based approaches to offer a general multiphase flow solver. The resulting algorithm is embarrassingly parallel, conservative, far more stable than current solvers even for real-life conditions, and general enough to capture the typical multiphase flow behaviors. Various simulation results are presented, including comparisons to both previous work and real footage, to highlight the advantages of our new method.

Objective: To study the epidemiology details and clinical features of hypoxic patients infected with SARS-CoV-2 infection that admitted to Renmin Hospital of Wu

Traditional methods in graphics to simulate liquid-air dynamics under different scenarios usually employ separate approaches with sophisticated interface tracking/reconstruction techniques. In this paper, we propose a novel unified approach which is easy and effective to produce a variety of liquid-air interface phenomena. These phenomena, such as complex surface splashes, bubble interactions, as well as surface tension effects, can co-exist in one single simulation, and are created within the same computational framework. Such a framework is unique in that it is free from any complicated interface tracking/reconstruction procedures. Our approach is developed from the two-phase lattice Boltzmann method with the mean field model, which provides a unified framework for interface dynamics but is numerically unstable under turbulent conditions. Considering the drawbacks of the existing approaches, we propose techniques to suppress oscillations for significant stability enhancement, as well as derive a new subgrid-scale model to further improve stability, faithfully preserving liquid-air interface details without excessive diffusion by taking into account the density variation. The whole framework is highly parallel, enabling very efficient implementation. Comparisons with the related approaches show superiority on stable simulations with detail preservation and multiphase phenomena simultaneously involved. A set of animation results demonstrate the effectiveness of our method.

It has been reported that KDM3A participates in several cardiovascular diseases through epigenetic mechanisms. However, its biological role post myocardial infarction (MI) has not been explored. Excessive and prolonged inflammation period can aggravate post-MI injuries and accelerates left ventricular (LV) remodeling. Previous studies have shown that macrophages play a momentous role in post-MI injuries by regulating the balance between the inflammatory phase. In this study, we aimed to demonstrate whether KDM3A could regulate the polarization of macrophages to affect the inflammatory response after myocardial infarction and whether targeting KDM3A could influence the prognosis of myocardial infarction and adverse LV remodeling. To explore the biological function of KDM3A and the underlying mechanisms, the loss of function experiments were designed in vitro and vivo. we analyzed the function of macrophages by a phagocytosis and migration assay and explored the polarization of macrophages. The expression of macrophage inflammation-related genes in the acute inflammatory phase and surface markers was detected by western blot and immunofluorescence assays. Echocardiography, Masson's trichrome staining and hematoxylin and eosin (H&E) staining were used to detect cardiac ventricular function. Our data showed that KDM3A is essential for the biological function of rat bone marrow macrophages (BMDMs), and KDM3A deficiency decreases the capacity for phagocytosis and migration, promoting M1 but restraining M2 macrophage phenotype polarization in vitro. Furthermore, we constructed MI models of male rats to verify that KDM3A deficiency could regulate macrophage polarization to aggravate the inflammatory response and accelerate LV remodeling in vivo. Among them, we confirmed that IRF4 is a downstream effector of the KDM3A-dependent pathway which could epigenetically influence the transcription of IRF4 by enhancing histone H3 lysine 9 di-methylation(H3K9me2) accumulation on the IRF4 gene proximal promoter region to modulate macrophage polarization. These results demonstrated that KDM3A plays an essential role in the cardiac repair process of post-MI and LV remodeling by modulating the macrophage phenotype, thereby suggesting a promising therapy to treat post MI injuries.

Vectorizing vortex-core lines is crucial for high-quality visualization and analysis of turbulence. While several techniques exist in the literature, they can only be applied to classical fluids. Recently, quantum fluids with turbulence get more and more attention in physics. It is thus desirable that vortex-core lines can also be well extracted and visualized for quantum fluids. In this paper, we aim for this goal and developed an efficient vortex-core line vectorization method for quantum fluids, which enables real-time visualization of high-resolution quantum turbulence structure. Given the datasets by simulation, our technique is developed from the vortices identified by the circulation-based method. To vectorize the vortex-core lines enclosed by those vortices, we propose a novel graph-based data structure, with iterative graph reduction and density-guided local optimization, to locate more precisely sub-grid-scale vortex-core line samples, which are then vectorized by continuous curves. This not only represents vortex-core line structures continuously, but also naturally preserves complex topology, such as branching during reconnection. By vectorization, the memory consumption can be largely reduced by orders of magnitude, enabling real-time rendering performance. Different types of interactive visualizations are demonstrated to show the effectiveness of our technique, which could assist further research on quantum turbulence., Comment: 14 pages, 19 figures

Kinetic approaches, i.e., methods based on the lattice Boltzmann equations, have long been recognized as an appealing alternative for solving incompressible Navier-Stokes equations in computational fluid dynamics. However, such approaches have not been widely adopted in graphics mainly due to the underlying inaccuracy, instability and inflexibility. In this paper, we try to tackle these problems in order to make kinetic approaches practical for graphical applications. To achieve more accurate and stable simulations, we propose to employ the non-orthogonal central-moment-relaxation model, where we develop a novel adaptive relaxation method to retain both stability and accuracy in turbulent flows. To achieve flexibility, we propose a novel continuous-scale formulation that enables samples at arbitrary resolutions to easily communicate with each other in a more continuous sense and with loose geometrical constraints, which allows efficient and adaptive sample construction to better match the physical scale. Such a capability directly leads to an automatic sample construction which generates static and dynamic scales at initialization and during simulation, respectively. This effectively makes our method suitable for simulating turbulent flows with arbitrary geometrical boundaries. Our simulation results with applications to smoke animations show the benefits of our method, with comparisons for justification and verification., 17 pages, 17 figures, accepted by IEEE Transactions on Visualization and Computer Graphics

The exploration and analysis of data mining methodologies is an important task for effective knowledge discovery, especially in today's heterogeneous information networks. Previously presented approaches for mining optimization aim primarily at the improvements of time complexity, space complexity, accuracy, and robustness. We extend the state-of-the-art method by concentrating on user-availability and algorithm understandability. Specifically, we use Rankclus, a classic clustering algorithm as an example. After uncovering the unseen computing processes to be displayed in a visual form, the whole clustering processes are transparent to the users, which may help them more clearly and quickly understand how the algorithms are computed, how does each object influence one another. In addition, we use a density approach to intuitively simplify the discovery of data patterns, and through the visualized results, users can adjust algorithm parameters with or without professional training. Finally, we use another two visual techniques to improve the visualization quality: a heatmap matrix designed for checking the similarities of objects which are in the same cluster, and a DOItree implemented to further analyze the accuracy of the algorithms.

This paper addresses a challenging single-view modeling and animation problem with cartoon images. Our goal is to model the hairs in a given cartoon image with consistent layering and occlusion, so that we can produce various visual effects from just a single image. We propose a novel 2.5D modeling approach to deal with this problem. Given an input image, we first segment the hairs of the cartoon character into regions of hair strands. Then, we apply our novel layering metric, which is derived from the Gestalt psychology, to automatically optimize the depth ordering among the hair strands. After that, we employ our hair completion method to fill the occluded part of each hair strand, and create a 2.5D model of the cartoon hair. By using this model, we can produce various visual effects, e.g., we develop a simplified fluid simulation model to produce wind blowing animations with the 2.5D hairs. To further demonstrate the applicability and versatility of our method, we compare our results with real cartoon hair animations, and also apply our model to produce a wide variety of hair manipulation effects, including hair editing and hair braiding.

Dual bypass gas metal arc welding (DB-GMAW) is a novel welding process which is capable of achieving different full penetration level by adjusting bypass current while keeping the total welding current constant for a constant mass input. In this paper, an experimental system is constructed to implement DB-GMAW and full penetration weld is produced on aluminum. To describe the relationship between bypass current (input) and full penetration level (output), a nonlinear model is proposed, identified, and validated based on process analysis and through experiments. To assure the desired full penetration level be produced under varying welding conditions, the parameters are on-line identified/updated and an adaptive control algorithm is proposed. Experiments verified the effectiveness of the developed adaptive nonlinear control system.

Even though the temporal information is lost, a still picture of moving animals hints at their motion. In this paper, we infer motion cycle of animals from the "motion snapshots" (snapshots of different individuals) captured in a still picture. By finding the motion path in the graph connecting motion snapshots, we can infer the order of motion snapshots with respect to time, and hence the motion cycle. Both "half-cycle" and "full-cycle" motions can be inferred in a unified manner. Therefore, we can animate a still picture of a moving animal group by morphing among the ordered snapshots. By refining the pose, morphology, and appearance consistencies, smooth and realistic animal motion can be synthesized. Our results demonstrate the applicability of the proposed method to a wide range of species, including birds, fishes, mammals, and reptiles.

In the past, EBS performance test was conducted with traditional instruments, which was tedious and costly. This study is made on the system of EBS performance test developed based on LabVIEW. This system, which is easy to operate and quite practicable, can achieve simultaneous monitoring, recording and display of analog signal, digital signal and GPS communication signals. Experiment showed that the good stability and reliability of the system was very helpful for the operators to evaluate and analyse EBS performance.

Based on embedded Linux operating system, the major control messages and streaming media service functions of the RTMP server is analyzed in detail, and the powerful streaming media function of adoble company's flash media server is simplified to transplant the services of the live and VOD streaming media to embedded system. The experimental results show the transplanted services can be successfully run on TMS320DM6467T chip evaluation boards, and support the service of real-time or on demand publish of video and audio. In addition, the results show that the solution supports the direct access of flash media player, and the live and VOD streaming functions can be used in electronic products (embedded network streaming media), reduce costs and cycle of developing client-side media player.

Resonant circuit is widely used in communication system and other kinds of electronic systems. In most cases, the signal induced by the antenna of a receiver is always very weak, which calls for high-frequency small-signal resonant amplifier to restore the signal. The design in this article is composed of three modules: attenuation circuit, small-signal amplifying circuit, and voltage regulator circuit. We use integrated chips in attenuation circuit. We choose transformer feedback LC oscillator circuit to select standard 15MHz signal, and we use triode to implement 60dB amplifying of the high-frequency small-signal. The voltage regulator circuit is constructed by LM317 three-terminal adjustable voltage regulator. After examination, the output signal is barely distorted and this circuit is low-power consumption and high-gain.

This paper introduces concepts and digital characteristics of cloud model which is a converter between qualitative and quantitative information. Then a theory that speed and steering of robot are manipulated by cloud model controller which process uncertain information collected by infrared distance sensors is proposed. Also, the design of core modules constitute control system is described. Finally performance of cloud model controller is test by field testing.

Customer Relationship Management builds a kind of platform for enterprise to collect, summarize, analyze and make use of customer-information, which integrates information technology, network technology, database technology. This thesis firstly briefly analyzes the selected topic background, the research significance and development status of CRM system in the world as well as unique characteristics of market in China, talking about jobs and structure of this paper. This system includes contact management, contract management, storage management, finance management, service management, which supply a convenient, efficient, informationzed platform for Anjou Nature Building Materials Trading Co., Ltd, enhancing competitiveness and realizing sustainable development.

Commercial 3D scene acquisition systems such as the Microsoft Kinect sensor can reduce the cost barrier of realizing mid-air interaction. However, since it can only sense hand position but not hand orientation robustly, current mid-air interaction methods for 3D virtual object manipulation often require contextual and mode switching to perform translation, rotation, and scaling, thus preventing natural continuous gestural interactions. A novel handle bar metaphor is proposed as an effective visual control metaphor between the user's hand gestures and the corresponding virtual object manipulation operations. It mimics a familiar situation of handling objects that are skewered with a bimanual handle bar. The use of relative 3D motion of the two hands to design the mid-air interaction allows us to provide precise controllability despite the Kinect sensor's low image resolution. A comprehensive repertoire of 3D manipulation operations is proposed to manipulate single objects, perform fast constrained rotation, and pack/align multiple objects along a line. Three user studies were devised to demonstrate the efficacy and intuitiveness of the proposed interaction techniques on different virtual manipulation scenarios.

Estimating illumination and deformation fields on textures is essential for both analysis and application purposes. Traditional methods for such estimation usually require complicated and sometimes labor-intensive processing. In this paper, we propose a new perspective for this problem and suggest a novel statistical approach which is much simpler and more efficient. Our experiments show that many textures in daily life are statistically invariant in terms of colors and gradients. Variations of such statistics can be assumed to be influenced by illumination and deformation. This implies that we can inversely estimate the spatially varying illumination and deformation according to the variation of the texture statistics. This enables us to decompose a texture photo into an illumination field, a deformation field, and an implicit texture which are illumination- and deformation-free, within a short period of time, and with minimal user input. By processing and recombining these components, a variety of synthesis effects, such as exemplar preparation, texture replacement, surface relighting, as well as geometry modification, can be well achieved. Finally, convincing results are shown to demonstrate the effectiveness of the proposed method.

Natural scene text location is the precondition of the text recognition, a fast and effective technique is proposed for text location oriented Chinese environment. First, the color edge of the image is detected in consideration of the stroke directions of Chinese characters, then the collection of candidate text blocks is obtained by post-processing; Second, because text differs from non-text in texture, local binary pattern (LBP) operator is employed to extract the texture feature of candidate text block, then feed them into SVM classifier for verification, thus a great number of non-text blocks are excluded, and a higher accuracy rate is obtained. Finally, the algorithm is tested on our database, which includes 1000 images, and experimental results show that the proposed algorithm works well and very robust under the conditions of uneven lighting, blurring, and low contrast etc.

We propose a novel reaction diffusion (RD) simulator to evolve image-resembling mazes. The evolved mazes faithfully preserve the salient interior structures in the source images. Since it is difficult to control the generation of desired patterns with traditional reaction diffusion, we develop our RD simulator on a different computational platform, cellular neural networks. Based on the proposed simulator, we can generate the mazes that exhibit both regular and organic appearance, with uniform and/or spatially varying passage spacing. Our simulator also provides high controllability of maze appearance. Users can directly and intuitively ?paint? to modify the appearance of mazes in a spatially varying manner via a set of brushes. In addition, the evolutionary nature of our method naturally generates maze without any obvious seam even though the input image is a composite of multiple sources. The final maze is obtained by determining a solution path that follows the user-specified guiding curve. We validate our method by evolving several interesting mazes from different source images.

The purpose of this paper is to study the operational competitiveness of Chinese aeronautics and astronautics manufacturing companies (CAAMC) by analyzing the case CAAMC in a global manufacturing strategies (GMSS) database. Analytical models are used to analyze the operational competitiveness of the case CAAMC based on the weights of the multi-criteria manufacturing strategies. The results show quality value of the case Chinese astronautics manufacturing company (CASMC) is higher than the case Chinese aeronautics manufacturing company's, but customer focus value of the case Chinese aeronautics manufacturing company (CAEMC) is higher than the case CASMC's. The ranking of operational competitiveness implies CASMC has stronger competitiveness than CAEMC in prospector group.

In this paper, we present an example-based colorization technique robust to illumination differences between grayscale target and color reference images. To achieve this goal, our method performs color transfer in an illumination-independent domain that is relatively free of shadows and highlights. It first recovers an illumination-independent intrinsic reflectance image of the target scene from multiple color references obtained by web search. The reference images from the web search may be taken from different vantage points, under different illumination conditions, and with different cameras. Grayscale versions of these reference images are then used in decomposing the grayscale target image into its intrinsic reflectance and illumination components. We transfer color from the color reflectance image to the grayscale reflectance image, and obtain the final result by relighting with the illumination component of the target image. We demonstrate via several examples that our method generates results with excellent color consistency.

A method is presented for separating corneal reflections in an image of human irises to estimate illumination from the surrounding scene. Previous techniques for reflection separation have demonstrated success in only limited cases, such as for uniform colored lighting and simple object textures, so they are not applicable to irises which exhibit intricate textures and complicated reflections of the environment. To make this problem feasible, we present a method that capitalizes on physical characteristics of human irises to obtain an illumination estimate that encompasses the prominent light contributors in the scene. Results of this algorithm are presented for eyes of different colors, including light colored eyes for which reflection separation is necessary to determine a valid illumination estimate