Modeling of Macroeconomics by a Novel Discrete Nonlinear Fractional Dynamical System

We propose a new nonlinear economic system with fractional derivative. According to the Jumarie’s definition of fractional derivative, we obtain a discrete fractional nonlinear economic system. Three variables, the gross domestic production, inflation, and unemployment rate, are considered by this nonlinear system. Based on the concrete macroeconomic data of USA, the coefficients of this nonlinear system are estimated by the method of least squares. The application of discrete fractional economic model with linear and nonlinear structure is shown to illustrate the efficiency of modeling the macroeconomic data with discrete fractional dynamical system. The empirical study suggests that the nonlinear discrete fractional dynamical system can describe the actual economic data accurately and predict the future behavior more reasonably than the linear dynamic system. The method proposed in this paper can be applied to investigate other macroeconomic variables of more states

Product-driven Entrepreneurs and Online Crowdfunding

Advancements in information technology is known for enabling new business models and new market mechanisms. Online crowdfunding is one such new mechanism through which entrepreneurs can advertise their potential products and attract investors from the mass. In this study, we advance the existing theory on online crowdfunding markets by recognizing that online crowdfunding provides not only a venue of fundraising to entrepreneurs but also a venue for them to obtain demand information before production and to signal their intention. We formulate a spatial competition model between profit-driven entrepreneurs and product-driven entrepreneurs and find that on average profit-driven entrepreneurs earn higher profits, but their advantage is constrained by the mechanism of the crowdfunding campaign, and product-driven entrepreneurs earn a significant fraction of the market. Comparing to the Keep-it-all funding scheme we used in the baseline model, the All-or-nothing scheme is more favorable for product-driven entrepreneur, under which the two type entrepreneurs earn equal market shares. We further discuss model implications for consumer satisfaction of the platform and find that including more product-driven entrepreneurs, or adopting All-or-nothing funding scheme improves the overall quality of the platform, but the effects on design popularity and consumer welfare are subtle

Optimizing Illuminant Estimation in Dual-Exposure HDR Imaging

High dynamic range (HDR) imaging involves capturing a series of frames of the same scene, each with different exposure settings, to broaden the dynamic range of light. This can be achieved through burst capturing or using staggered HDR sensors that capture long and short exposures simultaneously in the camera image signal processor (ISP). Within camera ISP pipeline, illuminant estimation is a crucial step aiming to estimate the color of the global illuminant in the scene. This estimation is used in camera ISP white-balance module to remove undesirable color cast in the final image. Despite the multiple frames captured in the HDR pipeline, conventional illuminant estimation methods often rely only on a single frame of the scene. In this paper, we explore leveraging information from frames captured with different exposure times. Specifically, we introduce a simple feature extracted from dual-exposure images to guide illuminant estimators, referred to as the dual-exposure feature (DEF). To validate the efficiency of DEF, we employed two illuminant estimators using the proposed DEF: 1) a multilayer perceptron network (MLP), referred to as exposure-based MLP (EMLP), and 2) a modified version of the convolutional color constancy (CCC) to integrate our DEF, that we call ECCC. Both EMLP and ECCC achieve promising results, in some cases surpassing prior methods that require hundreds of thousands or millions of parameters, with only a few hundred parameters for EMLP and a few thousand parameters for ECCC

Product-driven Entrepreneurs and Crowdfunding

Advancements in information technology is known for enabling new business models and newmarket mechanisms. Online crowdfunding is one such new mechanism through which entrepreneurscan advertise their potential products and attract investors from the mass. In this study, we advancethe existing theory on online crowdfunding markets by recognizing that online crowdfunding pro-vides not only a venue of fundraising to entrepreneurs but also a venue for them to obtain demand in-formation before production and to signal their intention. We formulate a spatial competition modelbetween profit-driven entrepreneurs and product-driven entrepreneurs. We find that, while, on aver-age, profit-driven entrepreneurs earn higher profits than product-driven ones, their advantage is con-strained by the mechanism of the crowdfunding campaign, and product-driven entrepreneurs earn asignificant fraction of the market. We also discuss model implications on consumer satisfaction andcrowdfunding platform design

Nucleosome positioning dynamics in evolution and disease

Nucleosome positioning is involved in a variety of cellular processes, and it provides a likely substrate for species evolution and may play roles in human disease. However, many fundamental aspects of nucleosome positioning remain controversial, such as the relative importance of underlying sequence features, genomic neighbourhood and trans-acting factors. In this thesis, I have focused on analyses of the divergence and conservation of nucleosome positioning, associated substitution spectra, and the interplay between them. I have investigated the extent to which nucleosome positioning patterns change following the duplication of a DNA sequence and its insertion into a new genomic region within the same species, by assessing the relative nucleosome positioning between paralogous regions in both the human (using in vitro and in vivo datasets) and yeast (in vivo) genomes. I observed that the positioning of paralogous nucleosomes is generally well conserved and detected a strong rotational preference where nucleosome positioning has diverged. I have also found, in all datasets, that DNA sequence features appear to be more important than local chromosomal environments in nucleosome positioning evolution, while controlling for trans-acting factors that can potentially confound inter-species comparisons. I have also examined the relationships between chromatin structure and DNA sequence variation, with a particular focus on the spectra of (germline and somatic) substitutions seen in human diseases. Both somatic and germline substitutions are found to be enriched at sequences coinciding with nucleosome cores. In addition, transitions appear to be enriched in germline relative to somatic substitutions at nucleosome core regions. This difference in transition to transversion ratio is also seen at transcription start sites (TSSs) genome wide. However, the contrasts seen between somatic and germline mutational spectra do not appear to be attributable to alterations in nucleosome positioning between cell types. Examination of multiple human nucleosome positioning datasets shows conserved positioning across TSSs and strongly conserved global phasing between 4 cancer cell lines and 7 non-cancer cell lines. This suggests that the particular mutational profiles seen for somatic and germline cells occur upon a common landscape of conserved chromatin structure. I extended my studies of mutational spectra by analysing genome sequencing data from various tissues in a cohort of individuals to identify human somatic mutations. This allowed an assessment of the relationship between age and mutation accumulation and a search for inherited genetic variants linked to high somatic mutation rates. A list of candidate germline variants that potentially predispose to increased somatic mutation rates was the outcome. Together these analyses contribute to an integrated view of genome evolution, encompassing the divergence of DNA sequence and chromatin structure, and explorations of how they may interact in human disease

Investor Attention and Crowdfunding Performance

Today's digital era facilitates the rise of crowdfunding markets by allowing entrepreneurs to seek funding directly from crowds. Crowdfunding, as IT-enabled disintermediation, lowers entry barriers for crowds to invest in business projects and entrepreneurs to obtain funding, yet may exacerbate information asymmetry and absorb investor attention to process information about the potential projects. We develop a model wherein investors with limited attention aggregate personalized information about (reward-based) crowdfunding projects and conduct comparative analyses on how rises in investors’ unit attention cost (associated with greater distractions) affect investor attention, investment decisions, and crowdfunding performance. We then exploit a novel measure of distraction---news pressure---to test the effects of distraction on investor engagement and crowdfunding performance empirically, and the results support our model predictions

Forward Kinematics of Object Transport by a Multi-Robot System with Deformable Sheet

We present object handling and transport by a multi-robot team with a deformable sheet as a carrier. Due to the deformability of the sheet and the high dimension of the whole system, it is challenging to clearly describe all the possible positions of the object on the sheet for a given formation of the multi-robot system. A complete forward kinematics (FK) method is proposed in this paper for object handling by an $N$-mobile robot team with a deformable sheet. Based on the virtual variable cables model, a constrained quadratic problem (CQP) is formulated by combining the form closure and minimum potential energy conditions of the system. Analytical solutions to the CQP are presented and then further verified with the force closure condition. With the proposed FK method, all possible solutions are obtained with the given initial sheet shape and the robot team formation. We demonstrate the effectiveness, completeness, and efficiency of the FK method with simulation and experimental results.Comment: 8 pages, 6 figures, has been submitted to IEEE Robotics and Automation Letter