The LpL_p Chord Minkowski problem in a critical interval

Chord measures and $L_p$ chord measures were recently introduced by Lutwak-Xi-Yang-Zhang by establishing a variational formula regarding a family of fundamental integral geometric invariants called chord integrals. Prescribing the $L_p$ chord measure is known as the $L_p$ chord Minkowski problem, which includes the $L_p$ Minkowski problem heavily studied in the past 2 decades as special cases. In the current work, we solve the $L_p$ chord Minkowski problem when $0\leq p<1$, without symmetry assumptions.Comment: revised and to appear in Math. An

Judge’s Advice Utilization: Whose Advice is More Persuasive, AI or Human?

In recent years, especially with the development of Generative AI, more and more people seek advice from AI application when they make important decisions like career choice. The trend raises an important question: Do judges prefer to rely on human or AI advice in different advising scenarios? Although this topic has been discussed variously in research on algorithm appreciation and algorithm aversion, there are still some gaps need to be filled. Based on belief revision theory and the judge-advisor system, this study attempts to explore how advice strategy types (clinical vs. actuarial) and feedback inconsistency will affect judges’ perceived advice utilization when the advisor is different (Human vs. AI). To achieve this objective, a scenario-based online experiment will be carried out to collect data and test our research model

The Role of Postoperative Radiotherapy on Stage N2 Non-small Cell Lung Cancer

Background and objective The clinical value of postoperative radiotherapy (PORT) in stage N2 nonsmall-cell lung cancer (NSCLC) is controversy. The aim of this study is to analyze the efficacy of PORT in subgroup of stage N2 NSCLC, which can help clinicians to choose proper patients for PORT. Methods Clinical data of 359 patients with stage N2 NSCLC treated with radical surgery between Mar. 2000 and Jul. 2005 were retrospectively reviewed. Two hundred and seven patients received adjuvant chemotherapy and one hundred and four patients received adjuvant radiotherapy. First, the group of patients were analyzed to evaluate the factors affecting the overall survival. The all patients were divided based on tumor size and the number of lymph node metastasis station (single station or multiple station) so as to evaluate the role of PORT. The endpoint was overall survival (OS) and local recurrence-free survival (LRFS). Kaplan-Meier method was used to calculate the OS, LRFS and Log-rank was used to compare the difference in OS and LRFS between different groups. Results The median duration of follow-up was 2.3 years. 224 patients died. The median survival was 1.5 years and 1, 3, 5-year survival were 78%, 38% and 26%. Univariate analysis showed tumor size, the number of lymph node metastasis station and PORT were correlated with OS. Among patients, 5-year survival rates in PORT and non-PORT were 29% and 24% (P=0.047) respectively. In subgroups, PORT was related with high survival in patients with multiple station N2 compared to non-PORT: 36% vs 20% (P=0.013) and 33% vs 15% (P=0.002) in patients in patients with tumor size > 3 cm. Also, it was related with low local recurrence compared to non-PORT: 65% vs 48% (P=0.006) and 62% vs 48% (P=0.033). Conclusion PORT can improve overall survival for N2 NSCLC, especially the patients with the factors as follows: tumor size &gt; 3 cm and multiple station N2 can benefit from PORT more or less

Radiation produces differential changes in cytokine profiles in radiation lung fibrosis sensitive and resistant mice

<p>Abstract</p> <p>Background</p> <p>Recent research has supported that a variety of cytokines play important roles during radiation-induced lung toxicity. The present study is designed to investigate the differences in early cytokine induction after radiation in sensitive (C57BL/6) and resistant mice (C3H).</p> <p>Results</p> <p>Twenty-two cytokines in the lung tissue homogenates, bronchial lavage (BAL) fluids, and serum from 3, 6, 12, 24 hrs to 1 week after 12 Gy whole lung irradiation were profiled using a microsphere-based multiplexed cytokine assay. The majority of cytokines had similar baseline levels in C57BL/6 and C3H mice, but differed significantly after radiation. Many, including granulocyte colony-stimulating factor (G-CSF), interleukin-6 (IL-6), and keratinocyte-derived chemokine (KC) were elevated significantly in specimens from both strains. They usually peaked at about 3–6 hrs in C57BL/6 and 6–12 hrs in C3H. At 6 hrs in lung tissue, G-CSF, IL-6, and KC increased 6, 8, and 11 fold in C57BL/6 mice, 4, 3, and 3 fold in the C3H mice, respectively. IL-6 was 10-fold higher at 6 hrs in the C57BL/6 BAL fluid than the C3H BAL fluid. MCP-1, IP-10, and IL-1α also showed some differences between strains in the lung tissue and/or serum. For the same cytokine and within the same strain of mice, there were significant linear correlations between lung tissue and BAL fluid levels (R²ranged 0.46–0.99) and between serum and tissue (R²ranged 0.56–0.98).</p> <p>Conclusion</p> <p>Radiation induced earlier and greater temporal changes in multiple cytokines in the pulmonary fibrosis sensitive mice. Positive correlation between serum and tissue levels suggests that blood may be used as a surrogate marker for tissue.</p

Neural Chinese Word Segmentation with Lexicon and Unlabeled Data via Posterior Regularization

Existing methods for CWS usually rely on a large number of labeled sentences to train word segmentation models, which are expensive and time-consuming to annotate. Luckily, the unlabeled data is usually easy to collect and many high-quality Chinese lexicons are off-the-shelf, both of which can provide useful information for CWS. In this paper, we propose a neural approach for Chinese word segmentation which can exploit both lexicon and unlabeled data. Our approach is based on a variant of posterior regularization algorithm, and the unlabeled data and lexicon are incorporated into model training as indirect supervision by regularizing the prediction space of CWS models. Extensive experiments on multiple benchmark datasets in both in-domain and cross-domain scenarios validate the effectiveness of our approach.Comment: 7 pages, 11 figures, accepted by the 2019 World Wide Web Conference (WWW '19