Channel Disturbances Research Articles

The longer arc of channel recovery post-dam removal

Dam removals are opportunistic experiments to address fundamental questions about river recovery to disturbance. Previous studies have shown that gravel-bedded rivers are resilient with covariate adjustments to channel dimensions occurring rapidly in the wake of disturbance. Yet, beyond the cross section, at the reach or watershed-scale, adjustment appears to take much longer. Understanding of the longer arc of reach and watershed recovery is limited by the relatively few dam removals studies that include long-term monitoring. Here, we present results from a five-year dam removal study punctuated by an extreme flood and show that the initial, rapid response of a channel is driven by the prevailing hydrology whereas longer-term adjustments to morphology at the reach scale are driven by external forces imposed on the channel. We summarize these results by classifying various channel features as either ‘intrinsic channel properties’ that are rapidly adjustable by the prevailing hydrology or ‘extrinsic channel properties’ that respond over various time scales to external boundary conditions imposed on the channel by climate, vegetation, geology, and valley dimensions (extrinsic controls). We show that this framework applies to channel recovery beyond the former reservoir and thus may prove applicable to channel disturbances beyond dam removal, such as extreme floods.

Inferring on fluvial resilience from multi-temporal high-resolution topography and geomorphic unit diversity

The resilience of a river corridor represents its ability to withstand and recover from disturbances. Quantifying fluvial resilience in the face of various stressors is essential for integrating ecology and geomorphology in a context of river management. Geomorphic unit diversity analysis emerges as a valuable tool for characterizing and quantifying fluvial resilience to disturbances due to its inherent connection with fluvial dynamics. This paper aims to analyse and quantify the fluvial resilience of a wandering gravel-bed river affected by natural (e.g., floods) and human-induced (e.g., instream gravel mining) stressors. To achieve this goal, we use multi-temporal high-resolution topographic surveys of the Upper River Cinca (South-Central Pyrenees) spanning from 2014 to 2020. By employing the Geomorphic Unit Tool (GUT) on these surveys, we can map geomorphic units over time, quantify their diversity, and study geomorphic adjustments through morphodynamic signatures, altogether allowing inferring fluvial resilience.Our findings reveal that topographic changes (i.e., erosion and sedimentation) correlate with the type of stressor: maintenance works and gravel mining lead to degradation, while floods induce aggradation. Geomorphic Unit Diversity decreases following channel disturbances caused by gravel mining but rebounds after periods primarily stressed by floods, returning to pre-impact levels within six years. Geomorphic adjustments, such as channel incision and mid bar development, reflect erosion and sedimentation processes respectively, with channel maintenance works and floods being the main drivers. Despite the recovery of the geomorphic unit diversity within the reach, the deficit resulting from gravel extraction remains unresolved, perpetuating a degrading trend that poses risks in reducing lateral connectivity and could potentially catalyse future vegetation encroachment in bars and floodplains, causing changes on flood conveyance and hydraulics. Monitoring the river's geomorphic diversity provides crucial insights for effective conservation and management decisions regarding land use, development, and conservation along riverbanks, thereby sustaining or enhancing fluvial system resilience.

Adaptive Control for a Two-Axis Semi-Strapdown Stabilized Platform Based on Disturbance Transformation and LWOA-PID.

A two-axis semi-strapdown stabilized platform is a device designed to eliminate aircraft disturbances and ensure the stability of the sensor's orientation. A traditional two-axis semi-strapdown stabilization platform for aircraft can effectively control disturbance in pitch and yaw channel, but it cannot achieve ideal disturbance control in the roll channel. In order to solve this problem, an adaptive control method based on disturbance transformation and LWOA-PID is proposed. Disturbance transformation is the process of integrating the angular position disturbance of the roll from the previous moment into the combined disturbance of the pitch and yaw at the current moment. This is followed by decoupling the combined disturbance of the pitch and yaw at the current moment, thereby eliminating the disturbance caused by the roll from the previous moment. This process is repeated to achieve the goal of eliminating roll channel disturbances. To ensure the line of sight (LOS) pointing accuracy stability in the two-axis semi-strapdown stabilized platform system for aircraft, a whale optimization adaptive proportional-integral-derivative (LWOA-PID) controller based on Latin hypercube sampling is designed. It is then compared with the classical PID controller in Matlab/Simulink. The simulation results indicate that the disturbance conversion module proposed in this paper can eliminate the impact of roll axis disturbances on the LOS pointing accuracy of the two-axis semi-strapdown stabilized platform for aircraft. Compared to the classical PID controller, the LWOA-PID controller reduces tracking errors for step and sinusoidal signals by 50% and 75%, respectively. It also shortens optimization time by 37.5% compared to the WOA-PID while maintaining the same level of accuracy. Furthermore, when combined with the conversion module, the tracking error is reduced by an additional order of magnitude.

Exploring the Link Between Ativyayama (Overexercise) and Srotodusti, with Emphasis on Pranavaha Srotas: A Comprehensive Scientific Analysis

Vyayama, a specialized concept in Ayurveda, serves as both the cause and remedy for various illnesses. While physical exercise is beneficial, excessive engagement in it can lead to negative health outcomes. Over-exertion aggravates the Vata Dosha, which in turn affects the qualities of the channels (Srotas), making them Ruksha and Khara. Consequently, Vyayama becomes a primary factor in the disturbance of the channels Pranavaha, Asthivaha, and Swedavaha Srotas. Conversely, insufficient exercise disrupts the Medovaha Srotas. The Pranavaha Srotas serves as the vital channel responsible for carrying Vata, especially Prana, which sustains the vitality of every cell. Disruption in the structure or function of this channel leads to illness. When exercise is excessive, it can lead to Hridayoparodha resulting in impairment of the primary site of action. This can manifest as acute conditions (as myocardial infarction) or chronic conditions (as Shosha). It's important to engage in exercise appropriately according to Bala and Ritu to preserve health. This article explores the scientific evidence supporting the notion that excessive exercise (Ativyayama) can disturb the balance of the body's channels, particularly the Pranavaha Srotas. It offers a thorough examination of the relationship between overexercise and channel disturbances, providing insights into potential risks and preventive measures.

The effect of obstacle length and height in subcritical free-surface flow

Two-dimensional free-surface flow past a submerged rectangular disturbance in an open channel is considered. The forced Korteweg–de Vries model of Binder et al. (Theor Comput Fluid Dyn 20:125–144, 2006) is modified to examine the effect of varying obstacle length and height on the response of the free-surface. For a given obstacle height and flow rate in the subcritical flow regime an analysis of the steady solutions in the phase plane of the problem determines a countably infinite set of discrete obstacle lengths for which there are no waves downstream of the obstacle. A rich structure of nonlinear behaviour is also found as the height of the obstacle approaches critical values in the steady problem. The stability of the steady solutions is investigated numerically in the time-dependent problem with a pseudospectral method.

The Stable Gastric Pentadecapeptide BPC 157 Pleiotropic Beneficial Activity and Its Possible Relations with Neurotransmitter Activity.

We highlight the particular aspects of the stable gastric pentadecapeptide BPC 157 pleiotropic beneficial activity (not destroyed in human gastric juice, native and stable in human gastric juice, as a cytoprotection mediator holds a response specifically related to preventing or recovering damage as such) and its possible relations with neurotransmitter activity. We attempt to resolve the shortage of the pleiotropic beneficial effects of BPC 157, given the general standard neurotransmitter criteria, in classic terms. We substitute the lack of direct conclusive evidence (i.e., production within the neuron or present in it as a precursor molecule, released eliciting a response on the receptor on the target cells on neurons and being removed from the site of action once its signaling role is complete). This can be a network of interconnected evidence, previously envisaged in the implementation of the cytoprotection effects, consistent beneficial particular evidence that BPC 157 therapy counteracts dopamine, serotonin, glutamate, GABA, adrenalin/noradrenalin, acetylcholine, and NO-system disturbances. This specifically includes counteraction of those disturbances related to their receptors, both blockade and over-activity, destruction, depletion, tolerance, sensitization, and channel disturbances counteraction. Likewise, BPC 157 activates particular receptors (i.e., VGEF and growth hormone). Furthermore, close BPC 157/NO-system relations with the gasotransmitters crossing the cell membrane and acting directly on molecules inside the cell may envisage particular interactions with receptors on the plasma membrane of their target cells. Finally, there is nerve-muscle relation in various muscle disturbance counteractions, and nerve-nerve relation in various encephalopathies counteraction, which is also exemplified specifically by the BPC 157 therapy application.

Spatial and Temporal Characteristics of Channel Disturbance Zones in Big River, Southeast Missouri (1937–2018)

abstract: Ozarks watersheds have responded to land clearing and settlement disturbances by transporting large amounts of gravel and sediment to main valleys of medium-large river systems. Historical gravel and sediment accumulate in disturbance zones, which are areas of excessive channel activity that can be detected over time using historical aerial photographs. This project uses a series of aerial photos from 1937–2018 to identify disturbance zones in the Big River of southeast Missouri, which has a history of lead mining and ore processing that has caused widespread contamination of the channel and floodplain deposits. Variations in active areas of the historical meander belt show that disturbance zones account for 24 percent of the channel length at an interval of one per 2.5 km of channel. Megabars and extensions are the most prominent types of disturbance zones, but translations and cutoffs are larger with higher potential for sediment storage. From 1937 to 1976, areas of channel activity have cycled between expansion and contraction. However, after a period of recovery prior to 1976, disturbance zone areas have been expanding over the last 40 years likely in response to an increase in flood magnitude and frequency from more high intensity rainfall events since 1973.

Refined sliding mode disturbance observer‐based finite‐time composite control for Euler–Lagrange systems with multiple disturbances

AbstractA wide range of practical control systems such as robot manipulators and spacecrafts can be modeled by Euler–Lagrange systems. On one hand, the requirements for system control accuracy, response speed, and robustness are ever increasing. On the other hand, the control performances are inevitably degraded by multiple disturbances. In this paper, a novel finite‐time composite control law is proposed for a class of Euler–Lagrange systems subject to multiple heterogeneous disturbances including a neutrally stable disturbance and a norm‐bounded disturbance. More specifically, a refined sliding mode disturbance observer (RSMDO) is proposed to estimate and reject the neutrally stable disturbance in the feedforward channel, while an adaptive nonsingular backstepping control (ANBC) is designed in the feedback channel to stabilize the system and attenuate the observer error as well as the norm‐bounded disturbance. The proposed RSMDO can not only fully utilize the disturbance information, but also quantify the convergence time and steady‐state accuracy of the estimation error. The finite‐time stability analysis is carried out for the closed‐loop system. Finally, an example of spacecraft attitude control system is given to demonstrate the effectiveness of the proposed methods.

Variable Gain Impulsive Synchronization for Discrete-Time Delayed Neural Networks and Its Application in Digital Secure Communication.

This article revisits the problems of impulsive stabilization and impulsive synchronization of discrete-time delayed neural networks (DDNNs) in the presence of disturbance in the input channel. A new Lyapunov approach based on double Lyapunov functionals is introduced for analyzing exponential input-to-state stability (EISS) of discrete impulsive delayed systems. In the framework of double Lyapunov functionals, a pair of timer-dependent Lyapunov functionals are constructed for impulsive DDNNs. The pair of Lyapunov functionals can introduce more degrees of freedom that not only can be exploited to reduce the conservatism of the previous methods, but also make it possible to design variable gain impulsive controllers. New design criteria for impulsive stabilization and impulsive synchronization are derived in terms of linear matrix inequalities. Numerical results show that compared with the constant gain design technique, the proposed variable gain design technique can accept larger impulse intervals and equip the impulsive controllers with a stronger disturbance attenuation ability. Applications to digital signal encryption and image encryption are provided which validate the effectiveness of the theoretical results.

Evaluating the performance of instream structures for a stream restoration project in Colorado

AbstractMetals pollution and channel disturbance associated with historical mining, land use, and water development degraded aquatic and riparian habitat along the upper Arkansas River near Leadville, Colorado. Stream restoration was conducted for an 8 km reach to improve aquatic habitat and increase trout populations. Instream structures were prescribed to stabilize streambanks, create diverse stream morphology, and provide overhead cover, refuge, spawning, and overwinter habitat for trout. At least 90% of all structures were expected to be stable and functional 3 years after implementation. The objectives of this study were to investigate structure performance by (1) evaluating the integrity and function of instream structures and (2) evaluating the change in residual pool depths (RPD). Annual surveys utilized a rapid assessment procedure to qualitatively rank integrity, erosion, and deposition at each structure (n = 137). Rankings were investigated with ordinal regression to determine if performance varied by structure type and year. Longitudinal profile surveys were conducted annually and used to estimate RPD for 86 pools. The change in RPD was investigated with repeated measures ANOVA to determine if RPD varied between structure types and changed over time. Results suggest that some structures were more prone to failure, with higher rankings observed for boulder toe, log vanes, log toe, and boulder vanes. Pool depths increased during construction, decreased following the first runoff, and then remained relatively stable in subsequent years. Understanding the performance of instream structures from this case study will help inform the design, evaluation, and expectations for future stream restoration projects.

Spatio-temporal mapping and long-term evolution of debris flow activity after a high magnitude earthquake

A high-magnitude earthquake can trigger substantial amounts of co-seismic debris and unstable hillslopes in mountainous regions, which leads to a significant increase in the frequency and magnitude of post-earthquake debris flows. The long-term impacts of earthquakes on the debris flow activity have not been fully understood, primarily because of a lack of multi-temporal mapping inventories of debris flow activity. Therefore, it is crucial to analyze the spatio-temporal evolution of debris flow activities and their driving factors after the 2008 Wenchuan earthquake for disaster risk management and mitigation from a dynamic perspective. We used the fusion of remote sensing data to develop the first systematic multi-temporal inventory of debris flow activity to quantify changes in spatial and temporal activity of post-earthquake debris flows from 2008 to 2021. Subsequently, we examined the control of material sources, topographic and hydrological factors on the evolution of post-earthquake debris flow activities. A close relationship between the decline in debris flow activity and the reduced active material sources was observed in both time and space, so the supply capacity of hillslope deposits after the earthquake was the first-order indicator controlling post-earthquake debris flow activity. With the progressive depletion and stabilization of co-seismic landslide materials over time, topographic and hydrological factors occupied a dominant role in the occurrence of debris flow. In general, an oscillatory decay pattern of debris flow activity over time was observed after the 2008 Wenchuan earthquake. We observed that the period of post-earthquake debris flow activity varied considerably in different regions attributed to the magnitude of the earthquake, and the geological and climatic environments. Based on the debris flow channel disturbances, the dynamic evolution of landslide materials and hydrodynamics, we divided the debris flow active period after the Wenchuan earthquake into three phases: high activity period (lasting 2 ∼ 5 years), medium activity period (lasting 3 ∼ 10 years), and low activity period (lasting 9 ∼ 18 years). Following the above three activity periods, the debris flow activity will evolve into a steady period. We also proposed a quantitative model for debris flow activeness in the main Wenchuan earthquake-affected area, which predicts that the activeness of debris flows will tend to pre-earthquake levels in 46 years following the earthquake.

Ion Channel Disturbances in Migraine Headache: Exploring the Potential Role of the Kynurenine System in the Context of the Trigeminovascular System

Migraine is a primary headache disorder, which is an enormous burden to the healthcare system. While some aspects of the pathomechanism of migraines remain unknown, the most accepted theory is that activation and sensitization of the trigeminovascular system are essential during migraine attacks. In recent decades, it has been suggested that ion channels may be important participants in the pathogenesis of migraine. Numerous ion channels are expressed in the peripheral and central nervous systems, including the trigeminovascular system, affecting neuron excitability, synaptic energy homeostasis, inflammatory signaling, and pain sensation. Dysfunction of ion channels could result in neuronal excitability and peripheral or central sensitization. This narrative review covers the current understanding of the biological mechanisms leading to activation and sensitization of the trigeminovascular pain pathway, with a focus on recent findings on ion channel activation and modulation. Furthermore, we focus on the kynurenine pathway since this system contains kynurenic acid, which is an endogenous glutamate receptor antagonist substance, and it has a role in migraine pathophysiology.

Spatial and Temporal Characteristics of Channel Disturbance Zones in Big River, Southeast Missouri (1937-2018)

Ozarks watersheds have responded to land clearing and settlement disturbances by transporting large amounts of gravel and sediment to main valleys of medium-large river systems. Historical gravel and sediment accumulate in disturbance zones, which are areas of excessive channel activity that can be detected over time using historical aerial photographs. This project uses a series of aerial photos from 1937-2018 to identify disturbance zones in the Big River of southeast Missouri, which has a history of lead mining and ore processing that has caused widespread contamination of the channel and floodplain deposits. Variations in active areas of the historical meander belt show that disturbance zones account for 24 percent of the channel length at an interval of one per 2.5 km of channel. Megabars and extensions are the most prominent types of disturbance zones, but translations and cutoffs are larger with higher potential for sediment storage. From 1937 to 1976, areas of channel activity have cycled between expansion and contraction. However, after a period of recovery prior to 1976, disturbance zone areas have been expanding over the last 40 years likely in response to an increase in flood magnitude and frequency from more high intensity rainfall events since 1973.

Robust dynamic feedback stabilization for linear systems with disturbances

In this paper, we are concerned with the dynamic feedback design for linear systems with input disturbance. We propose a new approach to design dynamic feedback such that the disturbance in the control channel can be compensated effectively. An interesting characteristic about the disturbance robustness of dynamic feedback is found. Thanks to this interesting characteristic, we just need to consider the disturbance-free system to make the dynamic feedback design. This fact is well validated by several dynamic feedback laws proposed in this paper. Our results are available for the regular linear system with harmonic disturbance. Moreover, the stabilization of an unstable heat equation with general periodic disturbance is also investigated. In order to validate the theoretical results visually, some numerical simulations are given to show the effectiveness of the proposed dynamic feedback.

Neuromorphic computing with hybrid CNN–Stochastic Reservoir for time series WiFi based human activity recognition

Wi-Fi Channel State Information (CSI) based human activity recognition (HAR) which using channel disturbances caused by signal reflection is a novel way of environment sensing and motion recognition. The collected channels characteristics are heavily influenced by the environment, human activity patterns and subject’s weight and height. These signal variations reflected from body components are mainly affected by static multipath effects comprises random noise and behave differently in individuals, and thus an active field of research. To reach further for achieving automated real-time classification, lower computational cost and easy adaptability to hardware are necessary. In this work, a CSI-based HAR with hybrid framework, Convolutional Neural Network (CNN)-Stochastic Reservoir (SR) (CNN-SR) has been proposed, enabling a subject adaptable and more efficient hardware implementation with minimal computational complexity. A subcarrier correlation matrix is first computed and portrayed in image without preprocessing based on the reflection of the raw CSI signal induced by human activities at regular intervals, allowing visual observation of whole pattern changes. The time-based features are subsequently extracted through CNN and these feature arrays are then feed into SR which based on stochastic spiking neural network (SSNN) in simple cycle reservoir architecture for template matching. SR offers attractive power savings over typical von Neumann systems, by doing stochastic computations. The proposed method has also been demonstrated that is capable for HAR based on partially captured signals. The signal pattern of each segment can be observed in a single sight and then employed for person-to-person template recognition. This enables HAR with minimal computational complexity and solving the inter-person variability concerns. The results demonstrate that the proposed CNN-SR achieves impressive performance in recognizing human activities and surpasses existing models with an average accuracy of 93.49%.

Field test of quantum key distribution over aerial fiber based on simple and stable modulation.

We have developed a simple time-bin phase encoding quantum key distribution system, using the optical injection locking technique. This setup incorporates both the merits of simplicity and stability in encoding, and immunity to channel disturbance. We have demonstrated the field implementation of quantum key distribution over long-distance deployed aerial fiber automatically. During the 70-day field test, we achieved approximately a 1.0 kbps secure key rate with stable performance. Our work takes an important step toward widespread implementation of QKD systems in diverse and complex real-life scenarios.

Synthesis of Adaptive Observer of State Variables for a Linear Stationary Object in the Presence of Measurement Noise

The paper is devoted to the problem of state variables observers synthesis for linear stationary system operating under condition of noise or disturbances in the measurement channel. The paper considers a completely observable linear stationary system with known parameters. It is assumed that the state variables are not measured, and the measured output variable contains a small amplitude (in general, modulo less than one) additive noise or disturbance. It is also assumed that there is no a priori information about the disturbance or noise in the measurement channel (for example, frequency spectrum, covariance, etc.). It is well known that many observer synthesis methods have been obtained for this type of systems, including the Kalman filter, which has proven itself in practice. Under the condition of complete observability and the presence of some a priori information about a random process (which is typical for the case when a disturbance in the measurement channel can be represented as white noise), approaches based on Kalman filtering demonstrate the highest quality estimates of state variables convergence to true values. Without disputing the numerous results obtained using the application of the Kalman filter, an alternative idea of the state variables observer constructing is considered in this paper. The alternative of the new approach is primarily due to the fact that there is no need to use the usual approaches based on the Luenberger observer. The paper proposes an approach based on the estimation of unknown parameters (in this case, an unknown vector of initial conditions of the plant state variables) of a linear regression model. Within the framework of the proposed method, after a simple transformation, a transition is made from a dynamic system to a linear regression model with unknown constant parameters containing noise or disturbing effects. After that, a new nonlinear parametrization of the original regression model and an algorithm for identifying unknown constant parameters using the procedure of dynamic expansion of the regressor and mixing are proposed which ensure reduction the influence of noise. The article presents the results of computer simulations verifying the stated theoretical results.

Data-Based Feedback Relearning Control for Uncertain Nonlinear Systems With Actuator Faults.

In this article, a data-based feedback relearning (FR) algorithm is developed for the uncertain nonlinear systems with control channel disturbances and actuator faults. Uncertain problems will influence the accuracy of collected data episodes, and in turn affect the convergence and optimality of the data-based reinforcement learning (RL) algorithm. The proposed FR algorithm can update the strategy online by relearning from the empirical data. The strategy can continuously approach the optimal solution, which improves the convergence and optimality of the algorithm. Moreover, based on the experience replay technology, a data processing method is designed to further improve the data utilization efficiency and the algorithm convergence. A neural network (NN)-based fault observer is used to achieve the model-free fault compensation. The polynomial activation function is redesigned by using the sigmoid function/hyperbolic tangent activation function, to reduce the difficulty of NNs design for an unknown nonlinear system and improve the generalization. In the face of disturbances and actuator faults, the control performance, algorithm convergence, and optimality of the proposed strategy can be well guaranteed through comparative simulation.

The Emergence of TRP Channels Interactome as a Potential Therapeutic Target in Pancreatic Ductal Adenocarcinoma

Integral membrane proteins, known as Transient Receptor Potential (TRP) channels, are cellular sensors for various physical and chemical stimuli in the nervous system, respiratory airways, colon, pancreas, bladder, skin, cardiovascular system, and eyes. TRP channels with nine subfamilies are classified by sequence similarity, resulting in this superfamily's tremendous physiological functional diversity. Pancreatic Ductal Adenocarcinoma (PDAC) is the most common and aggressive form of pancreatic cancer. Moreover, the development of effective treatment methods for pancreatic cancer has been hindered by the lack of understanding of the pathogenesis, partly due to the difficulty in studying human tissue samples. However, scientific research on this topic has witnessed steady development in the past few years in understanding the molecular mechanisms that underlie TRP channel disturbance. This brief review summarizes current knowledge of the molecular role of TRP channels in the development and progression of pancreatic ductal carcinoma to identify potential therapeutic interventions.

The influence of free-surface vortex on underwater ghost imaging

The vortex generated in the gas–liquid interface may appear in the propagation path, and shows severe disturbance to light propagation, thus affects the final imaging. In this Letter, the influence from the vortex on underwater ghost imaging is investigated experimentally. We find a counter-intuitive phenomenon that imaging quality becomes worse when the vortex is close to the imaging target, which is absolutely different from the typical channel disturbances, such as atmospheric turbulence and scattering. This phenomenon can be explained by the influence mechanism of speckle variation and the effective data distribution on the bucket detector. Meanwhile, a modified imaging method based on the effective bucket samples is proposed to enhance imaging quality and verified in experiment.