@article{liu_zhong_wu_fylstra_si_huang_2022, title={Inferring Human-Robot Performance Objectives During Locomotion Using Inverse Reinforcement Learning and Inverse Optimal Control}, volume={7}, ISSN={["2377-3766"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85123342480&partnerID=MN8TOARS}, DOI={10.1109/LRA.2022.3143579}, abstractNote={Quantitatively characterizing a locomotion performance objective for a human-robot system is an important consideration in the assistive wearable robot design towards human-robot symbiosis. This problem, however, has only been addressed sparsely in the literature. In this study, we propose a new inverse approach from observed human-robot walking behavior to infer a human-robot collective performance objective represented in a quadratic form. By an innovative design of human experiments and simulation study, respectively, we validated the effectiveness of two solution approaches to solving the inverse problem using inverse reinforcement learning (IRL) and inverse optimal control (IOC). The IRL-based experiments of human walking with robotic transfemoral prosthesis validated the realistic applicability of the proposed inverse approach, while the IOC-based analysis provided important human-robot system properties such as stability and robustness that are difficult to obtain from human experiments. This study introduces a new tool to the field of wearable lower limb robots. It is expected to be expandable to quantify joint human-robot locomotion performance objectives for personalizing wearable robot control in the future.}, number={2}, journal={IEEE ROBOTICS AND AUTOMATION LETTERS}, author={Liu, Wentao and Zhong, Junmin and Wu, Ruofan and Fylstra, Bretta L. and Si, Jennie and Huang, He}, year={2022}, month={Apr}, pages={2549–2556} }
 @article{liu_tian_youssef_birgand_chescheir_2022, title={Patterns of long-term variations of nitrate concentration - Stream discharge relationships for a drained agricultural watershed in Mid-western USA}, volume={614}, ISSN={["1879-2707"]}, DOI={10.1016/j.jhydrol.2022.128479}, abstractNote={Nitrate Concentration–discharge (C-Q) relationships have been used to infer nitrate sources, storage, reactions, and transport in watersheds, and to reveal key processes that control runoff chemistry. Yet, studies on long-term nitrate C-Q relationships are limited due to scarce high frequency (e.g., daily) concentration data. In this paper, using a long-term high-frequency dataset (1976–2019) comprising stream flow and nitrate concentrations, we quantitatively analyzed the long-term variations of event-scale hysteresis patterns (quantified by hysteresis index, HI, and flushing index, FI) to infer the leaching mechanisms of nitrate in an artificially drained agricultural watershed in Mid-western U.S. Our results revealed that most events exhibited anti-clockwise behaviors (HI < 0), regardless of whether nitrate was flushed or diluted during events. This means that water with high levels of nitrate-N reaches the stream network slower than water with lower nitrate concentrations. Long-term mean FI was close to zero but had strong seasonal patterns with dilution patterns observed during Winter and Summer, and flushing patterns during late Spring and Fall. The consistently negative HI values regardless of the FI value gave a strong indication of the preponderant role of the near-drain zone that usually exhibits accelerated leaching and less accumulation of nitrate in the soil profile in these drained agricultural watersheds. Both HI and FI depicted strong but opposite seasonality because of weather patterns and agricultural activities, particularly N fertilization. Overall, our findings suggest a little evidence of the role of deep groundwater and instead a strong evidence of the role of subsurface drainage as the primary pathway for nitrate transport in drained agricultural watersheds. Therefore, artificial drainage could dampen N legacy caused by the historically intensive N fertilization in drained agricultural landscapes.}, journal={JOURNAL OF HYDROLOGY}, author={Liu, Wenlong and Tian, Shiying and Youssef, Mohamed A. and Birgand, Francois P. and Chescheir, George M.}, year={2022}, month={Nov} }
 @misc{liu_birgand_tian_chen_2021, title={Event-scale hysteresis metrics to reveal processes and mechanisms controlling constituent export from watersheds: A review}, volume={200}, ISSN={["1879-2448"]}, DOI={10.1016/j.watres.2021.117254}, abstractNote={Due to the increased availability of high-frequency measurements of stream chemistry provided by in situ sensors, researchers have gained more access to relationships between stream discharge and constituent concentrations (C-Q relationships) at event-scales. Existing studies reveal that event-scale C-Q relationships are mostly non-linear and exhibit temporal lags between peaks (or troughs) of hydrographs and chemographs, resulting in apparent hysteresis effects. In this paper, we summarize and introduce tools and methods in hysteresis analysis, especially the history and progresses of metrics to quantify hysteresis patterns. In addition, this paper provides a typical workflow to conduct event-scale hysteresis analysis, such as how to obtain the access to high-frequency measurements, existing methods to delineate storm events, approaches to classify and quantify hysteresis patterns, possible features/properties controlling hysteresis patterns, statistical methods to identify features at play, and strategies to deliver the inferences from hysteresis analysis. Lastly, we discuss some potential limitations that arise in the workflow and possible future work to address the challenges, including the development of advanced quantitative hysteresis metrics, generalized and standardized tools to delineate events and the integration of hysteresis analysis with numerical modeling. This paper aims to provide a critical overview of technical approaches for hysteresis analysis for researchers and hopefully foster their interests to advance our understanding of complex mechanisms in event-scale hydro-biogeochemical processes.}, journal={WATER RESEARCH}, author={Liu, Wenlong and Birgand, Francois and Tian, Shiying and Chen, Cheng}, year={2021}, month={Jul} }
 @article{liu_youssef_birgand_chescheir_tian_maxwell_2020, title={Processes and mechanisms controlling nitrate dynamics in an artificially drained field: Insights from high-frequency water quality measurements}, volume={232}, ISSN={["1873-2283"]}, DOI={10.1016/j.agwat.2020.106032}, abstractNote={Intensive agricultural activities, especially in artificially drained agricultural landscapes, generate a considerable amount of nutrient export, which has been identified as a primary cause of water quality impairment. Several management practices have been developed and installed in agricultural watersheds to reduce nutrient export, e.g. nitrate-nitrogen (NO3-N). Although published research reported considerable water quality benefits of these practices, there exist many unanswered questions regarding the inherent processes and mechanisms that control nitrate fate and transport from drained agricultural landscape. To advance our understanding of processes and mechanisms, we deployed two high-frequency sampling systems in a drained agricultural field to investigate the relationship between agricultural drainage and nitrate concentrations (C-Q relationship). Results indicated that the high-frequency measuring system was able to capture the rapidly changing C-Q relationships at the experimental site, e.g. hysteresis patterns. The 22 identified storm events exhibited anti-clockwise behavior with high variability of flushing/dilution effects. In addition, high drainage flows contributed far more nitrate loading compared with lower flows. For instance, the top 10 % of drainage flow exported more than 50 % of the nitrate lost via subsurface drainage during the monitoring period. Additionally, we observed that animal waste application was the most influential practice to change the C-Q relationship by increasing the size of soil nitrogen pools. The insights obtained from the high-frequency water quality measurements could help provide practical suggestions regarding the design and management of conservation practices, such as controlled drainage, bioreactors, and saturated buffers, to improve their nitrogen removal efficiencies. This subsequently leads to better nutrient management in drained agricultural lands.}, journal={AGRICULTURAL WATER MANAGEMENT}, author={Liu, Wenlong and Youssef, Mohamed A. and Birgand, Francois P. and Chescheir, George M. and Tian, Shiying and Maxwell, Bryan M.}, year={2020}, month={Apr} }
 @article{tang_luo_jia_liu_li_wu_2016, title={Evaluating Retention Capacity of Infiltration Rain Gardens and Their Potential Effect on Urban Stormwater Management in the Sub-Humid Loess Region of China}, volume={30}, ISSN={["1573-1650"]}, DOI={10.1007/s11269-015-1206-5}, number={3}, journal={WATER RESOURCES MANAGEMENT}, author={Tang, S. and Luo, W. and Jia, Z. and Liu, W. and Li, S. and Wu, Y.}, year={2016}, month={Feb}, pages={983–1000} }