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Your search keyword '"Wang, Xiaoxiao"' showing total 342 results
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342 results on '"Wang, Xiaoxiao"'

1. Interface suppressed nematicity and enhanced superconductivity of FeSe/NdFeO3 in the low doping regime

Author

Li, Chihao, Song, Yuanhe, Wang, Xiaoxiao, Lei, Minyinan, Chen, Xiaoyang, Xu, Haichao, Peng, Rui, and Feng, Donglai

Subjects
Condensed Matter - Superconductivity, Condensed Matter - Materials Science
Abstract

The discovery of interface-enhanced superconductivity in single-layer FeSe/oxides has generated intensive research interests. Beyond the family of FeSe interfaced with various TiO$_2$ terminated oxides, high pairing temperature up to 80~K has been recently observed in FeSe interfaced with FeO$_x$-terminated LaFeO$_3$. Here we successfully extend the FeSe/FeO$_x$ superconducting interface to FeSe/NdFeO$_3$, by constructing 1uc-FeSe/6uc-NdFeO$_3$/Nb:SrTiO$_3$ heterostructures. Intriguingly, well-annealed FeSe/NdFeO$_3$ exhibits a low doping level of 0.038$\sim$0.046 ~e$^-/$Fe which deviates universally magic doping level (0.10$\sim$0.12 e$^-/\rm{Fe}$) and provides a new playground for studying the FeSe/oxide interface in the low electron-doped regime. Comparing it with thick FeSe films at the comparable electron doping level induced by surface potassium dosing, FeSe/NdFeO$_3$ shows a larger superconducting gap and the absence of a nematic gap, indicating an enhancement of the superconductivity and suppression of nematicity by the FeSe/FeO$_x$ interface. These results not only expand the FeSe/FeO$_x$ superconducting family but also enrich the current understanding on the roles of the oxide interface., Comment: 8 pages, 4 figures

Published
2024
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2. Reliable Interval Prediction of Minimum Operating Voltage Based on On-chip Monitors via Conformalized Quantile Regression

Author

Yin, Yuxuan, Wang, Xiaoxiao, Chen, Rebecca, He, Chen, and Li, Peng

Subjects
Electrical Engineering and Systems Science - Systems and Control, Computer Science - Artificial Intelligence, Computer Science - Hardware Architecture
Abstract

Predicting the minimum operating voltage ($V_{min}$) of chips is one of the important techniques for improving the manufacturing testing flow, as well as ensuring the long-term reliability and safety of in-field systems. Current $V_{min}$ prediction methods often provide only point estimates, necessitating additional techniques for constructing prediction confidence intervals to cover uncertainties caused by different sources of variations. While some existing techniques offer region predictions, but they rely on certain distributional assumptions and/or provide no coverage guarantees. In response to these limitations, we propose a novel distribution-free $V_{min}$ interval estimation methodology possessing a theoretical guarantee of coverage. Our approach leverages conformalized quantile regression and on-chip monitors to generate reliable prediction intervals. We demonstrate the effectiveness of the proposed method on an industrial 5nm automotive chip dataset. Moreover, we show that the use of on-chip monitors can reduce the interval length significantly for $V_{min}$ prediction., Comment: Accepted by DATE 2024. Camera-ready version

Published
2024

12. Study on denitrification with coffee pectin hydrolysate as carbon source

Author

LUO Xuejing, ZHONG Yijian, LI Jincheng, LU Zuxian, WANG Xiaoxiao, and LI Xinyue

Subjects
denitrification, carbon source, biological denitrification, coffee pectin, Environmental technology. Sanitary engineering, TD1-1066
Abstract

Coffee pectin hydrolysate as an additional carbon source, the denitrification performance was explored by analyzing the denitrification effect in denitrifying biofilter(DNBF) reactor under different HRT and m(COD)/m(TN) (C/N) and microbial community characteristics, and compared with the traditional carbon source of sodium acetate. The results showed that the optimal HRT for the coffee pectin hydrolysate system was 1 h, and the optimal C/N was 6. Under these conditions, when the influent TN and NH4+-N were (33.97±2.06) mg/L and (3.09±0.19) mg/L respectively, coffee pectin hydrolysate as carbon source could reduce the effluent TN and NH4+-N to (3.12±0.59) mg/L and(2.19±0.14) mg/L, respectively. The effluent NO3--N was stabilized below 1 mg/L, and the removal rate reached 97.13%. NO2--N had no obvious accumulation. The NO3--N removed by denitrification per unit COD was 0.22 g/g, which was close to that of the control group sodium acetate. The microbial diversity in the system of coffee pectin hydrolysate was better than that of sodium acetate. There were a large quantities of microorganisms with organic degradation function and denitrification function, such as Zoogloea, Ignavibacterium, unclassified_prolixibacitraceae and Longilinea, which ensured the denitrification effect of coffee pectin hydrolysate as a carbon source.

Published
2024
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13. Advances in intensive antihypertensive treatment in hypertensive patients complicated with cardiovascular disease

Author

Zhang Rongzhen, Jia Min, Lou Doudou, Wang Xiaoxiao, Wang Liang, Wang Rutao, Tao Ling

Subjects
hypertension, intensive antihypertensive treatment, coronary heart disease, heart failure, atrial fibrillation, Medicine
Abstract

Hypertension is a serious public health problem worldwide and a major risk factor for cardiovascular disease. Hypertensive patients are constantly complicated with cardiovascular disease. Effective blood pressure control could improve clinical prognosis of these patients. In June 2023， 2023 ESH Guidelines for the management of arterial hypertension were released with updated recommendations for the timing of starting antihypertensive therapy. For patients with normal high-value blood pressure with prior cardiovascular disease， the guidelines recommend initiating antihypertensive therapy from 130/80 mmHg. The 2023 edition of the Chinese Guidelines for the Prevention and Control of Hypertension also recommends that the target blood pressure for those with high and very high cardiovascular risk can be further reduced to less than 130/80 mmHg. This suggests that greater clinical benefit can be achieved from intensive blood pressure control in hypertensive patients with comorbid cardiovascular disease. In recent years， multiple studies have shown the advantages of intensive blood pressure management in hypertensive patients. In this article， the progress in clinical studies related to intensive blood pressure control in hypertensive populations complicated with different cardiovascular diseases was reviewed， aiming to provide insight and evidence for intensive antihypertensive treatment in these patients.

Published
2024
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14. Physicochemical Properties, Structural Characterization, Immunoenhancing and Hypoglycemic Activities of Fucoidan Extracts from Two Sargassums Species

Author

CHEN Shutong, ZHOU Qingling, YANG Ruiyu, WANG Xiaoxiao, DING Rui, LI Rui, LUO Lianxiang, ZHONG Saiyi,

Subjects
sargassum, fucoidan, physicochemical properties, structural characterization, immunomodulatory, hypoglycemic, Food processing and manufacture, TP368-456
Abstract

In this study, the chemical compositions, structures, immunomodulatory and hypoglycemic activities of fucoidans from Sargassum zhangii (SZ-Fuc) and Sargassum hemiphylla (SH-Fuc) were analyzed and compared. The results showed that the sulfate group content and molecular mass of SZ-Fuc were (29.74 ± 0.01)% and 111.28 kDa, respectively, and SZ-Fuc had a relatively loose surface structure. The main chain of SZ-Fuc was composed of (→1) linked fucose, xylose, glucose, mannose and galactose, (1→3)- and (1→4)- linked xylose, (1→2)-linked mannose, (1→3)-, (1→4)- and (1→6)-linked galactose, and (1→4)- and (1→6)-linked glucose. Meanwhile, the sulfate group content and molecular mass of SH-Fuc were (44.11 ± 0.01)% and 1 166.48 kDa, respectively, SH-Fuc had a compact surface structure, and its main chain contained (→1), (1→3)- and (1→4)-linked fucose, (→1), (1→4)- and (1→6)-linked glucose, (→1) and (1→2)-linked mannose, and (1→4)-linked galactose. Besides, both SZ-Fuc and SH-Fuc had branched structures. They significantly increased NO release from RAW264.7 cells and improved the protein expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), indicating good immunomodulatory activity. The immunomodulatory activity of SZ-Fuc was better than that of SH-Fuc, while the inhibitory effect of SH-Fuc on α-glucosidase was better than that of SZ-Fuc, suggesting that SH-Fuc had better hypoglycemic potential. This study can provide a theoretical basis for polysaccharides from S. zhangii and S. hemiphylla in the development of functional and nutritional foods with immunomodulatory and blood glucose-reducing activity.

Published
2024
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35. Advancing Reinforcement Learning: Multi-Agent Optimization, Opportunistic Exploration, and Causal Interpretation

Author

Wang, Xiaoxiao

Subjects
African literature, Computer science, Electrical engineering, causal explanation, contextual bandit, multi-task learning, opportunistic learning, reinforcement learning
Abstract

Reinforcement learning (RL), a critical subfield of machine learning, effectively models sequential decision-making scenarios for agents operating in various environments. Despite its extensive applications, RL encounters significant challenges in real world settings, particularly regarding limited data availability, the exploration-exploitation trade-off, and the lack of explainability. In this dissertation, I explore these issues through three distinct lenses. Firstly, I improve data efficiency in situations involving multiple agents or tasks. Secondly, I propose opportunistic learning algorithms in environments with varying exploration costs. Thirdly, I interpret the agent's learned policy through causal explanations. The following sections outline the contributions. Initially, I study online global optimization in multi-agent situations. Cellular network configuration is a suitable application area experiencing these challenges, including the scarcity of diverse historical data, constrained experimental budgets imposed by network operators, and highly complex and unknown network performance functions. To overcome these challenges, I introduce an online-learning-based joint-optimization algorithm combining neural network regression with Gibbs sampling, which considerably outperforms distributed Q-learning in overall performance and ramp-up time. By leveraging similarities among tasks/base stations, I propose a kernel-based multi-task contextual bandit algorithm with the similarity estimated via conditional kernel embedding. These algorithms notably outperform the default cellular network configuration and the respective baseline algorithms.Next, I focus on opportunistic learning, where the exploration cost in RL varies based on different environmental conditions. Given that exploration cost directly impacts the regret of selecting a sub-optimal action, I design the learning strategy to explore more when the cost is low and exploit when the cost is high. I propose an AdaLinUCB algorithm for opportunistic contextual bandits to balance the exploration-exploitation trade-off adaptively. My algorithm significantly outperforms existing contextual bandit algorithms in scenarios with large exploration cost fluctuations. I further develop two algorithms OppUCRL2 and OppPSRL for the finite-horizon episodic Markov decision process, demonstrating the benefits of opportunistic RL. My algorithms balance the exploration-exploitation trade-off dynamically through a variation factor dependent optimism, leading to superior performance. These results are supported by theoretical regret bound analyses ensuring their performance.Lastly, I aim to enhance RL's interpretability by providing causal explanations. My approach quantifies the causal influence of states on actions and their temporal impact, thereby surpassing associative methods in RL policy explanation. I propose a mechanism to quantify the individual-level causal counterfactual path-specific importance score for a structural causal model. This mechanism effectively evaluates causal influence in decision chains, allowing us to comprehend better how a specific decision variable influences an outcome variable.

Published
2024

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