166 research outputs found

    Differentiable Retrieval Augmentation via Generative Language Modeling for E-commerce Query Intent Classification

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    Retrieval augmentation, which enhances downstream models by a knowledge retriever and an external corpus instead of by merely increasing the number of model parameters, has been successfully applied to many natural language processing (NLP) tasks such as text classification, question answering and so on. However, existing methods that separately or asynchronously train the retriever and downstream model mainly due to the non-differentiability between the two parts, usually lead to degraded performance compared to end-to-end joint training. In this paper, we propose Differentiable Retrieval Augmentation via Generative lANguage modeling(Dragan), to address this problem by a novel differentiable reformulation. We demonstrate the effectiveness of our proposed method on a challenging NLP task in e-commerce search, namely query intent classification. Both the experimental results and ablation study show that the proposed method significantly and reasonably improves the state-of-the-art baselines on both offline evaluation and online A/B test.Comment: 5 pages, 2 figures; accepted by CIKM202

    Dynamic Object Tracking for Quadruped Manipulator with Spherical Image-Based Approach

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    Exactly estimating and tracking the motion of surrounding dynamic objects is one of important tasks for the autonomy of a quadruped manipulator. However, with only an onboard RGB camera, it is still a challenging work for a quadruped manipulator to track the motion of a dynamic object moving with unknown and changing velocities. To address this problem, this manuscript proposes a novel image-based visual servoing (IBVS) approach consisting of three elements: a spherical projection model, a robust super-twisting observer, and a model predictive controller (MPC). The spherical projection model decouples the visual error of the dynamic target into linear and angular ones. Then, with the presence of the visual error, the robustness of the observer is exploited to estimate the unknown and changing velocities of the dynamic target without depth estimation. Finally, the estimated velocity is fed into the model predictive controller (MPC) to generate joint torques for the quadruped manipulator to track the motion of the dynamical target. The proposed approach is validated through hardware experiments and the experimental results illustrate the approach's effectiveness in improving the autonomy of the quadruped manipulator

    Survival outcomes of autologous breast reconstruction after mastectomy: A matched case-control study

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    BackgroundDue to the lack of strong evidence-based medical evidence, the relationship between autologous breast reconstruction (ABR) after mastectomy and long-term prognosis is unclear. This study aims to explore if ABR after mastectomy is associated with the prognosis of breast cancer (BC) patients based on the data from the Surveillance, Epidemiology, and End Results (SEER) database.MethodsWe collected data for all cases diagnosed with BC who underwent or did not undergo ABR after mastectomy from 2010-2015 in the SEER database. The primary outcome of our study was overall survival (OS) and cancer specific survival (CSS). The Propensity Score-Matched (PSM) analysis was used to eliminate the effects of non-random statistics, setting the caliper as 0.0001 to balance the baseline variables within the groups. Chi-square test, Kaplan-Meier method, univariate and multivariate cox regression analysis were used to analyze the data and subgroup analysis was performed to find the subgroups of people who might benefit from ABR.ResultOf 27893 eligible patients, 11038 patients were matched. The cohort consisted of 5519 (50%) ABR patients and 5519 (50%) non-ABR patients after PSM. After PSM, on multivariate cox regression analysis, ABR still exerted a significant influence on the OS (hazard ratio (HR), 0.83, P< 0.05). However, no statistical difference was shown on CSS (HR, 0.93, P = 0.31). Kaplan-Meier survival analysis showed ABR group had better OS (P = 0.001), but similar CSS (P = 0.174) between ARB and mastectomy groups. Subgroup analysis showed that after matching, those with 50-59 years old, earlier stages of disease, without a marital partner and living in urban areas had better OS after ABR.ConclusionsABR after mastectomy was associated with better OS, but not affect CSS

    Differences in ethylene sensitivity, expression of ethylene biosynthetic genes and vase life among carnation varieties

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    Carnation (Dianthus caryophyllus L.) is a typical ethylene-sensitive cut flower. Variations in carnation vase life and sensitivity to ethylene have been reported, but no detailed analysis has been performed to date. In order to investigate the ethylene sensitivity of different cut carnation varieties and study the effect of ethylene on postharvest physiological changes of different carnation varieties, 14 varieties were used to explore ethylene sensitivity, and six varieties were used to analyze the release pattern of endogenous ethylene and the expression pattern of related genes. The results showed that among the 14 carnation varieties, 'Master' had the strongest ethylene sensitivity and 'Snow White' had the weakest ethylene sensitivity. Ethylene release changes of 'Master' are the terminal ascending type, and 'Cloud Shium', 'Little Pink', 'Seashell', 'Freedom' and 'Snow White' are the similar ethylene leap type. Ethylene biosynthesis genes DcACS1 and DcACO1 of 'Master' were up-regulated the most, and DcACO1 of 'Snow White' was the least up-regulated. The transient silencing and overexpression of DcACS1 and DcACO1 were performed and it was found that transient silencing can significantly delay aging, and overexpression significantly accelerates aging. This study laid the foundation for further research on the molecular mechanism of ethylene regulation of postharvest senescence of cut flowers of carnation, and also indicated the direction for further breeding and artificial screening of new storage tolerant carnation species by gene editing technology

    A COVID-19 Risk Score Combining Chest CT Radiomics and Clinical Characteristics to Differentiate COVID-19 Pneumonia From Other Viral Pneumonias

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    With the continued transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the world, identification of highly suspected COVID-19 patients remains an urgent priority. In this study, we developed and validated COVID-19 risk scores to identify patients with COVID-19. In this study, for patient-wise analysis, three signatures, including the risk score using radiomic features only, the risk score using clinical factors only, and the risk score combining radiomic features and clinical variables, show an excellent performance in differentiating COVID-19 from other viral-induced pneumonias in the validation set. For lesion-wise analysis, the risk score using three radiomic features only also achieved an excellent AUC value. In contrast, the performance of 130 radiologists based on the chest CT images alone without the clinical characteristics included was moderate as compared to the risk scores developed. The risk scores depicting the correlation of CT radiomics and clinical factors with COVID-19 could be used to accurately identify patients with COVID-19, which would have clinically translatable diagnostic and therapeutic implications from a precision medicine perspective

    The second ACTRIS inter-comparison (2016) for Aerosol Chemical Speciation Monitors (ACSM) : Calibration protocols and instrument performance evaluations

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    AbstractThis work describes results obtained from the 2016 Aerosol Chemical Speciation Monitor (ACSM) intercomparison exercise performed at the Aerosol Chemical Monitor Calibration Center (ACMCC, France). Fifteen quadrupole ACSMs (Q_ACSM) from the European Research Infrastructure for the observation of Aerosols, Clouds and Trace gases (ACTRIS) network were calibrated using a new procedure that acquires calibration data under the same operating conditions as those used during sampling and hence gets information representative of instrument performance. The new calibration procedure notably resulted in a decrease in the spread of the measured sulfate mass concentrations, improving the reproducibility of inorganic species measurements between ACSMs as well as the consistency with co-located independent instruments. Tested calibration procedures also allowed for the investigation of artifacts in individual instruments, such as the overestimation of m/z 44 from organic aerosol. This effect was quantified by the m/z (mass-to-charge) 44 to nitrate ratio measured during ammonium nitrate calibrations, with values ranging from 0.03 to 0.26, showing that it can be significant for some instruments. The fragmentation table correction previously proposed to account for this artifact was applied to the measurements acquired during this study. For some instruments (those with high artifacts), this fragmentation table adjustment led to an ?overcorrection? of the f44 (m/z 44/Org) signal. This correction based on measurements made with pure NH4NO3, assumes that the magnitude of the artifact is independent of chemical composition. Using data acquired at different NH4NO3 mixing ratios (from solutions of NH4NO3 and (NH4)2SO4) we observe that the magnitude of the artifact varies as a function of composition. Here we applied an updated correction, dependent on the ambient NO3 mass fraction, which resulted in an improved agreement in organic signal among instruments. This work illustrates the benefits of integrating new calibration procedures and artifact corrections, but also highlights the benefits of these intercomparison exercises to continue to improve our knowledge of how these instruments operate, and assist us in interpreting atmospheric chemistry.Peer reviewe
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