58 research outputs found

    Who benefited from the US tariffs on the Chinese tires?

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    The purpose of this paper is to evaluate the short-run effect of the tariffs on Chinese tires imposed by the US in September 2009. First, we investigated whether the tariffs were beneficial to the US domestic tire industry in terms of employment. Our empirical analysis found that there were no significant benefits to US employment in the tire industry. This result led us to the next question: Who benefited from the tariffs? We found that the tire imports to the US were significantly deviated from China to other countries such as Thailand and Korea.Tariffs; Chinese Tires; Difference-in-Difference

    Who benefited from the US tariffs on the Chinese tires?

    Get PDF
    The purpose of this paper is to evaluate the short-run effect of the tariffs on Chinese tires imposed by the US in September 2009. First, we investigated whether the tariffs were beneficial to the US domestic tire industry in terms of employment. Our empirical analysis found that there were no significant benefits to US employment in the tire industry. This result led us to the next question: Who benefited from the tariffs? We found that the tire imports to the US were significantly deviated from China to other countries such as Thailand and Korea

    SPOTS: Stable Placement of Objects with Reasoning in Semi-Autonomous Teleoperation Systems

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    Pick-and-place is one of the fundamental tasks in robotics research. However, the attention has been mostly focused on the ``pick'' task, leaving the ``place'' task relatively unexplored. In this paper, we address the problem of placing objects in the context of a teleoperation framework. Particularly, we focus on two aspects of the place task: stability robustness and contextual reasonableness of object placements. Our proposed method combines simulation-driven physical stability verification via real-to-sim and the semantic reasoning capability of large language models. In other words, given place context information (e.g., user preferences, object to place, and current scene information), our proposed method outputs a probability distribution over the possible placement candidates, considering the robustness and reasonableness of the place task. Our proposed method is extensively evaluated in two simulation and one real world environments and we show that our method can greatly increase the physical plausibility of the placement as well as contextual soundness while considering user preferences.Comment: 7 page

    CLARA: Classifying and Disambiguating User Commands for Reliable Interactive Robotic Agents

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    In this paper, we focus on inferring whether the given user command is clear, ambiguous, or infeasible in the context of interactive robotic agents utilizing large language models (LLMs). To tackle this problem, we first present an uncertainty estimation method for LLMs to classify whether the command is certain (i.e., clear) or not (i.e., ambiguous or infeasible). Once the command is classified as uncertain, we further distinguish it between ambiguous or infeasible commands leveraging LLMs with situational aware context in a zero-shot manner. For ambiguous commands, we disambiguate the command by interacting with users via question generation with LLMs. We believe that proper recognition of the given commands could lead to a decrease in malfunction and undesired actions of the robot, enhancing the reliability of interactive robot agents. We present a dataset for robotic situational awareness, consisting pair of high-level commands, scene descriptions, and labels of command type (i.e., clear, ambiguous, or infeasible). We validate the proposed method on the collected dataset, pick-and-place tabletop simulation. Finally, we demonstrate the proposed approach in real-world human-robot interaction experiments, i.e., handover scenarios

    Did China Tire Safeguard Save U.S. Workers?

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    It has been well documented that trade adjustment costs to workers due to globalization are significant and that temporary trade barriers have been progressively used in many countries, especially during periods with high unemployment rates. Consequently, temporary trade barriers are perceived as a feasible policy instrument for securing domestic jobs in the presence of increased globalization and economic downturns. However, no study has assessed whether such temporary barriers have actually saved domestic jobs. To overcome this deficiency, we evaluate the China-specific safeguard case on consumer tires petitioned by the United States. Contrary to claims made by the Obama administration, we find that total employment and average wages in the tire industry were unaffected by the safeguard using the ‘synthetic control’ approach proposed by Abadie et al. (2010). Further analysis reveals that this result is not surprising as we find that imports from China are completely diverted to other exporting countries partly due to the strong presence of multinational corporations in the world tire market

    Two-dimensional Layered MoS2 Biosensors Enable Highly Sensitive Detection of Biomolecules

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    We present a MoS2 biosensor to electrically detect prostate specific antigen (PSA) in a highly sensitive and label-free manner. Unlike previous MoS2-FET-based biosensors, the device configuration of our biosensors does not require a dielectric layer such as HfO2 due to the hydrophobicity of MoS2. Such an oxide-free operation improves sensitivity and simplifies sensor design. For a quantitative and selective detection of PSA antigen, anti-PSA antibody was immobilized on the sensor surface. Then, introduction of PSA antigen, into the anti-PSA immobilized sensor surface resulted in a lable-free immunoassary format. Measured off-state current of the device showed a significant decrease as the applied PSA concentration was increased. The minimum detectable concentration of PSA is 1 pg/mL, which is several orders of magnitude below the clinical cut-off level of ~4 ng/mL. In addition, we also provide a systematic theoretical analysis of the sensor platform – including the charge state of protein at the specific pH level, and self-consistent channel transport. Taken together, the experimental demonstration and the theoretical framework provide a comprehensive description of the performance potential of dielectric-free MoS2-based biosensor technology

    Foreign Direct Investment, Technology Diffusion, and Host Country Productivity Growth

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    The principal objective of this paper is to ascertain whether foreign direct investment (FDI) has statistically significant effects on host countries\u27 economic performance, such as total factor productivity. Such effects are often referred to as FDI externalities or spillover effects. This paper attempts to evaluate whether these spillover effects depend on the sending countries\u27 income levels. Our empirical analysis shows that FDI exerts positive impacts on less developed countries. Further, we determine that the impacts of FDI from developed countries are more prevalent. So-called North-South effects were confirmed; however, we do not detect South-South effects. We also investigated the other channel, imports, and demonstrate its significant impacts on total factor productivity. © 2011 by Asian Development Bank

    The transfer of workers within multinationals and ownership of foreign affiliates

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    We study the variation in ownership shares across affiliates of the same multinational firm. Using the micro-level data on foreign affiliates of South Korean multinationals, we construct a proxy for the headquarter intangible asset using transferred Korean workers from the parent to the affiliate. Our results show a strong relationship with the parent ownership share even after controlling for the parent fixed effect. Our empirical evidence thus extends support for the theory on multinational firm boundaries at the micro-level

    Cresset: The One Template to Train Them All

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    A new MLOps paradigm for deep learning development using Docker Compose with the aim of providing reproducible and easy-to-use interactive development environments for deep learning practitioners.If you use this software, please cite it using the metadata from this file
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