Time Delay Research Articles

Incorporating hydrological constraints with deep learning for streamflow prediction

Streamflow prediction is a fundamental task serving for flood prevention and efficient water resource management. Deep learning-based methods have emerged as the dominant approach and have made remarkable progress in the task. However, these methods ignore the hydrological constraints on streamflow, such as water delay time and streamflow direction, resulting in inaccurate prediction. To address this problem, this study incorporates hydrological constraints with deep learning models to improve streamflow prediction, and develops a hydrological constrained graph convolutional network (HCGCN) model. Specifically, the model designs a time-delayed spatiotemporal directed graph to present the spatiotemporal relationships and hydrological constraints, and develops a hydrological feature aggregation module to adaptively learn the complex spatiotemporal dependencies. In addition, HCGCN proposes a streamflow prediction neural network to predict streamflow by stacking the feature aggregation modules. Experimental results show that HCGCN significantly improves the prediction accuracy in a real streamflow prediction task. This study provides an exploration of introducing hydrological constraints to improve streamflow prediction, and provides a new reference for various hydrological prediction tasks.

Enhanced anti-icing performance of novel superhydrophobic F-L@KH-SiO2/OTMS coating synergistic preparation with bionic micro-nano structures and modified nanoparticles

Surface icing significantly impacts equipment operation and safety in low-temperature environments. Passive de-icing technologies using superhydrophobic materials are gaining attention for their environmental and cost benefits. This study presents a novel superhydrophobic F-L@KH-SiO2/OTMS coating, fabricated through femtosecond laser etching of aluminum alloy to create bionic micro-nano lattice structures. Subsequently, a hydrophobic epoxy coating was sprayed as an adhesive layer, followed by chemical modification of the ablated aluminum alloy surface using 3-(trimethoxysilyl) propyl methacrylate (KH570) modified silicon dioxide (SiO2) nanoparticles, γ-aminopropyltriethoxysilane (KH550), and octadecyltrimethoxysilane (OTMS) as hydrophobizing agents. The resulting coating exhibits excellent superhydrophobic properties, with a contact angle (CA) of 165.92° and a sliding angle (SA) of only 1.25°. The coating demonstrated superior anti-adhesion and bouncing capabilities, effectively preventing droplet freezing and ice formation, which is attributed to the synergistic effect of the modified silica and the cross-linked lattice structure. Compared to other reported superhydrophobic surfaces, this coating showed a longer freezing delay time of 730 s at −20 °C. These findings highlight the potential of the F-L@KH-SiO2/OTMS coating for efficient anti-icing, de-icing, and defrosting applications.

Multi-messenger signatures of delayed choked jets in tidal disruption events

Abstract Recent radio observations and coincident neutrino detections suggest that some tidal disruption events (TDEs) exhibit late-time activities, relative to the optical ehmission peak, and these may be due to delayed outflows launched from the central supermassive black hole. We investigate te possibility that jets launched with a time delay of days to months, interact with a debris that may expand outwards. We discuss the effects of the time delay and expansion velocity on the outcomes of jet breakout and collimation. We find that a jet with an isotropic-equivalent luminosity of ≲ 5 × 1045 erg/s is likely to be choked for a delay time of ∼3 months. We also study the observational signatures of such delayed choked jets. The jet-debris interaction preceding the breakout would lead to particle acceleration and the resulting synchrotron emission can be detected by current and near-future radio, optical and X-ray telescopes, and the expanding jet-driven debris could explain late-time radio emission. We discuss high-energy neutrino production in delayed choked jets, and the time delay can significantly alleviate the difficulty of the hidden jet scenario in explaining neutrino coincidences.

Vector magnetic field measurement based on fiber ring microwave photonic filter with the Vernier effect

A vector magnetic field sensor based on enhanced Vernier effect is experimentally demonstrated. The Vernier effect is generated from two microwave photonic filters (MPFs) with close free spectral range (FSR), which is constructed by the fiber ring (FR) and the optical carrier microwave interferometry (OCMI). Linear chirped fiber Bragg grating (LCFBG) is inserted in the FR to act as the dispersion element to provide time delay. By attaching the fiber Bragg grating (FBG) on the magnetostrictive material (MA), the magnetic field can be transferred into the wavelength shift, as well as the time delay of the FR and the frequency response of the FR-MPF. By choosing opposite dispersion of LCFBGs and closer FSRs, cascaded FR-MPFs based sensor can greatly improve the sensitivity. The sensitivities for the magnetic field intensity and direction are 127.71 kHz/Oe, the magnification factor of which is 432, and 418.16 kHz/deg. The proposed scheme has merits of high sensitivity and interference immunity, which is suitable for high precision measurement.

Radial velocity estimation method for a single hydrophone based on passive target line spectrum characteristics

Passive radial velocity estimation based on a single hydrophone has a wide range of applications in engineering, and can be used in small underwater platforms such as submerged buoys and underwater gliders. The conventional passive radial velocity estimation method based on a single hydrophone has poor performance due to the influence of noise. In this paper, the time delay coherence coefficient (TDCC) of passive target line spectrum is derived based on a single hydrophone. Further, the radial velocity can be obtained by the time delay required by the phase change of TDCC for one period. Based on the characteristics that the line spectrum phase is stable and the noise phase is random, coherent averaging (CA) is applied to suppress noise. The use of CA greatly reduces the influence of noise on TDCC and efficiently improves the accuracy of radial velocity estimation. The performance and system error of the proposed CA-TDCC method are analyzed through a series of simulations. Finally, the CA-TDCC method is used to process SwellEx-96 data, and the relative error of radial velocity estimation is less than 10%, which verifies the effectiveness of this method in practical applications.Abbreviation: CA, Coherent averaging; SNRs, Signal-to-noise ratios; TDCC, Time delay coherence coefficient; TMA, Target motion analysis.

Simplified Finite Control Set Model Predictive Control for single-phase grid-tied inverters with twisted parameters

Large computational burden, time delay, and the necessity for precise modeling accuracy are the three main challenges for Finite Control Set-Model Predictive Control (FCS-MPC) in single-phase grid-tied inverters. To solve these issues, a twisted parameter scheme is proposed for the single-phase inverter in this article. Firstly, the law regarding the influence of the model parameter on the current total harmonic distortion (THD) is outlined, emphasizing that a decrease in the inductance parameter leads to a corresponding reduction in current THD. Second, a linear observer is constructed to identify the actual value of inductance and resistance, and an RBF-GA (Radial Basis Function neural network-Genetic Algorithm) scheme is used to obtain the optimal twisted parameter. Subsequently, the efficacy of the proposed methods was verified utilizing MATLAB/Simulink simulations, with further validation conducted through hardware-in-the-loop (HIL) experiments performed on Speedgoat performance real-time target machines. Simulation and experimental results demonstrate that within a specific range, decreasing the inductance parameter can significantly improve the quality of the current. Furthermore, the proposed method outperforms the traditional delay compensation method by reducing computational complexity, minimizing prediction error, and decreasing the number of switching transitions.

Effect of lubricant loading in slippery liquid-infused surface for persistent anti-icing performance

Due to the vast applications in biomedical materials and aerospace industry, smart slippery liquid-infused porous surfaces (SLIPSs) have attracted remarkable attention. However, there are still challenges in the fabrication of durable SLIPS. In this work, based on linear polyurea and silicone oil, a series of durable anti-icing surface were fabricated. Based on the long-lasting secretion of lubricant, the ice adhesion strength of 60-PUa was 2.7 ± 0.5 kPa and could remain below 10 kPa even after 30 icing-deicing cycles. And the icing delay time of 60-PUa could be extended up to 870 s at a temperature of −15 °C. The introduction of large numbers of reversible hydrogen bonds in the system and silicone oil made it possible to achieve high self-healing efficiency under natural conditions. The coating system not only improved the ice removal ability, but also had excellent water-sliding properties, the droplet could slide under its own weight on 60-PUa at a tilt angle of 4.7°. This work provides an easy way to fabricate multi-functional SLIPS with durability.

Frequency chimera state induced by time delays in FitzHugh-Nagumo neural networks

The delay of information transmission is an inherent factor of the nervous systems, which has great influences on their collective dynamic behaviors. In this paper, we constructed a ring neural network using FitzHugh-Nagumo (FHN) neuron model as the network node and memristive synapses as the connection mode. Our primary focus was on investigating the effects of time delay and coupling strength on the firing frequency of neurons. Simulation results revealed that the frequency chimera state could be induced in the neural network with appropriate time delay, which is a new type of chimera state characterized by firing frequency rather than traditional membrane potential. By adjusting the time delay properly, the neural network can also display multi-cluster frequency chimera states that coexisted with various incoherent regions and coherent regions. Meanwhile, we exhibit that initial value and coupling strength could have great influences on the effects of time delay on inducing frequency chimera state of the nervous systems.

Pathological complete response of locally advanced triple-negative breast cancer: case report

Background. Triple-negative breast cancer is the most aggressive molecular subtype among breast malignancies. Due to the high proliferative activity of tumor cells and the lack of targets for targeted therapy, neoadjuvant chemotherapy plays the main role in complex treatment of this subtype. The optimal time to start neoadjuvant chemotherapy is defined as less than 8 weeks. Delays in time to treatment initiation may adversely affect treatment outcomes, as well as cause local or systemic disease progression. Achieving complete pathological response after neoadjuvant chemotherapy reduces the relative risk of relapse by more than 70 %, which, in turn, leads to a significant improvement in long-term survival of these patients. Description of the clinical case. A 32-year-old woman came to the clinic 15 months after being diagnosed with triple-negative breast cancer. The patient was treated with alternative medicine methods for 15 months, and upon admission to the hospital, the patient had pronounced local tumor growth with massive decay, tumor lysis syndrome and nutritional disorders. We decided to perform neoadjuvant chemotherapy: 12 cycles of weekly paclitaxel + carboplatin, followed by 4 cycles of dose-dense doxorubicin + cyclophosphamide. Chemotherapy resulted in a significant reduction in tumor size and improvement of health status of the patient. There were no clinically significant side effects requiring hospitalization or dose reduction. Upon completion of neoadjuvant treatment, the patient underwent mastectomy. The histological examination revealed a complete pathological response of the primary tumor and regional lymph nodes. The patient underwent adjuvant external beam radiation therapy. The patient is alive 3 years after diagnosis and 1.5 years after treatment completion. She plans delayed breast reconstruction with contralateral breast augmentation. Conclusion. This is a rare case of locally advanced triple-negative breast cancer with pathological complete response to neoadjuvant chemotherapy 15 months after diagnosis.

Model-Mediated Teleoperation: An Operator-Centric Perspective

Abstract Haptic teleoperation is a means of dexterously manipulating environments wherein a human operator can be situated several hundreds of kilometers away from the site of manipulation. Time delays between the local and remote sites pose problems for the user experience. Model-mediated teleoperation addresses these problems, but assumes a sufficiently representative model of the operator and of the environment. When applied to complex environments, this model becomes difficult to work with. A solution to this difficulty lies in the fact that human perceptual capabilities are limited. So too, possibly, is the amount of feedback needed in order to accomplish tasks effectively. In this work, we review information on human perception of the environmental properties involved in environmental perception (inertia, friction, roughness, compliance, and geometry). Moreover, we detail how these properties can be modeled. Finally, we propose some open questions that are relevant in understanding the link between the environment presented to the operator and their effectiveness at accomplishing tasks.

Spin effect induced momentum spiral and asymmetry degree in pair production

Spin effect on the pair production under circularly polarized fields is investigated. Significantly different from what momentum spirals caused by two counterrotating fields with a time delay, we find for the first time that the spirals can also be induced due to the particle spin effect even if in a single field. We further examine the bichromatic combinational fields. The inhomogeneous spiral structures can be observed in the momentum spectrum; in particular, the spiral not only does exist in two cases of spin, but also is about 2 orders of magnitude amplified compared with that in the single field. Meanwhile, the spin asymmetry degree on the momentum distributions is investigated, and it was found that the effect of spin flip exists with an increased time delay between two fields. The spin asymmetry degree on the number density can reach to 98% in certain conditions. These results indicate that the signatures of created particles, especially the spiral structures, are strongly associated with information pertaining to the laser field as well as the created particle spin, which can deepen the understanding of vacuum pair production. Published by the American Physical Society 2024

Controlled mechanochemical coupling of anti-junctions in DNA origami arrays

Allostery is a hallmark of cellular function and important in every biological system. Still, we are only starting to mimic it in the laboratory. Here, we introduce an approach to study aspects of allostery in artificial systems. We use a DNA origami domino array structure which–upon binding of trigger DNA strands–undergoes a stepwise allosteric conformational change. Using two FRET probes placed at specific positions in the DNA origami, we zoom in into single steps of this reaction cascade. Most of the steps are strongly coupled temporally and occur simultaneously. Introduction of activation energy barriers between different intermediate states alters this coupling and induces a time delay. We then apply these approaches to release a cargo DNA strand at a predefined step in the reaction cascade to demonstrate the applicability of this concept in tunable cascades of mechanochemical coupling with both spatial and temporal control.

Effects of hydrogen addition on ignition characteristics and engine performance of ammonia-hydrogen blended fuel: A kinetic analysis

To investigate the effects of hydrogen addition on the ignition characteristics and engine performance of ammonia-hydrogen fuel, a reaction kinetics mechanism suitable for high-pressure engine conditions was proposed. The study explores the influence of hydrogen blending ratios on the ignition delay time (IDT) of ammonia-hydrogen fuel, revealing the sensitive reactions and evolution characteristics of reaction pathways during the ignition process of ammonia-hydrogen fuel promoted by hydrogen. The study also investigates the impact of hydrogen blending ratios on the engine performance of ammonia-hydrogen fuel. The results show that the IDT of ammonia significantly decreases with increasing hydrogen blending ratios and temperature. The addition of hydrogen to ammonia significantly lowers the autoignition temperature boundary of the mixture. Under low-temperature and low-pressure conditions, ammonia, which would not ignite originally, ignites due to the addition of hydrogen. The addition of hydrogen shifts the sensitive reactions of the mixture from NH3 and NH2-related reactions to H2/O2-related reactions, without altering the reaction pathway of ammonia, only changing the pathway flux of components such as NH2, H2NN, H2NO, and HONO. In a spark-ignition (SI) engine, maintaining the total fuel heat value and ignition timing constant, an increase in hydrogen blending ratio significantly raises the peak cylinder pressure. However, due to the forward movement of the heat release process, the power performance of engine experiences varying degrees of reduction. Therefore, it is necessary to delay the ignition timing of engine with the increase in hydrogen blending ratio, moving the combustion center beyond the top dead center (TDC). Furthermore, increasing the hydrogen concentration in the blend significantly raises the temperature and pressure during the engine combustion process, leading to an increase in the concentration of thermal NOX in the emissions.

Advancing Programmable Information Encryption Circuits Through Colorful Phosphorescent Carbon Nanodots with Versatile Lifetimes

AbstractOptical encryption technology attracts considerable attention in the field of information encryption, information storage, and anti‐counterfeiting. However, optical encryption based on conventional on/off mode still faces issues such as low scalability, ease of cracking, and poor storage capacity; multi‐dimensional and high storage capacity information encryption systems are thus needed. Herein, a programmable information encryption circuit system is demonstrated by constructing a delay light‐emitting diode (LED) array using multi‐color phosphorescent carbon nanodots (CNDs) with versatile lifetimes. The CNDs show adjustable luminescence wavelength and lifetime from 192 to 1148 ms. The programmable delay luminescent circuit provides an intricate framework for meticulously integrating an LED array, enabling the creation of intricate patterns or alphanumeric codes. These intricate designs are engineered to serve as a component of an encryption system, which can be deciphered and unveiled under a specific delay time range. This study demonstrates the feasibility and superiority of the system as a new type of information anti‐counterfeiting encryption technology, providing a new concept for exploring the field of integrated circuit anti‐counterfeiting and encryption.

Dynamic analysis and optimal control of a mosquito-borne infectious disease model under the influence of biodiversity dilution effect

In this paper, biodiversity and a saturation treatment rate are introduced into a type of mosquito-borne infectious disease model with an incubation time delay. Through the dynamical analysis of the model, conditions for the existence and stability of disease-free and endemic equilibria are determined. The basic reproduction number of the model is calculated, and the condition for the existence of backward bifurcation is outlined. The study finds that under the dual influence of biodiversity and saturation treatment, the threshold characteristic of the basic reproduction number becomes invalidated. When R0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$R_{0}$\\end{document} is less than 1, the model may exhibit four equilibrium states, with both the disease-free equilibrium and the endemic equilibrium being locally stable. In this scenario, whether the virus will become extinct depends on the initial conditions. The study also finds that when the basic reproduction number R0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$R_{0}$\\end{document} is greater than 1, the stability of the model is influenced by the time delay, with Hopf bifurcation occurring at a specific time delay. In addition, another novel contribution of this paper is the formulation of an optimal control problem that takes into account the minimization of damage caused by humans to biodiversity. Based on the Pontryagin’s maximum principle, the specific characteristics of the optimal control measures are given, and the optimal strategy is derived by comparing five groups of control strategies. The optimal control results highlight the synergistic effect of multiple control measures with biodiversity. Under optimal control, a significant complementary effect between medical inputs and the dilution effect of biodiversity is evident. The findings imply that maintaining high biodiversity levels can decrease the demand for medical resources in mosquito-borne disease control efforts.

Continuous Coherent Quantum Feedback with Time Delays: Tensor Network Solution

In this paper, we develop a novel method to solve problems involving quantum optical systems coupled to coherent quantum feedback loops featuring time delays. Our method is based on exact mappings of such non-Markovian problems to equivalent Markovian driven dissipative quantum many-body problems. In this work, we show that the resulting Markovian quantum many-body problems can be solved (numerically) exactly and efficiently using tensor network methods for a series of paradigmatic examples, consisting of driven quantum systems coupled to waveguides at several distant points. In particular, we show that our method allows solving problems in so far inaccessible regimes, including problems with arbitrary long time delays and arbitrary numbers of excitations in the delay lines. We obtain solutions for the full real-time dynamics as well as the steady state in all these regimes. Finally, motivated by our results, we develop a novel mean-field approach, which allows us to find the solution semianalytically, and we identify parameter regimes where this approximation is in excellent agreement with our tensor network results. Published by the American Physical Society 2024

Fractional-Order Modeling and Identification for an SCR Denitrification Process

This paper presents an application of a fractional-order system on modeling an industrial process system with large inertia and time delay. The traditional integer-order model of the process system is extended to a fractional-order one in this work. To identify the parameters of the proposed fractional-order model, an output-error identification algorithm is presented. Based on the experimental step response data of the selective catalytic reduction (SCR) denitrification process in a power plant, this proposed fractional-order model shows a better fitting result compared with the typical integer-order models. An integer-order proportional–integral (PI) controller is designed for the process plant using a simple scheme according to the identified fractional-order and integer-order models, respectively. Validation tests are performed based on the obtained fractional-order and integer-order models, demonstrating the advantages of the proposed fractional-order model with the corresponding system identification approach for industrial processes with large inertia and time delay.

Biquaternion ambiguity function and associated uncertainty principles

A mathematical tool used to analyze signals in high-dimensional areas is the biquaternion ambiguity function. While typical ambiguity functions deal with time delay and Doppler frequency, biquaternion ambiguity functions extend the concept to rotations and scaling factors. Biquaternion ambiguity functions offer a more thorough representation of signal ambiguity in these high-dimensional spaces, which can help develop better signal processing algorithms for a range of uses. In this paper, we introduce the notion of biquaternion ambiguity function which is formed from conventional ambiguity function by invoking biquaternion algebra. We first establish the various properties, namely dilation, translation, shift, nonlinearity, boundedness, reconstruction formula, Moyal’s formula, and inversion formula. An interesting relationship between the biquaternion Fourier transform and the biquaternion ambiguity function is also established. Furthermore, we establish the various versions of uncertainty inequalities namely, Pitt’s inequality, sharp Hausdorff–Young inequality, sharp Local uncertainty principle and logarithmic uncertainty principle for biquaternion ambiguity function. Some potential applications are also presented at the end.

A targeted search for strongly lensed supernovae with the Las Cumbres Observatory

Abstract Gravitationally lensed supernovae (glSNe) are of interest for time delay cosmology and SN physics. However, glSNe detections are rare, owing to the intrinsic rarity of SN explosions, the necessity of alignment with a foreground lens, and the relatively short window of detectability. We present the Las Cumbres Observatory Lensed Supernova Search, LCOLSS, a targeted survey designed for detecting glSNe in known strong lensing systems. Using cadenced r′-band imaging, LCOLSS targeted 114 galaxy-galaxy lensing systems with high expected SN rates, based on estimated star formation rates. No plausible glSN was detected by LCOLSS during our two year observing program. We carry out an analysis here to measure a detection efficiency for these observations. We then perform Monte Carlo simulations using the predicted supernova rates to determine the expected number of glSN detections. The results of the simulation suggest an expected number of detections and $68\%$ Poisson confidence intervals, NSN = 0.20, [0, 2.1], NIa = 0.08, [0, 2.0], NCC = 0.12, [0, 2.0], for all SNe, Type Ia SNe, and core-collapse (CC) SNe respectively. These results are broadly consistent with the absence of a detection in our survey. Analysis of the survey strategy can provide insights for future efforts to develop targeted glSN discovery programs, especially considering the large anticipated yields of upcoming surveys.

Synchronization Control of Complex Spatio-Temporal Networks Based on Fractional-Order Hyperbolic PDEs with Delayed Coupling and Space-Varying Coefficients

This paper studies synchronization behaviors of two sorts of non-linear fractional-order complex spatio-temporal networks modeled by hyperbolic space-varying PDEs (FCSNHSPDEs), respectively, with time-invariant delays and time-varying delays, including one delayed coupling. One distributed controller with space-varying control gains is firstly designed. For time-invariant delayed cases, sufficient conditions for synchronization of FCSNHSPDEs are presented via LMIs, which have no relation to time delays. For time-varying delayed cases, synchronization conditions of FCSNHSPDEs are presented via spatial algebraic LMIs (SALMIs), which are related to time delay varying speeds. Finally, two examples show the validity of the control approaches.