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354 results on '"Li, Wendi"'

56. Safe Production Strategies for Soil-Covered Cultivation of Morel in Heavy Metal-Contaminated Soils

Author

Li, Xue, primary, Fu, Tianhong, additional, Li, Hongzhao, additional, Zhang, Bangxi, additional, Li, Wendi, additional, Zhang, Baige, additional, Wang, Xiaomin, additional, Wang, Jie, additional, Chen, Qing, additional, He, Xuehan, additional, Chen, Hao, additional, Zhang, Qinyu, additional, Zhang, Yujin, additional, Yang, Rende, additional, and Peng, Yutao, additional

Published
2023
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63. Global crisis citizenship and deliberation: A comparative study of young generations' climate communication in Hong Kong and Melbourne

Author

Li, Wendi and Li, Wendi

Abstract

With the rise of the unprecedented global youth climate activism in 2019, the young generations are now at the forefront of global climate communication and politics. However, their spontaneous climate communication and engagement have rarely been approached from a transnational comparative perspective. This thesis aims to fill this gap by assessing how climate-concerned young individuals in Hong Kong and Melbourne perceive the global climate crisis, communicate about it, and engage with this epochal challenge. Relating to Mannheim’s (1952) theory of generations, this thesis argues that generation-specific crisis consciousness cultivated during these young individuals’ formative years enables them to form a “generation entelechy” and generational agency to respond to climate change. Focusing on these specific forms of locally based yet globalised young publics in two global cities, this thesis specifically investigates the way they construct their own civic identity and form public opinions in the times of the climate crisis. ‘Global crisis citizenship’ and ‘transplanetary dialogic deliberation’ are conceptualised accordingly to encapsulate these two processes and related practices. Moving beyond methodological nationalism, this thesis theorises these young generations’ crisis agency in a globalised context and offers a translocal perspective to compare their climate perceptions and communication experiences. This thesis draws on in-depth interviews with forty climate-concerned young adults in these two cities (n = 20 in each city, n = 40 in total). The research reveals that most participants perceive climate change as a complex crisis, construct their identity as global citizens in the context of the climate crisis, and unfold the sense of climate justice in various dimensions. Despite being on two different continents, respondents from the two cities share similar climate information sources and demonstrate comparable reasoning and justification skills. They also

Published
2023

65. Room‐Temperature Intrinsic Ferromagnetic Chromium Tellurium Compounds with Thickness‐Tunable Magnetic Texture

Author

Wen, Yao, primary, Liang, Shiheng, additional, Dong, Zhuo, additional, Cheng, Ruiqing, additional, Yin, Lei, additional, He, Peng, additional, Wang, Hao, additional, Zhai, Baoxing, additional, Zhao, Yang, additional, Li, Wendi, additional, Jiang, Jian, additional, Li, Zhongwei, additional, Liu, Chuansheng, additional, Dong, Kaifeng, additional, He, Jun, additional, and Zhang, Kai, additional

Published
2023
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67. Towards Hierarchical Policy Learning for Conversational Recommendation with Hypergraph-based Reinforcement Learning

Author

Zhao1, Sen, Wei, Wei, Liu, Yifan, Wang, Ziyang, Li, Wendi, Mao, Xian-Ling, Zhu, Shuai, Yang, Minghui, and Wen, Zujie

Subjects
FOS: Computer and information sciences, Information Retrieval (cs.IR), Computer Science - Information Retrieval
Abstract

Conversational recommendation systems (CRS) aim to timely and proactively acquire user dynamic preferred attributes through conversations for item recommendation. In each turn of CRS, there naturally have two decision-making processes with different roles that influence each other: 1) director, which is to select the follow-up option (i.e., ask or recommend) that is more effective for reducing the action space and acquiring user preferences; and 2) actor, which is to accordingly choose primitive actions (i.e., asked attribute or recommended item) that satisfy user preferences and give feedback to estimate the effectiveness of the director's option. However, existing methods heavily rely on a unified decision-making module or heuristic rules, while neglecting to distinguish the roles of different decision procedures, as well as the mutual influences between them. To address this, we propose a novel Director-Actor Hierarchical Conversational Recommender (DAHCR), where the director selects the most effective option, followed by the actor accordingly choosing primitive actions that satisfy user preferences. Specifically, we develop a dynamic hypergraph to model user preferences and introduce an intrinsic motivation to train from weak supervision over the director. Finally, to alleviate the bad effect of model bias on the mutual influence between the director and actor, we model the director's option by sampling from a categorical distribution. Extensive experiments demonstrate that DAHCR outperforms state-of-the-art methods.

Published
2023
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74. Insights into Opposite and Positive Effects of Biochar and Organic Fertilizer on Red Soil Properties and Growth of Pennisetum giganteum.

Author

Zhang, Bangxi, Li, Xue, Fu, Tianhong, Li, Hongzhao, Li, Wendi, Zhang, Qinyu, Wang, Jie, Chen, Bo, Yang, Rende, Zhang, Baige, Wang, Xiaomin, He, Xuehan, Chen, Hao, Zhang, Yujin, and Peng, Yutao

Abstract

Biochar (BC) and organic fertilizers (OFs) are both organic soil amendments that can be used to improve soil quality, but their effects on soil physicochemical properties and microbial structures may be different. Comparative studies can help us understand the advantages and disadvantages of different types of soils. In the current research, five treatments, including a control group (CK), two concentrations of biochar (2% BC and 4% BC), and two concentrations of organic fertilizer (2% OF and 4% OF) and their effects on soil properties, enzyme activities, and bacterial diversity were evaluated. The BC and OF significantly increased the soil EC, pH, and soil nutrients (p < 0.05). The 2% BC increased the biomass of Pennisetum giganteum by 41.7%. The 4% BC and OF reduced the biomass of P. giganteum. Furthermore, the observed decrease in the P. giganteum yield following the application of the 4% BC can be attributed to reductions in the available phosphorus (AP) and CaCl2-P, as well as alterations in the soil enzyme activity. However, the negative impact of OFs on crop yield may be associated with an increased EC, elevated abundance of soil-borne pathogens, and decreased levels of beneficial microorganisms. In summary, a comparative study of the effects of BC and OF on the growth of P. giganteum in acidic soil is of great significance for improving the soil quality, promoting the development of organic agriculture, protecting the environment, and promoting land reclamation. [ABSTRACT FROM AUTHOR]

Published
2023
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76. Fairness and Trust in Human Bot Interaction - Amendment

Author

Makovi, Kinga, Li, Wendi, and Rahwan, Talal

Subjects
Social and Behavioral Sciences
Abstract

We are filing an amendment to the pre-analysis plan (egap.org, \#20190912AD), from now on PAP, after the analyses of the outcome data. In the attached document first, we discuss the motivation for this amendment, then, we discuss the content of the amendment. We do not restate the particulars of the experiment, conditions and procedures here, as no change have been made to the particulars of the experiment, or its procedures.

Published
2022
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88. Model Prediction for Lead-acid Batteries with Super-capacitor Anodes

Author

LI, WENDI

Subjects
Chemical engineering, BMS, Lead-acid batteries, Lifetime, Model Prediction, SOC, SOH
Abstract

The existing prediction models used in Battery Management Systems (BMS) for lead-acid batteries have difficulty in applying to lead-acid batteries with changed structure or materials. Four different lifetime prediction models of lead-acid batteries to be mainly used as energy storage for PV systems, EV, and hybrid EV are examined. Equivalent full cycles to failure, “Rain flow” cycles were counting, the Schiffer weighted Ah-throughput model and recurrent Neural Network-based Model are discussed for the accessibility and availability of the lead-acid batteries with the supercapacitor anode (hybrid batteries). By examining the mechanism, “Rain flow” cycles counting, the Schiffer weighted Ah-throughput model and recurrent Neural Network-based Model were three models could be used in hybrid batteries. By comparing the accuracy of these models in photovoltaic systems, the Schiffer weighted Ah-throughput model and recurrent Neural Network-based Model were selected to be the promising solutions. A modification of the Schiffer weighted Ah-throughput model is discussed based on the chemical mechanism. All possible effects are taking into account in the modified model based on the detailed analysis. Further estimations can be simply conducted through the factory data sheet of hybrid batteries.

Published
2016

93. Spin–Orbit Torque-Driven Memristor in L10 FePt Systems with Nanoscale-Thick Layers for Neuromorphic Computing.

Author

Tao, Ying, Sun, Chao, Li, Wendi, Wang, Cen, Jin, Fang, Zhang, Yue, Guo, Zhe, Zheng, Yuhong, Wang, Xiaoguang, and Dong, Kaifeng

Abstract

In this study, a memristor driven by spin–orbit torque (SOT) is realized in the nanoscale thickness L10 FePt systems with high perpendicular magnetization anisotropy (PMA). Due to the domain nucleation and expansion driven by current pulses, multilevel Hall resistance states can be continuously tuned by current density, where the memristive states are retained by the domain wall pinning effects. The properties of multilevel resistance states for samples with different structures are associated with the magnitude of field-like torque, and the larger efficiency of field-like torque enhances multiple resistance characteristics. Furthermore, the stable memristive behavior is obtained in the FePt/MgO/NiFe heterostructure. Finally, a three-layer multilayer perceptron (MLP) neural network is built to perform the MNIST handwritten digit recognition task based on the device's memristive behaviors, and the accuracy of weight update can reach up to 88.55%. These results pave the way for the application of L10 FePt nanomaterials in neuromorphic computing. [ABSTRACT FROM AUTHOR]

Published
2023
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