549 research outputs found

    Every Cloud Has a Silver Lining: Analysis of Negative Book Value Firms

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    Negative book value firms have become more prevalent in recent years, ranging from 0.41% of all Compustat firms in 1961 to 12.47% in 2016 with highest representations in the healthcare, telecommunication, and computer electronic industries. To examine why these negative book value firms are not liquidated, we investigate firmsā€™ 1) current accounting practices, 2) future investment opportunities, and 3) narrative investment disclosures. We first document that negative book value firms adopting a more conservative accounting practice in the current period are less likely to be liquidated. Next, we find that the liquidation likelihood is lower for negative book value firms with higher levels of future intangible investments. Furthermore, we employ a machine-learning-based latent Dirichlet allocation (LDA) approach to measure investment-oriented firm disclosures and find a lower liquidation likelihood for negative book value firms disclosing more future investment narratives. Our evidence is robust to including reorganization firms and extending the length of the liquidation window. Overall, our study sheds light on why negative book value firms are not liquidated by providing evidence on firmsā€™ current accounting practices and future investment opportunities

    Experimental Review of Ī›Ī›ĀÆ Production

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    Exclusive hyperon-antihyperon production provides a unique insight for understanding of the intrinsic dynamics when strangeness is involved. In this paper, we review the results of Ī›Ī›ĀÆ production via different reactions from various experiments, e.g., via pĀÆp annihilation from the LEAR experiment PS185, via electron-positron annihilation using the energy scan method at the CLEO-c and BESIII experiments and the initial-state-radiation approach utilized at the BaBar experiment. The production cross section of Ī›Ī›ĀÆ near the threshold is sensitive to QCD based prediction. Experimental high precision data for pĀÆpā†’Ī›ĀÆĪ› close to the threshold region is obtained. The cross section of e+eāˆ’ā†’Ī›Ī›ĀÆ is measured from its production threshold to high energy. A non-zero cross section for e+eāˆ’ā†’Ī›Ī›ĀÆ near threshold is observed at BaBar and BESIII, which is in disagreement with the pQCD prediction. However, more precise data is needed to confirm this observation. Future experiments, utilizing pĀÆp reaction such as PANDA experiment or electron-positron annihilation such as the BESIII and BelleII experiments, are needed to extend the experimental data and to understand the Ī›Ī›ĀÆ production

    Production Mechanism of the Charmed Baryon Ī›c+

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    As the lightest charmed baryon, precision measurement of the pair production cross section of Ī›c+ provides unprecedented experimental information for the investigation of baryon production mechanism. In addition, the extraction of the polar angle distributions of the outgoing Ī›c+ in the annihilation of the electronā€“positron help to determine its electromagnetic form factors, which is currently the unique key to access the internal structure of the baryons. In this article, the measurement of e+eāˆ’ā†’Ī›c+Ī›ĀÆcāˆ’ process via the initial state radiation technique at Belle detector and direct electronā€“positron annihilation at BESIII with discrete center-of-mass energies near threshold are briefly reviewed. In addition, the electromagnetic form factor ratios of Ī›c+ measured by BESIII are also investigated. A few theoretical models that parameterize the center-of-mass energy dependence of the cross section and electromagnetic form factors of baryon are introduced and the contributions of Ī›c+ data to them are discussed

    A real-time, practical sensor fault-tolerant module for robust EMG pattern recognition

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    BACKGROUND: Unreliability of surface EMG recordings over time is a challenge for applying the EMG pattern recognition (PR)-controlled prostheses in clinical practice. Our previous study proposed a sensor fault-tolerant module (SFTM) by utilizing redundant information in multiple EMG signals. The SFTM consists of multiple sensor fault detectors and a self-recovery mechanism that can identify anomaly in EMG signals and remove the recordings of the disturbed signals from the input of the pattern classifier to recover the PR performance. While the proposed SFTM has shown great promise, the previous design is impractical. A practical SFTM has to be fast enough, lightweight, automatic, and robust under different conditions with or without disturbances. METHODS: This paper presented a real-time, practical SFTM towards robust EMG PR. A novel fast LDA retraining algorithm and a fully automatic sensor fault detector based on outlier detection were developed, which allowed the SFTM to promptly detect disturbances and recover the PR performance immediately. These components of SFTM were then integrated with the EMG PR module and tested on five able-bodied subjects and a transradial amputee in real-time for classifying multiple hand and wrist motions under different conditions with different disturbance types and levels. RESULTS: The proposed fast LDA retraining algorithm significantly shortened the retraining time from nearly 1Ā s to less than 4Ā ms when tested on the embedded system prototype, which demonstrated the feasibility of a nearly ā€œzero-delayā€ SFTM that is imperceptible to the users. The results of the real-time tests suggested that the SFTM was able to handle different types of disturbances investigated in this study and significantly improve the classification performance when one or multiple EMG signals were disturbed. In addition, the SFTM could also maintain the systemā€™s classification performance when there was no disturbance. CONCLUSIONS: This paper presented a real-time, lightweight, and automatic SFTM, which paved the way for reliable and robust EMG PR for prosthesis control

    A real-time, practical sensor fault-tolerant module for robust EMG pattern recognition

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    BackgroundUnreliability of surface EMG recordings over time is a challenge for applying the EMG pattern recognition (PR)-controlled prostheses in clinical practice. Our previous study proposed a sensor fault-tolerant module (SFTM) by utilizing redundant information in multiple EMG signals. The SFTM consists of multiple sensor fault detectors and a self-recovery mechanism that can identify anomaly in EMG signals and remove the recordings of the disturbed signals from the input of the pattern classifier to recover the PR performance. While the proposed SFTM has shown great promise, the previous design is impractical. A practical SFTM has to be fast enough, lightweight, automatic, and robust under different conditions with or without disturbances.MethodsThis paper presented a real-time, practical SFTM towards robust EMG PR. A novel fast LDA retraining algorithm and a fully automatic sensor fault detector based on outlier detection were developed, which allowed the SFTM to promptly detect disturbances and recover the PR performance immediately. These components of SFTM were then integrated with the EMG PR module and tested on five able-bodied subjects and a transradial amputee in real-time for classifying multiple hand and wrist motions under different conditions with different disturbance types and levels.ResultsThe proposed fast LDA retraining algorithm significantly shortened the retraining time from nearly 1s to less than 4ms when tested on the embedded system prototype, which demonstrated the feasibility of a nearly ā€œzero-delayā€ SFTM that is imperceptible to the users. The results of the real-time tests suggested that the SFTM was able to handle different types of disturbances investigated in this study and significantly improve the classification performance when one or multiple EMG signals were disturbed. In addition, the SFTM could also maintain the systemā€™s classification performance when there was no disturbance.ConclusionsThis paper presented a real-time, lightweight, and automatic SFTM, which paved the way for reliable and robust EMG PR for prosthesis control

    Ultrashort Laser Pulses for Frequency Upconversion

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    Virulence Attributes and Hyphal Growth of C. neoformans Are Quantitative Traits and the MATĪ± Allele Enhances Filamentation

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    Cryptococcus neoformans is a fungal human pathogen with a bipolar mating system. It undergoes a dimorphic transition from a unicellular yeast to hyphal filamentous growth during mating and monokaryotic fruiting. The traditional sexual cycle that leads to the production of infectious basidiospores involves cells of both Ī± and a mating type. Monokaryotic fruiting is a modified form of sexual reproduction that involves cells of the same mating type, most commonly Ī±, which is the predominant mating type in both the environment and clinical isolates. However, some a isolates can also undergo monokaryotic fruiting. To determine whether mating type and other genetic loci contribute to the differences in fruiting observed between Ī± and a cells, we applied quantitative trait loci (QTL) mapping to an inbred population of F(2) progeny. We discovered that variation in hyphal length produced during fruiting is a quantitative trait resulting from the combined effects of multiple genetic loci, including the mating type (MAT) locus. Importantly, the Ī± allele of the MAT locus enhanced hyphal growth compared with the a allele. Other virulence traits, including melanization and growth at 39 Ā°C, also are quantitative traits that share a common QTL with hyphal growth. The Mac1 transcription factor, encoded in this common QTL, regulates copper homeostasis. MAC1 allelic differences contribute to phenotypic variation, and mac1Ī” mutants exhibit defects in filamentation, melanin production, and high temperature growth. Further characterization of these QTL regions will reveal additional quantitative trait genes controlling biological processes central to fungal development and pathogenicity

    Ferroelectric higher-order topological insulator in two dimensions

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    The interplay between ferroelectricity and band topology can give rise to a wide range of both fundamental and applied research. Here, we map out the emergence of nontrivial corner states in two-dimensional ferroelectrics, and remarkably demonstrate that ferroelectricity and corner states are coupled together by crystallographic symmetry to realize the electric control of higher-order topology. Implemented by density functional theory, we identify a series of experimentally synthesized two-dimensional ferroelectrics, such as In2_2Se3_3, BN bilayers, and SnS, as realistic material candidates for the proposed ferroelectric higher-order topological insulators. Our work not only sheds new light on traditional ferroelectric materials but also opens an avenue to bridge the higher-order topology and ferroelectricity that provides a nonvolatile handle to manipulate the topology in next-generation electronic devices
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