154 research outputs found

    Improving CTC-AED model with integrated-CTC and auxiliary loss regularization

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    Connectionist temporal classification (CTC) and attention-based encoder decoder (AED) joint training has been widely applied in automatic speech recognition (ASR). Unlike most hybrid models that separately calculate the CTC and AED losses, our proposed integrated-CTC utilizes the attention mechanism of AED to guide the output of CTC. In this paper, we employ two fusion methods, namely direct addition of logits (DAL) and preserving the maximum probability (PMP). We achieve dimensional consistency by adaptively affine transforming the attention results to match the dimensions of CTC. To accelerate model convergence and improve accuracy, we introduce auxiliary loss regularization for accelerated convergence. Experimental results demonstrate that the DAL method performs better in attention rescoring, while the PMP method excels in CTC prefix beam search and greedy search

    Contour detection network for zero-shot sketch-based image retrieval

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    Abstract Zero-shot sketch-based image retrieval (ZS-SBIR) is a challenging task that involves searching natural images related to a given hand-drawn sketch under the zero-shot scene. The previous approach projected image and sketch features into a low-dimensional common space for retrieval, and used semantic features to transfer the knowledge of seen to unseen classes. However, it is not effective enough to align multimodal features when projecting them into a common space, since the styles and contents of sketches and natural images are different and they are not one-to-one correspondence. To solve this problem, we propose a novel three-branch joint training network with contour detection network (called CDNNet) for the ZS-SBIR task, which uses contour maps as a bridge to align sketches and natural images to alleviate the domain gap. Specifically, we use semantic metrics to constrain the relationship between contour images and natural images and between contour images and sketches, so that natural image and sketch features can be aligned in the common space. Meanwhile, we further employ second-order attention to capture target subject information to increase the performance of retrieval descriptors. In addition, we use a teacher model and word embedding method to transfer the knowledge of the seen to the unseen classes. Extensive experiments on two large-scale datasets demonstrate that our proposed approach outperforms state-of-the-art CNN-based models: it improves by 2.6% on the Sketchy and 1.2% on TU-Berlin datasets in terms of mAP

    Soybean reduced internode 1 determines internode length and improves grain yield at dense planting

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    Abstract Major cereal crops have benefitted from Green Revolution traits such as shorter and more compact plants that permit high-density planting, but soybean has remained relatively overlooked. To balance ideal soybean yield with plant height under dense planting, shortening of internodes without reducing the number of nodes and pods is desired. Here, we characterized a short-internode soybean mutant, reduced internode 1 (rin1). Partial loss of SUPPRESSOR OF PHYA 105 3a (SPA3a) underlies rin1. RIN1 physically interacts with two homologs of ELONGATED HYPOCOTYL 5 (HY5), STF1 and STF2, to promote their degradation. RIN1 regulates gibberellin metabolism to control internode development through a STF1/STF2–GA2ox7 regulatory module. In field trials, rin1 significantly enhances grain yield under high-density planting conditions comparing to its wild type of elite cultivar. rin1 mutants therefore could serve as valuable resources for improving grain yield under high-density cultivation and in soybean–maize intercropping systems

    Precision control in lattice calculation of x-dependent pion distribution amplitude

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    We present a new Bjorken x-dependence analysis of a previous lattice quantum chromodynamics data for the pion distribution amplitude from MILC configurations with three lattice spacing a=0.06,0.09,0.12 fm. A leading renormalon resummation in renormalization as well as the perturbative matching kernel in the framework of large momentum expansion generates the power accuracy of the matching to the light-cone amplitude. Meanwhile, a small momentum log resummation is implemented for both the quark momentum xPz and the antiquark momentum (1−x)Pz inside a meson of boost momentum Pz up to 1.72 GeV along the z direction, allowing us to have more accurate determination of the x-dependence in the middle range. Finally, we use the complementarity between the short-distance factorization and the large momentum expansion to constrain the endpoint regions x∼0,1, thus obtaining the full-range x-dependence of the amplitude

    Resumming quark's longitudinal momentum logarithms in LaMET expansion of lattice PDFs

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    In the large-momentum expansion for parton distribution functions (PDFs), the natural physics scale is the longitudinal momentum (pz) of the quarks (or gluons) in a large-momentum hadron. We show how to expose this scale dependence through resumming logarithms of the type lnn⁡pz/μ in the matching coefficient, where μ is a fixed renormalization scale. The result enhances the accuracy of the expansion at moderate pz>1 GeV, and at the same time, clearly shows that the partons cannot be approximated from quarks with pz∼ΛQCD which are not predominantly collinear with the parent hadron momentum, consistent with power counting of the large-momentum effective theory. The same physics mechanism constrains the coordinate space expansion at large distances z, the conjugate of pz, as illustrated in the example of fitting the moments of the PDFs

    Improving Genomic Prediction Accuracy in the Chinese Holstein Population by Combining with the Nordic Holstein Reference Population

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    The size of the reference population is critical in order to improve the accuracy of genomic prediction. Indeed, improving genomic prediction accuracy by combining multinational reference populations has proven to be effective. In this study, we investigated the improvement of genomic prediction accuracy in seven complex traits (i.e., milk yield; fat yield; protein yield; somatic cell count; body conformation; feet and legs; and mammary system conformation) by combining the Chinese and Nordic Holstein reference populations. The estimated genetic correlations between the Chinese and Nordic Holstein populations are high with respect to protein yield, fat yield, and milk yield—whereby these correlations range from 0.621 to 0.720—and are moderate with respect to somatic cell count (0.449), but low for the three conformation traits (which range from 0.144 to 0.236). When utilizing the joint reference data and a two-trait GBLUP model, the genomic prediction accuracy in the Chinese Holsteins improves considerably with respect to the traits with moderate-to-high genetic correlations, whereas the improvement in Nordic Holsteins is small. When compared with the single population analysis, using the joint reference population for genomic prediction in younger animals, results in a 2.3 to 8.1 percent improvement in accuracy. Meanwhile, 10 replications of five-fold cross-validation were also implemented in order to evaluate the performance of joint genomic prediction, thereby resulting in a 1.6 to 5.2 percent increase in accuracy. With respect to joint genomic prediction, the bias was found to be quite low. However, for traits with low genetic correlations, the joint reference data do not improve the prediction accuracy substantially for either population

    Leading Power Accuracy in Lattice Calculations of Parton Distributions

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    In lattice-QCD calculations of parton distribution functions (PDFs) via large-momentum effective theory, the leading power (twist-three) correction appears as O(ΛQCD/Pz){\cal O}(\Lambda_{\rm QCD}/P^z) due to the linear-divergent self-energy of Wilson line in quasi-PDF operators. For lattice data with hadron momentum PzP^z of a few GeV, this correction is dominant in matching, as large as 30\% or more. We show how to eliminate this uncertainty through choosing the mass renormalization parameter consistently with the resummation scheme of the infrared-renormalon series in perturbative matching coefficients. An example on the lattice pion PDF data at Pz=1.9P^z = 1.9 GeV shows an improvement of matching accuracy by a factor of more than 353\sim 5 in the expansion region x=0.20.5x= 0.2\sim 0.5.Comment: Updated to version published on PL

    Development and validation of a dynamic nomogram based on conventional ultrasound and contrast-enhanced ultrasound for stratifying the risk of central lymph node metastasis in papillary thyroid carcinoma preoperatively

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    PurposeThe aim of this study was to develop and validate a dynamic nomogram by combining conventional ultrasound (US) and contrast-enhanced US (CEUS) to preoperatively evaluate the probability of central lymph node metastases (CLNMs) for patients with papillary thyroid carcinoma (PTC).MethodsA total of 216 patients with PTC confirmed pathologically were included in this retrospective and prospective study, and they were divided into the training and validation cohorts, respectively. Each cohort was divided into the CLNM (+) and CLNM (−) groups. The least absolute shrinkage and selection operator (LASSO) regression method was applied to select the most useful predictive features for CLNM in the training cohort, and these features were incorporated into a multivariate logistic regression analysis to develop the nomogram. The nomogram’s discrimination, calibration, and clinical usefulness were assessed in the training and validation cohorts.ResultsIn the training and validation cohorts, the dynamic nomogram (https://clnmpredictionmodel.shinyapps.io/PTCCLNM/) had an area under the receiver operator characteristic curve (AUC) of 0.844 (95% CI, 0.755–0.905) and 0.827 (95% CI, 0.747–0.906), respectively. The Hosmer–Lemeshow test and calibration curve showed that the nomogram had good calibration (p = 0.385, p = 0.285). Decision curve analysis (DCA) showed that the nomogram has more predictive value of CLNM than US or CEUS features alone in a wide range of high-risk threshold. A Nomo-score of 0.428 as the cutoff value had a good performance to stratify high-risk and low-risk groups.ConclusionA dynamic nomogram combining US and CEUS features can be applied to risk stratification of CLNM in patients with PTC in clinical practice

    Threshold resummation for computing large-x parton distribution through large-momentum effective theory

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    Abstract Parton distribution functions (PDFs) at large x are poorly constrained by high-energy experimental data, but extremely important for probing physics beyond standard model at colliders. We study the calculation of PDFs at large-x through large-momentum P z expansion of the lattice quasi PDFs. Similar to deep-inelastic scattering, there are two distinct perturbative scales in the threshold limit where the matching coefficient can be factorized into a space-like jet function at scale P z |1 − y| and a pair of heavy-light Sudakov form factors at scale P z . The matching formula allows us to derive a full renormalization group resummation of large threshold logarithms, and the result is consistent with the known calculation to the next-to-next to leading order (NNLO). This paves the way for direct large-x PDFs calculations in lattice QCD. As by-products, we find that the space-like jet function is related to a time-like version calculated previously through analytic continuation, and the heavy-light Sudakov form factor, calculated here to NNLO, is a universal object appearing as well in the large momentum expansion of quasi transverse-momentum-dependent PDFs and quasi wave-function amplitudes

    Analysis of fractured soft rock characteristics in fault rupture zones and laneway shoring

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    Abstract Fault rupture is a common phenomenon in geotechnical engineering. To prevent rupture, laneway shoring is performed, prior to which, convergence deformation, failure criteria, and fracture development in soft rocks in the fault rupture zone are carefully analyzed. Then, a supporting structure corresponding to the actual situation of the soft rock in the rupture zone is created. Herein, the water-rich laneway shoring through the fault rupture zone of the Hongqingliang coal mine located in the Inner Mongolia Autonomous Region is taken as the research object. Then, the fracture development and characteristics of argillaceous siltstones and laneway shoring cross-fault rupture zone are studied. Site inspection, indoor and field tests, theoretical analysis, numerical simulation, and field monitoring were used for systematic fracture analysis. Results indicated that laneway shoring through the fault fracture zone in the Hongqingliang coal mine could help prevent disasters. This method was extended to laneway supports built through the fault rupture zones in mines in other areas of China