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Open Access Publications from the University of California

Scholarly Works (142 results)

  • Thesis
  • Peer Reviewed
UC San Francisco Electronic Theses and Dissertations (1998)

    Cover page: Molecular mechanisms of organic cation transport in ephithelia
    • Thesis
    • Peer Reviewed
    UCLA Electronic Theses and Dissertations (2016)

    This dissertation contains three essays at the interaction between macroeconomics and the financial market, with an emphasis on macroeconomic implications of heterogeneous firms under financial frictions. My dissertation explores the relationships among financial market friction, firms' entry and exit behaviors, and job reallocation over the business cycle.

    Chapter 1 examines the macroeconomic effects of financial leverage and firms' endogenous entry and exit on job reallocation over the business cycle. Financial leverage and the extensive margin are the keys to explain job reallocation at both the firm-level and the aggregate level. I build a general equilibrium industry dynamics model with endogenous entry and exit, a frictional labor market, and borrowing constraints. The model provides a novel theory that financially constrained firms adjust employment more often. I characterize an analytical solution to the wage bargaining problem between a leveraged firm and workers. Higher financial leverage allows constrained firms to bargain for lower wages, but also induces higher default risks. In the model, firms adopt (S,s) employment decision rules. Because the entry and exit firms are more likely to be borrowing constrained, a negative shock affects the inaction regions of the entry and exit firms more than that of the incumbents. In the simulated model, the extensive margin explains 36% of the job reallocation volatility, which is very close to the data and is quantitatively significant.

    Chapter 2 investigates firms' financial behaviors and size distributions over the business cycle. We propose a general equilibrium industry dynamics model of firms' capital structure and entry and exit behaviors. The financial market frictions capture both the age dependence and size dependence of firms' size distributions. When we add the aggregate shocks to the model, it can account for the business cycle patterns of firm dynamics: 1) entry is more procyclical than exit; 2) debt is procyclical, and equity issuance is countercyclical; and 3) the cyclicalities of debt and equity issuance are negatively correlated with firm size and age.

    Chapter 3 studies the equilibrium pricing of complex securities in segmented markets by risk-averse expert investors who are subject to asset-specific risk. Investor expertise varies, and the investment technology of investors with more expertise is subject to less asset-specific risk. Expert demand lowers equilibrium required returns, reducing participation, and leading to endogenously segmented markets. Amongst participants, portfolio decisions and realized returns determine the joint distribution of financial expertise and financial wealth. This distribution, along with participation, then determines market-level risk bearing capacity. We show that more complex assets deliver higher equilibrium returns to expert participants. Moreover, we explain why complex assets can have lower overall participation despite higher market-level alphas and Sharpe ratios. Finally, we show how complexity affects the size distribution of complex asset investors in a way that is consistent with the size distribution of hedge funds.

      Cover page: Essays on Macroeconomics and Firm Dynamics
      • Article
      • Peer Reviewed
      UC Irvine Previously Published Works (2014)
      High order spatial derivatives and stiff reactions often introduce severe temporal stability constraints on the time step in numerical methods. Implicit integration method (IIF) method, which treats diffusion exactly and reaction implicitly, provides excellent stability properties with good efficiency by decoupling the treatment of reactions and diffusions. One major challenge for IIF is storage and calculation of the potential dense exponential matrices of the sparse discretization matrices resulted from the linear differential operators. Motivated by a compact representation for IIF (cIIF) for Laplacian operators in two and three dimensions, we introduce an array-representation technique for efficient handling of exponential matrices from a general linear differential operator that may include cross-derivatives and non-constant diffusion coefficients. In this approach, exponentials are only needed for matrices of small size that depend only on the order of derivatives and number of discretization points, independent of the size of spatial dimensions. This method is particularly advantageous for high dimensional systems, and it can be easily incorporated with IIF to preserve the excellent stability of IIF. Implementation and direct simulations of the array-representation compact IIF (AcIIF) on systems, such as Fokker-Planck equations in three and four dimensions and chemical master equations, in addition to reaction-diffusion equations, show efficiency, accuracy, and robustness of the new method. Such array-presentation based on methods may have broad applications for simulating other complex systems involving high-dimensional data.
        Cover page: Array-representation integration factor method for high-dimensional systems
        • Article
        • Peer Reviewed
        UC Davis Previously Published Works (2013)
        We examine the effect of the bond capital supply uncertainty of institutional investors (e.g., mutual bond funds and insurance companies) on the leverage of the firm using a novel data set. Our main finding is that the supply uncertainty of the firm's bond investor base - measured as (i) the average portfolio turnover, or (ii) the average flow volatility of investors holding the firm's bonds, or (iii) the prevalence of mutual funds among the firm's bondholders as opposed to insurance companies - has a negative and significant effect on the leverage of the firm. The supply uncertainty of the firm's bond investor base also has a negative and significant effect on the firm's probability of issuing bonds, and a positive and significant effect on the firm's probability of issuing equity and borrowing from banks. We take a multi-pronged approach to address potential endogeneity issues, including use of geography-based instruments and firm fixed effects, subsample analyses, and a placebo test. Our results highlight the fragility of access to the bond market for companies that depend on mutual funds with high turnover/ flow volatility as primary bond investors. © 2013 Elsevier B.V.
          • Article
          • Peer Reviewed
          UC San Francisco Previously Published Works (2012)
          The dynamic personalities and structural heterogeneity of proteins are essential for proper functioning. Structural determination of dynamic/heterogeneous proteins is limited by conventional approaches of X-ray and electron microscopy (EM) of single-particle reconstruction that require an average from thousands to millions different molecules. Cryo-electron tomography (cryoET) is an approach to determine three-dimensional (3D) reconstruction of a single and unique biological object such as bacteria and cells, by imaging the object from a series of tilting angles. However, cconventional reconstruction methods use large-size whole-micrographs that are limited by reconstruction resolution (lower than 20 Å), especially for small and low-symmetric molecule (<400 kDa). In this study, we demonstrated the adverse effects from image distortion and the measuring tilt-errors (including tilt-axis and tilt-angle errors) both play a major role in limiting the reconstruction resolution. Therefore, we developed a "focused electron tomography reconstruction" (FETR) algorithm to improve the resolution by decreasing the reconstructing image size so that it contains only a single-instance protein. FETR can tolerate certain levels of image-distortion and measuring tilt-errors, and can also precisely determine the translational parameters via an iterative refinement process that contains a series of automatically generated dynamic filters and masks. To describe this method, a set of simulated cryoET images was employed; to validate this approach, the real experimental images from negative-staining and cryoET were used. Since this approach can obtain the structure of a single-instance molecule/particle, we named it individual-particle electron tomography (IPET) as a new robust strategy/approach that does not require a pre-given initial model, class averaging of multiple molecules or an extended ordered lattice, but can tolerate small tilt-errors for high-resolution single "snapshot" molecule structure determination. Thus, FETR/IPET provides a completely new opportunity for a single-molecule structure determination, and could be used to study the dynamic character and equilibrium fluctuation of macromolecules.
            Cover page: IPET and FETR: Experimental Approach for Studying Molecular Structure Dynamics by Cryo-Electron Tomography of a Single-Molecule Structure
            • Article
            • Peer Reviewed
            UC Irvine Previously Published Works (2012)
            Abstract Background Colon crypts, a single sheet of epithelia cells, consist of a periodic pattern of stem cells, transit-amplifying cells, and terminally differentiated cells that constantly renew and turnover. Experimental evidence suggests that Wnt signaling promotes and regulates stem cell division, differentiation, and possible cell migrations while intestinal BMP signaling inhibits stem cell self-renewal and repression in crypt formation. As more molecular details on Wnt and BMP in crypts are being discovered, little is still known about how complex interactions among Wnt, BMP, and different types of cells, and surrounding environments may lead to de novo formation of multiple crypts or how such interactions affect regeneration and stability of crypts. Results We present a mathematical model that contains Wnt and BMP, a cell lineage, and their feedback regulations to study formation, regeneration, and stability of multiple crypts. The computational explorations and linear stability analysis of the model suggest a reaction–diffusion mechanism, which exhibits a short-range activation of Wnt plus a long-range inhibition with modulation of BMP signals in a growing tissue of cell lineage, can account for spontaneous formation of multiple crypts with the spatial and temporal pattern observed in experiments. Through this mechanism, the model can recapitulate some distinctive and important experimental findings such as crypt regeneration and crypt multiplication. BMP is important in maintaining stability of crypts and loss of BMP usually leads to crypt multiplication with a fingering pattern. Conclusions The study provides a mechanism for de novo formation of multiple intestinal crypts and demonstrates a synergetic role of Wnt and BMP in regeneration and stability of intestinal crypts. The proposed model presents a robust framework for studying spatial and temporal dynamics of cell lineages in growing tissues driven by multiple signaling molecules.
              Cover page: A reaction-diffusion mechanism influences cell lineage progression as a basis for formation, regeneration, and stability of intestinal crypts
              • Article
              • Peer Reviewed
              UC Irvine Previously Published Works (2014)
              High order spatial derivatives and stiff reactions often introduce severe temporal stability constraints on the time step in numerical methods. Implicit integration method (IIF) method, which treats diffusion exactly and reaction implicitly, provides excellent stability properties with good efficiency by decoupling the treatment of reactions and diffusions. One major challenge for IIF is storage and calculation of the potential dense exponential matrices of the sparse discretization matrices resulted from the linear differential operators. Motivated by a compact representation for IIF (cIIF) for Laplacian operators in two and three dimensions, we introduce an array-representation technique for efficient handling of exponential matrices from a general linear differential operator that may include cross-derivatives and non-constant diffusion coefficients. In this approach, exponentials are only needed for matrices of small size that depend only on the order of derivatives and number of discretization points, independent of the size of spatial dimensions. This method is particularly advantageous for high dimensional systems, and it can be easily incorporated with IIF to preserve the excellent stability of IIF. Implementation and direct simulations of the array-representation compact IIF (AcIIF) on systems, such as Fokker-Planck equations in three and four dimensions and chemical master equations, in addition to reaction-diffusion equations, show efficiency, accuracy, and robustness of the new method. Such array-presentation based on methods may have broad applications for simulating other complex systems involving high-dimensional data.
                Cover page: Array-representation Integration Factor Method for High-dimensional Systems.
                • Article
                • Peer Reviewed
                UC Irvine Previously Published Works (2018)

                Background

                Spatial pattern formation is a critical issue in developmental biology. Gene expression boundary sharpening has been observed from both experiments and modeling simulations. However, the mechanism to determine the sharpness of the boundary is not fully elucidated.

                Results

                We investigated the boundary sharpening resulted by three biological motifs, interacting with morphogens, and uncovered their probabilistic landscapes. The landscape view, along with calculated average switching time between attractors, provides a natural explanation for the boundary sharpening behavior relying on the noise induced gene state switchings. To possess boundary sharpening potential, a gene network needs to generate an asymmetric bistable state, i.e. one of the two stable states is less stable than the other. We found that the mutual repressed self-activation model displays more robust boundary sharpening ability against parameter perturbation, compared to the mutual repression or the self-activation model. This is supported by the results of switching time calculated from the landscape, which indicate that the mutual repressed self-activation model has shortest switching time, among three models. Additionally, introducing cross gradients of morphogens provides a more stable mechanism for the boundary sharpening of gene expression, due to a two-way switching mechanism.

                Conclusions

                Our results reveal the underlying principle for the gene expression boundary sharpening, and pave the way for the mechanistic understanding of cell fate decisions in the pattern formation processes of development.
                  Cover page: Landscape reveals critical network structures for sharpening gene expression boundaries
                  • Article
                  • Peer Reviewed
                  UC Riverside Previously Published Works (2017)

                  Motivation

                  Translation initiation is a key step in the regulation of gene expression. In addition to the annotated translation initiation sites (TISs), the translation process may also start at multiple alternative TISs (including both AUG and non-AUG codons), which makes it challenging to predict TISs and study the underlying regulatory mechanisms. Meanwhile, the advent of several high-throughput sequencing techniques for profiling initiating ribosomes at single-nucleotide resolution, e.g. GTI-seq and QTI-seq, provides abundant data for systematically studying the general principles of translation initiation and the development of computational method for TIS identification.

                  Methods

                  We have developed a deep learning-based framework, named TITER, for accurately predicting TISs on a genome-wide scale based on QTI-seq data. TITER extracts the sequence features of translation initiation from the surrounding sequence contexts of TISs using a hybrid neural network and further integrates the prior preference of TIS codon composition into a unified prediction framework.

                  Results

                  Extensive tests demonstrated that TITER can greatly outperform the state-of-the-art prediction methods in identifying TISs. In addition, TITER was able to identify important sequence signatures for individual types of TIS codons, including a Kozak-sequence-like motif for AUG start codon. Furthermore, the TITER prediction score can be related to the strength of translation initiation in various biological scenarios, including the repressive effect of the upstream open reading frames on gene expression and the mutational effects influencing translation initiation efficiency.

                  Availability and implementation

                  TITER is available as an open-source software and can be downloaded from https://github.com/zhangsaithu/titer .

                  Contact

                  lzhang20@mail.tsinghua.edu.cn or zengjy321@tsinghua.edu.cn.

                  Supplementary information

                  Supplementary data are available at Bioinformatics online.
                    Cover page: TITER: predicting translation initiation sites by deep learning
                    • Article
                    • Peer Reviewed
                    UC Berkeley Previously Published Works (2018)
                    The emergent ferroelectricity in HfO2-based systems has attracted significant attention as this simple binary high-k dielectric now offers the possibility of nonvolatile function. In this work we employ zero-field and field-dependent pyroelectricity to show that thin films of silicon-doped HfO2 do exhibit a broken-inversion symmetry and are indeed ferroelectric. In addition, the pyroelectric response is found to exhibit a wake-up behavior akin to the wake-up phenomenon observed in the ferroelectric polarization with electric-field cycling. Using polarization-electric field hysteresis measurements, this wake-up phenomenon is attributed to the presence of defect dipoles which explains the measured pyroelectric response. Finally, direct electrocaloric measurements are performed on these silicon-doped HfO2 thin films, revealing an electrocaloric coefficient ∼4 times larger in magnitude than that expected for the measured pyroelectric coefficient. This enhancement is explained using the plausible role played by defect dipoles that contribute to additional configurational or dipolar entropy.
                      Cover page: Pyroelectric and electrocaloric effects in ferroelectric silicon-doped hafnium oxide thin films
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