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Your search keyword '"Zeng, Zitong"' showing total 14 results
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14 results on '"Zeng, Zitong"'

8. What measures are needed to achieve a tobacco endgame target? A Singapore-based simulation study

Author

Zeng, Zitong, Cook, Alex R, and van der Eijk, Yvette

Abstract

BackgroundAn increasing number of countries are pursuing a tobacco ‘endgame’. We sought to determine the combination of measures it would take to achieve a tobacco endgame in the city-state of Singapore.MethodsUsing an open-cohort microsimulation model, we estimated the impact of existing measures (quit programmes, tobacco taxes, flavours ban) and more novel measures (very low nicotine cap, tobacco-free generation, raising the minimum legal age to 25 years), and combinations thereof, on smoking prevalence in Singapore over a 50-year horizon. We used Markov Chain Monte Carlo to estimate transition probabilities between the states of never smoker, current smoker and former smoker, updating each individual’s state across each year with prior distributions derived from national survey data.ResultsWithout new measures, smoking prevalence is expected to rebound from 12.2% (2020) to 14.8% (2070). The only scenarios to achieve a tobacco endgame target within a decade are those combining a very low nicotine cap with a flavours ban. A nicotine cap or tobacco-free generation alone also achieve endgame targets, but after 20 and 39 years, respectively. Taxes, quit programmes, a flavours ban and minimum legal age increase do augment the impact of other measures, but even when combined are insufficient to achieve a tobacco endgame target within 50 years.ConclusionIn Singapore, achieving a tobacco endgame within a decade requires a very low nicotine cap coupled with a tobacco flavours ban, although this target can also be achieved in the long term (within 50 years) with a tobacco-free generation.

Published
2024
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10. IR-drop calibration for Hardware Trojan detection

Author

Yuanhang He, Wanting Zhou, Ji Yang, Lei Li, and Zeng Zitong

Subjects
010302 applied physics, Computer science, business.industry, Electrical engineering, Hardware_PERFORMANCEANDRELIABILITY, 02 engineering and technology, Chip, 01 natural sciences, 020202 computer hardware & architecture, Process variation, Hardware Trojan, 0103 physical sciences, Hardware_INTEGRATEDCIRCUITS, 0202 electrical engineering, electronic engineering, information engineering, Calibration, business, Power network design, Nominal power (photovoltaic), Network analysis, Voltage
Abstract

Process variation is the critical issue in hardware Trojan detection. In the state-of-art works, ring oscillators are employed to address this problem. But ring oscillators are very sensitive to IR-drop effect, which exists ICs. In this paper, based on circuit theory, a IR-drop calibration method is proposed. The nominal power supply voltage and the others power supply voltage with a very small difference of the nominal power supply voltage are applied to the test chip. It is assumed that they have the same IR-drop ΔV. Combined with these measured data, the value of V th + ΔV, can be obtained by mathematic analysis. The typical V th from circuit simulation is used to compute ΔV. We studied the proposed method in a tested chip.

Published
2020
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14. Personalized chemotherapy selection for patients with triple-negative breast cancer using deep learning.

Author

Yang X, Vladmirovich RI, Georgievna PM, Sergeevna AY, He M, Zeng Z, Qiang Y, Cao Y, and Sergeevich KT

Abstract

Background: Potential uncertainties and overtreatment exist in adjuvant chemotherapy for triple-negative breast cancer (TNBC) patients., Objectives: This study aims to explore the performance of deep learning (DL) models in personalized chemotherapy selection and quantify the impact of baseline characteristics on treatment efficacy., Methods: Patients who received treatment recommended by models were compared to those who did not. Overall survival for treatment according to model recommendations was the primary outcome. To mitigate bias, inverse probability treatment weighting (IPTW) was employed. A mixed-effect multivariate linear regression was employed to visualize the influence of certain baseline features of patients on chemotherapy selection., Results: A total of 10,070 female TNBC patients met the inclusion criteria. Treatment according to Self-Normalizing Balanced (SNB) individual treatment effect for survival data model recommendations was associated with a survival benefit (IPTW-adjusted hazard ratio: 0.53, 95% CI, 0.32-8.60; IPTW-adjusted risk difference: 12.90, 95% CI, 6.99-19.01; IPTW-adjusted the difference in restricted mean survival time: 5.54, 95% CI, 1.36-8.61), which surpassed other models and the National Comprehensive Cancer Network guidelines. No survival benefit for chemotherapy was seen for patients not recommended to receive this treatment. SNB predicted older patients with larger tumors and more positive lymph nodes are the optimal candidates for chemotherapy., Conclusion: These findings suggest that the SNB model may identify patients with TNBC who could benefit from chemotherapy. This novel analytical approach may provide debiased individual survival information and treatment recommendations. Further research is required to validate these models in clinical settings with more features and outcome measurements., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Yang, Vladmirovich, Georgievna, Sergeevna, He, Zeng, Qiang, Cao and Sergeevich.)

Published
2024
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