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Molecular signatures of soil-derived dissolved organic matter constrained by mineral weathering

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Fundamental Research 2023年第3期3卷 377-383页

作者： Ying-Hui Wang Peng Zhang Chen He Jian-Chun Yu Quan Shi Randy A.Dahlgren Robert G.M.Spencer Zhi-Bing Yang Jun-Jian Wang State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control School of Environmental Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control School of Environmental Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan UniversityWuhan 430072China State Key Laboratory of Heavy Oil Processing China University of PetroleumBeijing 102249China Shanghai Engineering Research Center of Hadal Science and Technology College of Marine SciencesShanghai Ocean UniversityShanghai 201306China Department of Land Air and Water ResourcesUniversity of California DavisDavis 95616United States Department of Earth Ocean and Atmospheric ScienceFlorida State UniversityTallahassee 32306United States

Dissolved organic matter(DOM)in soils drives biogeochemical cycling and soil functions in different directions depending on its molecular ***,there is a distinct paucity of information concerning how the molecular signatures of soil DOM vary with different degrees of weathering across wide geographic ***,we resolved the DOM molecular signatures from 22 diverse Chinese reference soils and linked them with soil organic matter and weathering-related mineralogical *** mixed-effects models revealed that the yields of DOM were determined by soil organic carbon content,whereas the molecular signature of DOM was primarily constrained by the weathering-related *** soil weathering index showed a positive effect on the lability and a negative effect on the aromaticity of ***,DOM in highly weathered acidic soils featured more amino sugars,carbohydrates,and aliphatics,as well as less O-rich polyphenols and condensed aromatics,thereby conferring a higher DOM biolability and lower DOM *** study highlights the dominance of the weathering-related dimension in constraining the molecular signatures and potential functions of DOM in soils across a wide geographic scale.

关键词： Soil organic matter Dissolved organic matter Chemical composition Molecular signature Mineral weathering

Frontal gamma as a marker of effective training during neurofeedback to improve memory in patients with mild cognitive impairment

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Frontal gamma as a marker of effective training during neuro...

International IEEE/EMBS Conference on Neural engineering, CNE

作者： Yayu Lin I-Wei Shu Fiza Singh Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA Swartz Center for Computational Neuroscience Institute for Neural Computation University of California San Diego La Jolla CA USA Department of Psychiatry University of California San Diego La Jolla CA USA

Currently, more than 23 million people in the United States are affected by early Alzheimer's disease (AD), mild cognitive impairment (MCI), or subjective cognitive decline (SCD). Despite widespread awareness of the high costs to individuals and communities, treatment options for those at risk of, or with, AD is limited. To help meet this urgent need for new treatments, we identified frontal gamma activity, a neural signature of optimal memory function, as a promising treatment target. More specifically, patients with AD and MCI exhibit deficient frontal gamma activity, which we can help restore using electroencephalographic (EEG) neurofeedback (NFB). In brief, our MATLAB/EEGLAB-based brain-computer interface (BCI) converts frontal gamma coherence into re-inforcement signals, enabling patients with MCI to directly modulate frontal gamma activity. Preliminary results from our current double-blind, placebo-controlled randomized clinical trial (RCT) demonstrate that, compared to patients receiving placebo-NFB, patients receiving active-NFB (gamma-NFB, 30 min, 2/week, 12 weeks) exhibit significantly-increased frontal gamma coherence during training. Furthermore, among active gamma-NFB patients, baseline/pre-NFB gamma power at F4 (but not at other electrodes) significantly correlates with slope of training-related increases in frontal gamma coherence. These results support a model where, in patients with MCI, frontal gamma EEG-NFB specifically engages and increases frontal gamma activity. Furthermore, baseline/pre-NFB gamma power at F4 may serve as a predictor of training efficacy, a promising step towards more efficient and personalized treatment protocols for improving memory in patients with MCI or related neuropsychiatric difficulties.

关键词： Training Protocols Memory management Neural engineering Coherence Feedback amplifiers Mathematical models

Meaningful human control of partially automated driving systems: Insights from interviews with Tesla users

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Transportation Research Part F: Traffic Psychology and Behaviour 2025年 113卷 213-236页

作者： Suryana, Lucas Elbert Nordhoff, Sina Calvert, Simeon Zgonnikov, Arkady van Arem, Bart Department of Transport and Planning Faculty of Civil Engineering and Geosciences Delft University of Technology Delft Netherlands Electric Vehicle Research Center Institute of Transportation Studies University of California Davis United States Department of Cognitive Robotics Faculty of Mechanical Engineering Delft University of Technology Delft Netherlands Centre for Meaningful Human Control Delft University of Technology Delft Netherlands

Partially automated driving systems are designed to perform specific driving tasks—such as steering, accelerating, and braking—while still requiring human drivers to monitor the environment and intervene when necessary. This shift of driving responsibilities from human drivers to automated systems raises concerns about accountability, particularly in scenarios involving unexpected events. To address these concerns, the concept of meaningful human control (MHC) has been proposed. MHC emphasises the importance of humans retaining oversight and responsibility for decisions made by automated systems. Despite extensive theoretical discussion of MHC in driving automation, there is limited empirical research on how real-world partially automated systems align with MHC principles. This study offers two main contributions: (1) an empirical evaluation of MHC in partially automated driving, based on 103 semi-structured interviews with users of Tesla's Autopilot and Full Self-Driving (FSD) Beta systems;and (2) a methodological framework for assessing MHC through qualitative interview data. We operationalise the previously proposed tracking and tracing conditions of MHC using a set of evaluation criteria to determine whether these systems support meaningful human control in practice. Our findings indicate that several factors influence the degree to which MHC is achieved. Failures in tracking—where drivers' expectations regarding system safety are not adequately met—arise from technological limitations, susceptibility to environmental conditions (e.g., adverse weather or inadequate infrastructure), and discrepancies between technical performance and user satisfaction. Tracing performance—the ability to clearly assign responsibility—is affected by inconsistent adherence to safety protocols, varying levels of driver confidence, and the specific driving mode in use (e.g., Autopilot versus FSD Beta). These findings contribute to ongoing efforts to design partially automated driving

关键词： Human engineering

Quantum Vector Signal Analyzer: Wideband Electric Field Sensing via Motional Raman Transitions

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arXiv 2023年

作者： Wu, Hao Mitts, Grant D. Ho, Clayton Z.C. Rabinowitz, Joshua A. Hudson, Eric R. Department of Physics and Astronomy University of California Los Angeles Los AngelesCA United States Challenge Institute for Quantum Computation University of California Los Angeles Los AngelesCA United States Center for Quantum Science and Engineering University of California Los Angeles Los AngelesCA United States

Ultrasensitive detection of the frequency, phase, and amplitude of radio frequency (RF) electric fields is central to a variety of important applications, including radio communication, cosmology [1], dark matter searches [2], and high-fidelity qubit control [3]. Quantum harmonic oscillator systems, especially trapped ions, have been used with several quantum sensing techniques [4–7] to achieve electric field sensing with state-of-the-art sensitivity [8] and nanometer spatial resolution [9]. However, these systems are limited to a narrow frequency range centered around either the motional frequency of the trapped ion oscillator or the frequency of an optical transition in the ion;often these techniques are not sensitive to the RF phase. Here, we propose and demonstrate a procedure that unlocks the extreme sensitivity of a quantum harmonic oscillator to allow high precision wideband detection of the frequency, phase, and amplitude of an unknown electric field. Specifically, we use motional Raman transitions in a single trapped ion, cooled near its motional ground state to realize state of the art sensitivities to frequency, phase, and amplitude, and show the technique works over a frequency range that is > 800× larger than previous techniques. Further, this technique is shown to be compatible with both quantum amplification via squeezing and measurement in the Fock basis, allowing a demonstration of performance 3.4(20) dB below the standard quantum limit and the potential for several orders of magnitude improvement in sensitivity with moderate upgrades. In addition to providing an attractive platform for quantum sensing of small fields, this technique also allows in situ calibration of qubit control lines in systems using quantum harmonic oscillators, as well as transduction of external, non-resonant drives into oscillator excitation. Additionally, this approach can be extended to other quantum harmonic oscillator systems, such as a superconducting qubit-resonator sy

关键词： Trapped ions

Forecasting Slow-Wave Sleep Deficiency Through Stress-Related Markers in Forehead EEG

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Forecasting Slow-Wave Sleep Deficiency Through Stress-Relate...

IEEE International Conference on Systems, Man and Cybernetics

作者： Cheng-Hua Su Li-Wei Ko Tzyy-Ping Jung Julie Onton Shey-Cherng Tzou Jia-chi Juang Chung-Yao Hsu Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Science and Environmental Biology Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung Taiwan Institute for Neural Computation and Institute of Engineering in Medicine University of California San Diego La Jolla CA USA College of Electrical Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Institute for Neural Computation University of California San Diego La Jolla CA USA Department of Neurology Sleep Disorders Center Kaohsiung Medical University Hospital Kaohsiung Taiwan Department of Neurology College of Medicine Kaohsiung Medical University Kaohsiung Taiwan

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Sleep quality is critical for human well-being. Lack of sleep and poor sleep quality impair daily cognitive functions and health. While stress has been recognized as a detrimental factor on sleep quality, the relationship between pre-sleep stress level, resting EEG and subsequent sleep structure remains to be explored. This study presents a novel approach that evaluates pre-sleep stress levels using a 2-channel EEG to predict slow-wave sleep (SWS) deficiency. We recorded forehead EEG immediately before sleep onset, then utilized power spectra and entropy analysis to extract stress-related neurological features, including beta/delta correlation, alpha asymmetry, fuzzy entropy (FuzzEn), and spectral entropy (SpEn). We found that individuals with SWS deficiency exhibited signs of stress, such as a robust beta/delta correlation, higher alpha asymmetry, and increased FuzzEn. Conversely, individuals with ample SWS displayed weak beta/delta correlation and reduced FuzzEn in EEG recordings. Finally, we tested the robustness of the selected neuro markers with two supervised learning models and found that the selected markers predict SWS deficiency with an accuracy above 70%. Our study demonstrated that stress-related neurological markers derived from pre-sleep EEG can effectively predict SWS deficiency. The proposed method can be integrated with a portable EEG device and sleep-improving interventions to develop a personalized sleep-improvement solution.

关键词： Correlation Forehead Sleep Supervised learning Feature extraction Brain modeling Electroencephalography Entropy Forecasting Stress

Non-Euclidean Contraction Theory for Robust Nonlinear Stability

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arXiv 2021年

作者： Davydov, Alexander Jafarpour, Saber Bullo, Francesco The Department of Mechanical Engineering The Center for Control Dynamical Systems and Computation University of California Santa Barbara93106-5070 United States

We study necessary and sufficient conditions for contraction and incremental stability of dynamical systems with respect to non-Euclidean norms. First, we introduce weak pairings as a framework to study contractivity with respect to arbitrary norms, and characterize their properties. We introduce and study the sign and max pairings for the `1 and `∞ norms, respectively. Using weak pairings, we establish five equivalent characterizations for contraction, including the one-sided Lipschitz condition for the vector field as well as logarithmic norm and Demidovich conditions for the corresponding Jacobian. Third, we extend our contraction framework in two directions: we prove equivalences for contraction of continuous vector fields and we formalize the weaker notion of equilibrium contraction, which ensures exponential convergence to an equilibrium. Finally, as an application, we provide (i) incremental input-to-state stability and finite input-state gain properties for contracting systems, and (ii) a general theorem about the Lipschitz interconnection of contracting systems, whereby the Hurwitzness of a gain matrix implies the contractivity of the interconnected system. Copyright © 2021, The Authors. All rights reserved.

关键词： Dynamical systems

Non-Euclidean Monotone Operator Theory and Applications

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arXiv 2023年

作者： Davydov, Alexander Jafarpour, Saber Proskurnikov, Anton V. Bullo, Francesco Center for Control Dynamical Systems and Computation University of California Santa Barbara Santa BarbaraCA93106-5070 United States Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO80309-0020 United States Department of Electronics and Telecommunications Politecnico di Torino Turin10129 Italy

While monotone operator theory is often studied on Hilbert spaces, many interesting problems in machine learning and optimization arise naturally in finite-dimensional vector spaces endowed with non-Euclidean norms, such as diagonally-weighted 1 or ∞ norms. This paper provides a natural generalization of monotone operator theory to finite-dimensional non-Euclidean spaces. The key tools are weak pairings and logarithmic norms. We show that the resolvent and reflected resolvent operators of non-Euclidean monotone mappings exhibit similar properties to their counterparts in Hilbert spaces. Furthermore, classical iterative methods and splitting methods for finding zeros of monotone operators are shown to converge in the non-Euclidean case. We apply our theory to equilibrium computation and Lipschitz constant estimation of recurrent neural networks, obtaining novel iterations and tighter upper bounds via forward-backward splitting. © 2023, CC BY.

关键词： Recurrent neural networks

Game Theory for Autonomy: From Min-Max Optimization to Equilibrium and Bounded Rationality Learning

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Game Theory for Autonomy: From Min-Max Optimization to Equil...

American control Conference (ACC)

作者： Kyriakos G. Vamvoudakis Filippos Fotiadis João P. Hespanha Raphael Chinchilla Guosong Yang Mushuang Liu Jeff S. Shamma Lacra Pavel Daniel Guggenheim School of Aerospace Engineering Georgia Institute of Technology Atlanta GA USA Center for Control Dynamical Systems and Computation University of California Santa Barbara CA Department of Electrical and Computer Engineering Rutgers University Piscataway NJ USA Department of Mechanical and Aerospace Engineering University of Missouri Columbia MO USA Department of Industrial and Enterprise Systems Engineering University of Illinois at Urbana-Champaign IL USA Department of Electrical and Computer Engineering University of Toronto Canada

Finding Nash equilibria in non-cooperative games can be, in general, an exceptionally challenging task. This is owed to various factors, including but not limited to the cost functions of the game being nonconvex/nonconcave, the players of the game having limited information about one another, or even due to issues of computational complexity. The present tutorial draws motivation from this harsh reality and provides methods to approximate Nash or min-max equilibria in non-ideal settings using both optimization- and learning-based techniques. The tutorial acknowledges, however, that such techniques may not always converge, but instead lead to oscillations or even chaos. In that respect, tools from passivity and dissipativity theory are provided, which can offer explanations about these divergent behaviors. Finally, the tutorial highlights that, more frequently than often thought, the search for equilibrium policies is simply vain; instead, bounded rationality and non-equilibrium policies can be more realistic to employ owing to some players’ learning imperfectly or being relatively naive – "bounded rational." The efficacy of such plays is demonstrated in the context of autonomous driving systems, where it is explicitly shown that they can guarantee vehicle safety.

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NeRF in Robotics: A Survey

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arXiv 2024年

作者： Wang, Guangming Pan, Lei Peng, Songyou Liu, Shaohui Xu, Chenfeng Miao, Yanzi Zhan, Wei Tomizuka, Masayoshi Pollefeys, Marc Wang, Hesheng The University of Cambridge ETH Zurich Switzerland The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education of China China Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China ETH Zurich Zurich Switzerland Mechanical Systems Control Laboratory University of California Berkeley United States

Meticulous 3D environment representations have been a longstanding goal in computer vision and robotics fields. The recent emergence of neural implicit representations has introduced radical innovation to this field as implicit representations enable numerous capabilities. Among these, the Neural Radiance Field (NeRF) has sparked a trend because of the huge representational advantages, such as simplified mathematical models, compact environment storage, and continuous scene representations. Apart from computer vision, NeRF has also shown tremendous potential in the field of robotics. Thus, we create this survey to provide a comprehensive understanding of NeRF in the field of robotics. By exploring the advantages and limitations of NeRF, as well as its current applications and future potential, we hope to shed light on this promising area of research. Our survey is divided into two main sections: The Application of NeRF in Robotics and The Advance of NeRF in Robotics, from the perspective of how NeRF enters the field of robotics. In the first section, we introduce and analyze some works that have been or could be used in the field of robotics from the perception and interaction perspectives. In the second section, we show some works related to improving NeRF's own properties, which are essential for deploying NeRF in the field of robotics. In the discussion section of the review, we summarize the existing challenges and provide some valuable future research directions for reference. © 2024, CC BY-NC-ND.

关键词： Robotics