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546 results on '"Zhu, Jinxia"'

1. Value Maximization under Stochastic Quasi-Hyperbolic Discounting

Author

Yan, Kaixin, Wang, Wenyuan, and Zhu, Jinxia

Subjects
Mathematics - Optimization and Control
Abstract

We investigate a value-maximizing problem incorporating a human behavior pattern: present-biased-ness, for a firm which navigates strategic decisions encompassing earning retention/payout and capital injection policies, within the framework of L\'evy processes. We employ the concept of stochastic quasi-hyperbolic discounting to capture the present-biased inclinations and model decision making as an intra-personal game with sophisticated decision-makers. Our analysis yields closed-form solutions, revealing that double-barrier strategies constitute Markov equilibrium strategies. Our findings reveal that firms, influenced by present-biased-ness, initiate dividend payments sooner, diminishing overall value compared to scenarios without present-biased-ness (under exponential discounting). We also discuss bailout optimality, providing necessary and sufficient conditions. The impact of behavioral issues is examined in the Brownian motion and jump diffusion cases., Comment: 42 pages, 14 figures

Published
2024

10. Survey of Research on Personalized News Recommendation Approaches

Author

MENG Xiangfu, HUO Hongjin, ZHANG Xiaoyan, WANG Wanchun, ZHU Jinxia

Subjects
personalized news recommendation, deep learning, graph structure learning, Electronic computers. Computer science, QA75.5-76.95
Abstract

Personalized news recommendation is an important technology to help users obtain the news information they are interested in and alleviate information overload. In recent years, with the development of information technology and society, personalized news recommendation has been increasingly widely studied, and has achieved remarkable success in improving the news reading experience of users. This paper aims to systematically summarize personalized news recommendation methods based on deep learning. Firstly, it introduces personalized news recommendation methods and analyzes their characteristics and influencing factors. Then, the overall framework of personalized news recommendation is given, and the personalized news recommendation methods based on deep learning are analyzed and summarized. On this basis, it focuses on personalized news recommendation methods based on graph structure learning, including user-news interaction graph, knowledge graph and social relationship graph. Finally, it analyzes the challenges of the current personalized news recommendation, discusses how to solve the problems of data sparsity, model interpretability, diversity of recommendation results and news privacy protection in personalized news recommendation system, and puts forward more specific and operable research ideas in the future research direction.

Published
2023
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30. Treatment Response Assessment in Multiple Myeloma: Histogram Analysis of Total Tumor Apparent Diffusion Coefficient based on Whole‐body Diffusion‐weighted MR Imaging.

Author

Gao, Yuhan, Wang, Qin, Zhang, Lu, Li, Shuo, Liu, Dong, Wang, Shitian, Zhu, Jinxia, Zhang, Haibo, Xie, Sheng, Xia, Shuang, Huang, Wenyang, Xue, Huadan, and Li, Jian

Subjects
PROPORTIONAL hazards models, FISHER exact test, RECEIVER operating characteristic curves, MULTIPLE myeloma, MAGNETIC resonance imaging
Abstract

Background: The International Myeloma Working Group (IMWG) consensus criteria for response assessment in multiple myeloma (MM) has methodological limitations. Whole‐body diffusion‐weighted imaging (DWI) with apparent diffusion coefficient (ADC) histogram analysis may be complementary to response assessment of MM. Purpose: To explore the role of histogram analysis of the ADC based on the total tumor volume (ttADC) in response assessment in patients with newly diagnosed MM (NDMM). Study Type: Retrospective. Population: Thirty‐six patients with NDMM. Field Strength/Sequence: 3.0T/single‐shot DWI echo planar imaging (EPI) sequence with an integrated slice‐by‐slice shimming (iShim) technique. Assessment: Baseline (median: 1 day before treatment) and post‐treatment (median: five cycles of therapy) whole‐body DWI were analyzed. A region of interest (ROI) containing lesions on every section of baseline image was drawn to derive the per‐patient total tumor data. Post‐treatment image analysis was based on the same ROI as the corresponding baseline. Histogram metrics were extracted from both ROIs. Patients were categorized into the very good partial response or better (VGPR+) group and the less than VGPR group per the IMWG response criteria for response assessment. Progression‐free survival (PFS) was also calculated. Statistical Tests: Mann–Whitney test and Fisher's exact or Chi‐squared tests, Receiver operating characteristic (ROC) analysis and DeLong test, Kaplan–Meier analysis and Cox proportional hazards model. A two‐tailed P‐value <0.05 was considered statistically significant. Results: Thirty patients were categorized into the VGPR+ group and six into the less than VGPR group. The ttADC histogram changes between post‐treatment and baseline metrics (ΔttADC) revealed significant differences in all percentile values between the VGPR+ and less than VGPR groups. For distinguishing VGPR+, ΔttADC_5th percentile had the largest area under the curve (AUC) (0.950, 95% CI 0.821–0.995). Patients with lower ΔttADC_5th percentile values (cutoff point, 188.193) showed significantly longer PFS (HR = 34.911, 95% CI 6.392–190.677). Data Conclusion: ttADC histogram may facilitate response assessment in patients with NDMM. Level of Evidence: 3 Technical Efficacy: Stage 4 [ABSTRACT FROM AUTHOR]

Published
2024
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31. Dopamine in the regulation of glucose and lipid metabolism: a narrative review.

Author

Li, Zhehong, Zheng, Lifei, Wang, Jing, Wang, Liang, Qi, Yao, Amin, Buhe, Zhu, Jinxia, and Zhang, Nengwei

Subjects
LIPID metabolism, ENERGY metabolism, DOPAMINE receptors, GLUCOSE metabolism, PITUITARY gland, DOPAMINE
Abstract

Objective: Owing to the global obesity epidemic, understanding the regulatory mechanisms of glucose and lipid metabolism has become increasingly important. The dopaminergic system, including dopamine, dopamine receptors, dopamine transporters, and other components, is involved in numerous physiological and pathological processes. However, the mechanism of action of the dopaminergic system in glucose and lipid metabolism is poorly understood. In this review, we examine the role of the dopaminergic system in glucose and lipid metabolism. Results: The dopaminergic system regulates glucose and lipid metabolism through several mechanisms. It regulates various activities at the central level, including appetite control and decision‐making, which contribute to regulating body weight and energy metabolism. In the pituitary gland, dopamine inhibits prolactin production and promotes insulin secretion through dopamine receptor 2. Furthermore, it can influence various physiological components in the peripheral system, such as pancreatic β cells, glucagon‐like peptide‐1, adipocytes, hepatocytes, and muscle, by regulating insulin and glucagon secretion, glucose uptake and use, and fatty acid metabolism. Conclusions: The role of dopamine in regulating glucose and lipid metabolism has significant implications for the physiology and pathogenesis of disease. The potential therapeutic value of dopamine lies in its effects on metabolic disorders. [ABSTRACT FROM AUTHOR]

Published
2024
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42. Optimal financing and dividend distribution in a general diffusion model with regime switching

Author

Zhu, Jinxia and Yang, Hailiang

Subjects
Mathematics - Optimization and Control, Quantitative Finance - Portfolio Management
Abstract

We study the optimal financing and dividend distribution problem with restricted dividend rates in a diffusion type surplus model where the drift and volatility coefficients are general functions of the level of surplus and the external environment regime. The environment regime is modeled by a Markov process. Both capital injections and dividend payments incur expenses. The objective is to maximize the expectation of the total discounted dividends minus the total cost of capital injections. We prove that it is optimal to inject capitals only when the surplus tends to fall below zero and to pay out dividends at the maximal rate when the surplus is at or above the threshold dependent on the environment regime.

Published
2015

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