Does vertical integration increase product quality?

Numerous product quality scandals are caused by low-quality inputs. When input quality is not perfectly observed by downstream firms, upstream firms often have moral hazard problems. If vertical integration does not directly eliminate the moral hazard problems, does vertical integration still improve product quality? If so, under which conditions? We find that given the precision of monitoring technology used by downstream firms, when the level of public monitoring is very high or very low, downstream firms have no incentive to integrate upstream firms; when the level is intermediate, downstream firms have incentives to integrate and vertical integration increases product quality

Observation of a red-blue detuning asymmetry in matter-wave superradiance

We report the first experimental observations of strong suppression of matter-wave superradiance using blue-detuned pump light and demonstrate a pump-laser detuning asymmetry in the collective atomic recoil motion. In contrast to all previous theoretical frameworks, which predict that the process should be symmetric with respect to the sign of the pump-laser detuning, we find that for condensates the symmetry is broken. With high condensate densities and red-detuned light, the familiar distinctive multi-order, matter-wave scattering pattern is clearly visible, whereas with blue-detuned light superradiance is strongly suppressed. In the limit of a dilute atomic gas, however, symmetry is restored.Comment: Accepted by Phys. Rev. Let

Does public spending structure affect the efficiency of spending? Evidence from a panel tobit model for Chinese provinces

The general financial stress confronting Chinese local governments requires public spending to become more efficient. While previous work has attempted to study what determines the efficiency, the focus was put on various factors that were not under direct control by policymakers. This paper revisits the issue, controlling the factors commonly found to be significant in the literature, by evaluating the role of the spending structure which can be easily adjusted by policymakers. The paper focuses on the investment ratio, as public investment is known to be a key driver of the Chinese economy. Using data of 31 provinces between 2000 and 2017, we estimated a Tobit model, with the efficiency of public spending calculated by data envelopment analysis (DEA). The efficiency of public spending is partially determined by the structure of the spending; the former is an increasing function of the latter up to an optimal rate, which is estimated to be between 19-23 percent. As most local governments are over-investing according to this standard, future improvement of budget management would require policymakers to concentrate much more on non-investment projects, such as spending on benefits, education and healthcare – hence, the provision of public goods and services

POEM: Reconstructing Hand in a Point Embedded Multi-view Stereo

Enable neural networks to capture 3D geometrical-aware features is essential in multi-view based vision tasks. Previous methods usually encode the 3D information of multi-view stereo into the 2D features. In contrast, we present a novel method, named POEM, that directly operates on the 3D POints Embedded in the Multi-view stereo for reconstructing hand mesh in it. Point is a natural form of 3D information and an ideal medium for fusing features across views, as it has different projections on different views. Our method is thus in light of a simple yet effective idea, that a complex 3D hand mesh can be represented by a set of 3D points that 1) are embedded in the multi-view stereo, 2) carry features from the multi-view images, and 3) encircle the hand. To leverage the power of points, we design two operations: point-based feature fusion and cross-set point attention mechanism. Evaluation on three challenging multi-view datasets shows that POEM outperforms the state-of-the-art in hand mesh reconstruction. Code and models are available for research at https://github.com/lixiny/POEM.Comment: Accepted by CVPR 202

Pitfalls in Language Models for Code Intelligence: A Taxonomy and Survey

Modern language models (LMs) have been successfully employed in source code generation and understanding, leading to a significant increase in research focused on learning-based code intelligence, such as automated bug repair, and test case generation. Despite their great potential, language models for code intelligence (LM4Code) are susceptible to potential pitfalls, which hinder realistic performance and further impact their reliability and applicability in real-world deployment. Such challenges drive the need for a comprehensive understanding - not just identifying these issues but delving into their possible implications and existing solutions to build more reliable language models tailored to code intelligence. Based on a well-defined systematic research approach, we conducted an extensive literature review to uncover the pitfalls inherent in LM4Code. Finally, 67 primary studies from top-tier venues have been identified. After carefully examining these studies, we designed a taxonomy of pitfalls in LM4Code research and conducted a systematic study to summarize the issues, implications, current solutions, and challenges of different pitfalls for LM4Code systems. We developed a comprehensive classification scheme that dissects pitfalls across four crucial aspects: data collection and labeling, system design and learning, performance evaluation, and deployment and maintenance. Through this study, we aim to provide a roadmap for researchers and practitioners, facilitating their understanding and utilization of LM4Code in reliable and trustworthy ways

CHORD: Category-level Hand-held Object Reconstruction via Shape Deformation

In daily life, humans utilize hands to manipulate objects. Modeling the shape of objects that are manipulated by the hand is essential for AI to comprehend daily tasks and to learn manipulation skills. However, previous approaches have encountered difficulties in reconstructing the precise shapes of hand-held objects, primarily owing to a deficiency in prior shape knowledge and inadequate data for training. As illustrated, given a particular type of tool, such as a mug, despite its infinite variations in shape and appearance, humans have a limited number of 'effective' modes and poses for its manipulation. This can be attributed to the fact that humans have mastered the shape prior of the 'mug' category, and can quickly establish the corresponding relations between different mug instances and the prior, such as where the rim and handle are located. In light of this, we propose a new method, CHORD, for Category-level Hand-held Object Reconstruction via shape Deformation. CHORD deforms a categorical shape prior for reconstructing the intra-class objects. To ensure accurate reconstruction, we empower CHORD with three types of awareness: appearance, shape, and interacting pose. In addition, we have constructed a new dataset, COMIC, of category-level hand-object interaction. COMIC contains a rich array of object instances, materials, hand interactions, and viewing directions. Extensive evaluation shows that CHORD outperforms state-of-the-art approaches in both quantitative and qualitative measures. Code, model, and datasets are available at https://kailinli.github.io/CHORD.Comment: To be presented at ICCV 2023, Pari

Metagenomic Sequencing Identifies Highly Diverse Assemblages of Dinoflagellate Cysts in Sediments From Ships\u27 Ballast Tanks

Ships\u27 ballast tanks have long been known as vectors for the introduction of organisms. We applied next-generation sequencing to detect dinoflagellates (mainly as cysts) in 32 ballast tank sediments collected during 2001-2003 from ships entering the Great Lakes or Chesapeake Bay and subsequently archived. Seventy-three dinoflagellates were fully identified to species level by this metagenomic approach and single-cell polymerase chain reaction (PCR)-based sequencing, including 19 toxic species, 36 harmful algal bloom (HAB) forming species, 22 previously unreported as producing cysts, and 55 reported from ballast tank sediments for the first time (including 13 freshwater species), plus 545 operational taxonomic units (OTUs) not fully identified due to a lack of reference sequences, indicating tank sediments are repositories of many previously undocumented taxa. Analyses indicated great heterogeneity of species composition among samples from different sources. Light and scanning electron microscopy and single-cell PCR sequencing supported and confirmed results of the metagenomic approach. This study increases the number of fully identified dinoflagellate species from ballast tank sediments to 142 (\u3e 50% increase). From the perspective of ballast water management, the high diversity and spatiotemporal heterogeneity of dinoflagellates in ballast tanks argues for continuing research and stringent adherence to procedures intended to prevent unintended introduction of non-indigenous toxic and HAB-forming species