618 research outputs found

    Two Essays in Corporate Finance: The Effects of Ownership and Governance on a Firm\u27s Innovation and Capital Structure Decisions

    Get PDF
    In the first chapter, we assess the effect of changes of government ownership on corporate innovation activities. Across 58 non-US countries, treatment firms’ innovation, both in quantity and quality, decrease after a governmental acquisition by using a difference-in-difference regressions and propensity score matching. We show that there is conflict of interest between major shareholders and minor shareholders. The corporate innovation efficiency also decline after the government acquisition. We find that this negative relationship is more severe for the group with higher government ownership of banks, better creditor rights and worse stock market development. For second chapter, if the optimal capital structure exists, an overleveraged firm is expected to move towards the target structure by taking actions that would lower the leverage. Many previous studies, however, show that leverage-decreasing transactions, including offering stocks in exchange of bonds, are meted out with negative market reactions, suggesting deficiencies of the trade-off theory in explaining this phenomenon. In this paper we hypothesize and show that the negative market reactions might be attributed to incorrect rebalancing by poorly-governed firms in the under-leverage domain, who instead of increasing leverage are purposely engaged in leverage-reducing activities

    ECON 2000

    Get PDF
    The purpose of this course is to provide theoretical and practical frameworks within which financial management of private or public companies’ project can be analyzed. Moreover, this course will place an emphasis on the applications of financial principles to realistic case studies. At the conclusion of this course, the students shall know, in theory and in practice, an advanced level treatment of the following areas in financial administration: time value of money, analysis of financial statement, cost of capital, project valuation and project selection criteria

    Tetra-μ3-iodido-tetra­kis­{[ethyl 2-(1H-benzimidazol-1-yl)acetate-κN 3]copper(I)}

    Get PDF
    The complex mol­ecule of the tetra­nuclear cubane-type title compound, [Cu4I4(C11H12N2O2)4], has crystallographically imposed fourfold inversion symmetry. The CuI ions are coordinated in a distorted tetra­hedral geometry by an N atom of a benzimidazole ring system and three μ3-iodide ions, forming a Cu4I4 core. In the crystal, complex mol­ecules are connected into a three-dimensional network by C—H⋯O hydrogen bonds involving H and O atoms of adjacent eth­oxy­carbonyl groups

    Green Innovation and the Value of Multinationality

    Get PDF
    When do multinational corporations (MNCs) derive the most from internalizing the transfer of proprietary technological know how? We revisit this question, which lies at the core of theories on multinationality and performance, from the perspective of corporate strategy involving the mix of green versus non-green innovation effort and a foreign operations focus on countries with high-versus-low environmental standards. We find that high exposure to foreign markets with more stringent environmental regulations stimulates MNCs’ green patent applications. We further show that MNCs’ environmental competitive advantage obtained through green innovation activities, coupled with exposure to foreign countries with high environmental standards, increases firm value in the long run. However, this long-run advantage produces economic rents only when foreign countries have a common-law legal system, effective government, and high growth. Finally, the pursuit of green (or even non-green) innovation while competing in polluting industries is positively associated with market value. Overall, our study highlights that green technology development is a main source of value creation for multinationals

    Improving PTM Site Prediction by Coupling of Multi-Granularity Structure and Multi-Scale Sequence Representation

    Full text link
    Protein post-translational modification (PTM) site prediction is a fundamental task in bioinformatics. Several computational methods have been developed to predict PTM sites. However, existing methods ignore the structure information and merely utilize protein sequences. Furthermore, designing a more fine-grained structure representation learning method is urgently needed as PTM is a biological event that occurs at the atom granularity. In this paper, we propose a PTM site prediction method by Coupling of Multi-Granularity structure and Multi-Scale sequence representation, PTM-CMGMS for brevity. Specifically, multigranularity structure-aware representation learning is designed to learn neighborhood structure representations at the amino acid, atom, and whole protein granularity from AlphaFold predicted structures, followed by utilizing contrastive learning to optimize the structure representations.Additionally, multi-scale sequence representation learning is used to extract context sequence information, and motif generated by aligning all context sequences of PTM sites assists the prediction. Extensive experiments on three datasets show that PTM-CMGMS outperforms the state-of-the-art methods

    Millimeter-Thick Single-Walled Carbon Nanotube Forests: Hidden Role of Catalyst Support

    Full text link
    A parametric study of so-called "super growth" of single-walled carbon nanotubes(SWNTs) was done by using combinatorial libraries of iron/aluminum oxide catalysts. Millimeter-thick forests of nanotubes grew within 10 min, and those grown by using catalysts with a thin Fe layer (about 0.5 nm) were SWNTs. Although nanotube forests grew under a wide range of reaction conditions such as gas composition and temperature, the window for SWNT was narrow. Fe catalysts rapidly grew nanotubes only when supported on aluminum oxide. Aluminum oxide, which is a well-known catalyst in hydrocarbon reforming, plays an essential role in enhancing the nanotube growth rates.Comment: 11 pages, 3 figures. Jpn. J. Appl. Phys. (Express Letters) in pres

    Labor Law and Innovation Revisited

    Get PDF
    This paper examines the impact of changes in job security on corporate innovation in 20 non-U.S. OECD countries. Using a difference-in-differences approach, we provide firm-level evidence that the enhancement of labor protection has a negative impact on innovation. We then discuss possible channels and find that employee-friendly labor reforms induce inventor shirking and a distortion in labor flow. Further investigation reveals that the negative relation is more pronounced in (1) firms that heavily rely on external financing, (2) firms that have high R&D intensity, (3) manufacturing industries, and (4) civil-law countries. Our micro-level evidence indicates that enhanced employment protection impedes corporate innovation

    PhysHOI: Physics-Based Imitation of Dynamic Human-Object Interaction

    Full text link
    Humans interact with objects all the time. Enabling a humanoid to learn human-object interaction (HOI) is a key step for future smart animation and intelligent robotics systems. However, recent progress in physics-based HOI requires carefully designed task-specific rewards, making the system unscalable and labor-intensive. This work focuses on dynamic HOI imitation: teaching humanoid dynamic interaction skills through imitating kinematic HOI demonstrations. It is quite challenging because of the complexity of the interaction between body parts and objects and the lack of dynamic HOI data. To handle the above issues, we present PhysHOI, the first physics-based whole-body HOI imitation approach without task-specific reward designs. Except for the kinematic HOI representations of humans and objects, we introduce the contact graph to model the contact relations between body parts and objects explicitly. A contact graph reward is also designed, which proved to be critical for precise HOI imitation. Based on the key designs, PhysHOI can imitate diverse HOI tasks simply yet effectively without prior knowledge. To make up for the lack of dynamic HOI scenarios in this area, we introduce the BallPlay dataset that contains eight whole-body basketball skills. We validate PhysHOI on diverse HOI tasks, including whole-body grasping and basketball skills

    Analysis of surface roughness evolution of ferritic stainless steel using crystal plasticity finite element method

    Get PDF
    In order to evaluate the surface quality of ferritic stainless steel (FSS) sheets tensile deformation, a crystal plasticity (CP) model, in which the constitutive laws were incorporated with the consideration of the heterogeneous distribution of the properties of grains, was established to analyse the effect of texture, grain sizes and initial surface roughness on the surface roughness evolution of FSS sheets. The electron backscatter diffraction (EBSD) tests were performed to characterise the texture and the grains. A tensile test of the represent volume was simulated and further verified by experimental results. The numerical simulation results indicate that the surface roughness is dependent almost linearly on the average grain size. The {001}(110) and the {112}(110) components induce remarkable undulation on the surface of FSS sheets during uniaxial tension. The surface topology of FSS sheets after tensile deformation are obtained using 3D laser scanning microscope, which shows an agreement with the simulated results
    corecore