Changes In Properties Of Systems Research Articles

TranSMS: Transformers for Super-Resolution Calibration in Magnetic Particle Imaging.

Magnetic particle imaging (MPI) offers exceptional contrast for magnetic nanoparticles (MNP) at high spatio-temporal resolution. A common procedure in MPI starts with a calibration scan to measure the system matrix (SM), which is then used to set up an inverse problem to reconstruct images of the MNP distribution during subsequent scans. This calibration enables the reconstruction to sensitively account for various system imperfections. Yet time-consuming SM measurements have to be repeated under notable changes in system properties. Here, we introduce a novel deep learning approach for accelerated MPI calibration based on Transformers for SM super-resolution (TranSMS). Low-resolution SM measurements are performed using large MNP samples for improved signal-to-noise ratio efficiency, and the high-resolution SM is super-resolved via model-based deep learning. TranSMS leverages a vision transformer module to capture contextual relationships in low-resolution input images, a dense convolutional module for localizing high-resolution image features, and a data-consistency module to ensure measurement fidelity. Demonstrations on simulated and experimental data indicate that TranSMS significantly improves SM recovery and MPI reconstruction for up to 64-fold acceleration in two-dimensional imaging.

Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment

Abstract. Deforestation can considerably affect transpiration dynamics and magnitudes at the catchment scale and thereby alter the partitioning between drainage and evaporative water fluxes released from terrestrial hydrological systems. However, it has so far remained problematic to directly link reductions in transpiration to changes in the physical properties of the system and to quantify these changes in system properties at the catchment scale. As a consequence, it is difficult to quantify the effect of deforestation on parameters of catchment-scale hydrological models. This in turn leads to substantial uncertainties in predictions of the hydrological response after deforestation but also to a poor understanding of how deforestation affects principal descriptors of catchment-scale transport, such as travel time distributions and young water fractions. The objectives of this study in the Wüstebach experimental catchment are therefore to provide a mechanistic explanation of why changes in the partitioning of water fluxes can be observed after deforestation and how this further affects the storage and release dynamics of water. More specifically, we test the hypotheses that (1) post-deforestation changes in water storage dynamics and partitioning of water fluxes are largely a direct consequence of a reduction of the catchment-scale effective vegetation-accessible water storage capacity in the unsaturated root zone (SU, max) after deforestation and that (2) the deforestation-induced reduction of SU, max affects the shape of travel time distributions and results in shifts towards higher fractions of young water in the stream. Simultaneously modelling streamflow and stable water isotope dynamics using meaningfully adjusted model parameters both for the pre- and post-deforestation periods, respectively, a hydrological model with an integrated tracer routine based on the concept of storage-age selection functions is used to track fluxes through the system and to estimate the effects of deforestation on catchment travel time distributions and young water fractions Fyw. It was found that deforestation led to a significant increase in streamflow accompanied by corresponding reductions of evaporative fluxes. This is reflected by an increase in the runoff ratio from CR=0.55 to 0.68 in the post-deforestation period despite similar climatic conditions. This reduction of evaporative fluxes could be linked to a reduction of the catchment-scale water storage volume in the unsaturated soil (SU, max) that is within the reach of active roots and thus accessible for vegetation transpiration from ∼258 mm in the pre-deforestation period to ∼101 mm in the post-deforestation period. The hydrological model, reflecting the changes in the parameter SU, max, indicated that in the post-deforestation period stream water was characterized by slightly yet statistically not significantly higher mean fractions of young water (Fyw∼0.13) than in the pre-deforestation period (Fyw∼0.12). In spite of these limited effects on the overall Fyw, changes were found for wet periods, during which post-deforestation fractions of young water increased to values Fyw∼0.37 for individual storms. Deforestation also caused a significantly increased sensitivity of young water fractions to discharge under wet conditions from dFyw/dQ=0.25 to 0.36. Overall, this study provides quantitative evidence that deforestation resulted in changes in vegetation-accessible storage volumes SU, max and that these changes are not only responsible for changes in the partitioning between drainage and evaporation and thus the fundamental hydrological response characteristics of the Wüstebach catchment, but also for changes in catchment-scale tracer circulation dynamics. In particular for wet conditions, deforestation caused higher proportions of younger water to reach the stream, implying faster routing of stable isotopes and plausibly also solutes through the sub-surface.

Predictive Control of District Heating System Using Multi-Stage Nonlinear Approximation with Selective Memory

Innovative heating networks with a hybrid generation park can make an important contribution to the energy turnaround. By integrating heat from several heat generators and a high proportion of different renewable energies, they also have a high degree of flexibility. Optimizing the operation of such systems is a complex task due to the diversity of producers, the use of storage systems with stratified charging and continuous changes in system properties. Besides, it is necessary to consider conflicting economic and ecological targets. Operational optimization of district heating systems using nonlinear models is underrepresented in practice and science. Considering ecological and economic targets, the current work focuses on developing a procedure for an operational optimization, which ensures a continuous optimal operation of the heat and power generators of a local heating network. The approach presented uses machine learning methods, including Gaussian process regressions for a repeatedly updated multi-stage approximation of the nonlinear system behavior. For the formation of the approximation models, a selection algorithm is utilized to choose only essential and current process data. By using a global optimization algorithm, a multi-objective optimal setting of the controllable variables of the system can be found in feasible time. Implemented in the control system of a dynamic simulation, significant improvements of the target variables (operating costs, CO2 emissions) can be seen in comparison with a standard control system. The investigation of different scenarios illustrates the high relevance of the presented methodology.

Self-Tuning Deep Brain Stimulation Controller for Suppression of Beta Oscillations: Analytical Derivation and Numerical Validation.

Closed-loop control strategies for deep brain stimulation (DBS) in Parkinson's disease offer the potential to provide more effective control of patient symptoms and fewer side effects than continuous stimulation, while reducing battery consumption. Most of the closed-loop methods proposed and tested to-date rely on controller parameters, such as controller gains, that remain constant over time. While the controller may operate effectively close to the operating point for which it is set, providing benefits when compared to conventional open-loop DBS, it may perform sub-optimally if the operating conditions evolve. Such changes may result from, for example, diurnal variation in symptoms, disease progression or changes in the properties of the electrode-tissue interface. In contrast, an adaptive or “self-tuning” control mechanism has the potential to accommodate slowly varying changes in system properties over a period of days, months, or years. Such an adaptive mechanism would automatically adjust the controller parameters to maintain the desired performance while limiting side effects, despite changes in the system operating point. In this paper, two neural modeling approaches are utilized to derive and test an adaptive control scheme for closed-loop DBS, whereby the gain of a feedback controller is continuously adjusted to sustain suppression of pathological beta-band oscillatory activity at a desired target level. First, the controller is derived based on a simplified firing-rate model of the reciprocally connected subthalamic nucleus (STN) and globus pallidus (GPe). Its efficacy is shown both when pathological oscillations are generated endogenously within the STN-GPe network and when they arise in response to exogenous cortical STN inputs. To account for more realistic biological features, the control scheme is then tested in a physiologically detailed model of the cortical basal ganglia network, comprised of individual conductance-based spiking neurons, and simulates the coupled DBS electric field and STN local field potential. Compared to proportional feedback methods without gain adaptation, the proposed adaptive controller was able to suppress beta-band oscillations with less power consumption, even as the properties of the controlled system evolve over time due to alterations in the target for beta suppression, beta fluctuations and variations in the electrode impedance.

Predictive mechanics-based model for depth of cut (DOC) of waterjet in soft tissue for waterjet-assisted medical applications.

The use of waterjet technology is now prevalent in medical applications including surgery, soft tissue resection, bone cutting, waterjet steerable needles, and wound debridement. The depth of the cut (DOC) of a waterjet in soft tissue is an important parameter that should be predicted in these applications. For instance, for waterjet-assisted surgery, selective cutting of tissue layers is a must to avoid damage to deeper tissue layers. For our proposed fracture-directed waterjet steerable needles, predicting the cut depth of the waterjet in soft tissue is important to develop an accurate motion model, as well as control algorithms for this class of steerable needles. To date, most of the proposed models are only valid in the conditions of the experiments and if the soft tissue or the system properties change, the models will become invalid. The model proposed in this paper is formulated to allow for variation in parameters related to both the waterjet geometry and the tissue. In this paper, first the cut depths of waterjet in soft tissue simulants are measured experimentally, and the effect of tissue stiffness, waterjet velocity, and nozzle diameter are studied on DOC. Then, a model based on the properties of the tissue and the waterjet is proposed to predict the DOC of waterjet in soft tissue. In order to verify the model, soft tissue properties (constitutive response and fracture toughness) are measured using low strain rate compression tests, Split-Hopkinson-Pressure-Bar (SHPB) tests, and fracture toughness tests. The results show that the proposed model can predict the DOC of waterjet in soft tissue with acceptable accuracy if the tissue and waterjet properties are known. Graphical Abstract (Left) An overview of the problems of traditional steerable needles and the solutions provided by waterjet steerable needles. (A) Traditional tip-steerable needles and tip-bent needles suffer from poor curvature, especially in soft tissues. (B) Traditional steerable needles are unable to accomplish many bends because the cutting force only results from drastic tissue deformation. (C) The first step for realization of waterjet steerable needles is to understand and model the interaction between waterjet and soft tissues at the tip (predictive model for depth of cut). (D) Then, the equilibrium between shapes cut in the tissue and the straight elastic needle should be understood. (Right) Waterjet steerable needles in which the direction of the tissue fracture is contr olled by waterjet and then the flexible needle follows. The first step for waterjet steerable needle realization is to predict the depth of waterjet cut.

Optimal In-Operation Redesign of Mechanical Systems Considering Vibrations—A New Methodology Based on Frequency-Band Constraint Formulation and Efficient Sensitivity Analysis

The vibrational behavior of components in mechanical systems like drives and robots can become critical under changes in the system properties or loading in operation. Such undesired vibration can lead to detrimental conditions including excess wear, fatigue, discomfort, and acoustic emissions. Systems are designed to avoid certain frequencies to avoid such problems, but system parameters can change during operation due damage, wear, or change in loading. An example is the change in system properties or operation state that then activates resonance frequencies in our system. Therefore, this work has the goal of modifying the modal behavior of a system to avoid vibrational problems. Methods of design optimization are applied to find a new optimum design for this altered condition. Here, this is limited to the addition of mass in order to move the resonance frequency out of critical ranges. This though requires a new formulation of the optimization problem. We propose a new constraint formulation to avoid frequency ranges. To increase efficiency, a reduced analytical sensitivity analysis is introduced. This methodology is demonstrated on two test cases: a two-mass oscillator followed by a test case of higher complexity which is a gear housing considering over 15,000 design variables. The results show that the optimization solution gives the position and amount of mass added, which is a discrete solution that is practically implementable.

Adaptive Piezoelectric Absorber for Active Vibration Control

Passive vibration control solutions are often limited to working reliably at one design point. Especially applied to lightweight structures, which tend to have unwanted vibration, active vibration control approaches can outperform passive solutions. To generate dynamic forces in a narrow frequency band, passive single-degree-of-freedom oscillators are frequently used as vibration absorbers and neutralizers. In order to respond to changes in system properties and/or the frequency of excitation forces, in this work, adaptive vibration compensation by a tunable piezoelectric vibration absorber is investigated. A special design containing piezoelectric stack actuators is used to cover a large tuning range for the natural frequency of the adaptive vibration absorber, while also the utilization as an active dynamic inertial mass actuator for active control concepts is possible, which can help to implement a broadband vibration control system. An analytical model is set up to derive general design rules for the system. An absorber prototype is set up and validated experimentally for both use cases of an adaptive vibration absorber and inertial mass actuator. Finally, the adaptive vibration control system is installed and tested with a basic truss structure in the laboratory, using both the possibility to adjust the properties of the absorber and active control.

“Liquid-Gas” Transition in the Supercritical Region: Fundamental Changes in the Particle Dynamics

Recently, we have proposed a new dynamic line on the phase diagram in the supercritical region, the Frenkel line. Crossing the line corresponds to the radical changes of system properties. Here, we focus on the dynamics of model Lennard-Jones and soft-sphere fluids. We show that the location of the line can be rigorously and quantitatively established on the basis of the velocity autocorrelation function (VAF) and mean-square displacements. VAF is oscillatory below the line at low temperature, and is monotonically decreasing above the line at high temperature. Using this criterion, we show that the crossover of particle dynamics and key liquid properties occur on the same line. We also show that positive sound dispersion disappears in the vicinity of the line in both systems. We further demonstrate that the dynamic line bears no relationship to the existence of the critical point. Finally, we find that the region of existence of liquidlike dynamics narrows with the increase of the exponent of the repulsive part of interatomic potential.

Verification of Mixed-Signal Systems with Affine Arithmetic Assertions

Embedded systems include an increasing share of analog/mixed-signal components that are tightly interwoven with functionality of digital HW/SW systems. A challenge for verification is that even small deviations in analog components can lead to significant changes in system properties. In this paper we propose the combination of range-based, semisymbolic simulation with assertion checking. We show that this approach combines advantages, but as well some limitations, of multirun simulations with formal techniques. The efficiency of the proposed method is demonstrated by several examples.

Coupled 802.11 Flows in Urban Channels: Model and Experimental Evaluation

Contending flows in multihop 802.11 wireless networks compete with two fundamental asymmetries: 1) channel asymmetry, in which one flow has a stronger signal, potentially yielding physical layer capture; and 2) topological asymmetry, in which one flow has increased channel state information, potentially yielding an advantage in winning access to the channel. Prior work has considered these asymmetries independently with a highly simplified view of the other. However, in this paper, we perform thousands of measurements on coupled flows in urban environments and build a simple yet accurate model that jointly considers information and channel asymmetries. We show that if these two asymmetries are not considered jointly, throughput predictions of even two coupled flows are vastly distorted from reality when traffic characteristics are only slightly altered (e.g., changes to modulation rate, packet size, or access mechanism). These performance modes are sensitive not only to small changes in system properties, but also small-scale link fluctuations that are common in an urban mesh network. We analyze all possible capture relationships for two-flow subtopologies and show that capture of the reverse traffic can allow a previously starving flow to compete fairly. Finally, we show how to extend and apply the model in domains such as modulation rate adaptation and understanding the interaction of control and data traffic.

A simple lab exercise to challenge student's ability to predict changes in the functional state of the cardiovascular system

Students routinely learn how separate properties comprising the functional state of the cardiovascular system will individually affect blood pressure, cardiac output, and tissue perfusion. The challenge is learning to integrate such compartmentalized understanding to interpret how the overall state adjusts based upon observed changes in dependent hemodynamic variables. A simple lab exercise facilitates integration of compartmentalized learning. A student rides a stationary bike while the workload is increased in steps with heart rate and blood pressure measured at each step. Students must then apply their knowledge of vascular hemodynamics and cardiac load to estimate changes in cardiac output and peripheral resistance from the observed changes in heart rate and blood pressure. They next explain how arteriolar vascular tone must be altered so as to maintain relatively stable diastolic arterial pressure while meeting the need for increased perfusion to the working muscle, followed by discussion of the expected changes in myocardial contractility and venous capacitance necessary to support increased circulatory flow. Control of state properties by autonomic reflexes is then discussed. As the intended outcome, students gain insight into the orchestrated changes in system properties that must occur as the body adjusts to moderate exercise, by predicting the new system state based upon observed changes in heart rate and blood pressure.

Adaptations in a hierarchical food web of southeastern Lake Michigan

Two issues in ecological network theory are: (1) how to construct an ecological network model and (2) how do entire networks (as opposed to individual species) adapt to changing conditions? We present a novel method for constructing an ecological network model for the food web of southeastern Lake Michigan (USA) and we identify changes in key system properties that are large relative to their uncertainty as this ecological network adapts from one time point to a second time point in response to multiple perturbations. To construct our food web for southeastern Lake Michigan, we followed the list of seven recommendations outlined in Cohen et al. [Cohen, J.E., et al., 1993. Improving food webs. Ecology 74, 252–258] for improving food webs. We explored two inter-related extensions of hierarchical system theory with our food web; the first one was that subsystems react to perturbations independently in the short-term and the second one was that a system's properties change at a slower rate than its subsystems’ properties. We used Shannon's equations to provide quantitative versions of the basic food web properties: number of prey, number of predators, number of feeding links, and connectance (or density). We then compared these properties between the two time-periods by developing distributions of each property for each time period that took uncertainty about the property into account. We compared these distributions, and concluded that non-overlapping distributions indicated changes in these properties that were large relative to their uncertainty. Two subsystems were identified within our food web system structure ( p < 0.001). One subsystem had more non-overlapping distributions in food web properties between Time 1 and Time 2 than the other subsystem. The overall system had all overlapping distributions in food web properties between Time 1 and Time 2. These results supported both extensions of hierarchical systems theory. Interestingly, the subsystem with more non-overlapping distributions in food web properties was the subsystem that contained primarily benthic taxa, contrary to expectations that the identified major perturbations (lower phosphorous inputs and invasive species) would more greatly affect the subsystem containing primarily pelagic taxa. Future food-web research should employ rigorous statistical analysis and incorporate uncertainty in food web properties for a better understanding of how ecological networks adapt.

Interaction of polymer matrix and bound water in poly(N-vinylcaprolaktam) films

Interaction of water molecules and the polymer matrix of poly(N-vinylcaprolaktam) (PVCL), depending on temperature (−100 and 50°C) and water concentration (less than 1, 5 and 24 wt %), was investigated using the dielectric spectroscopy method (at 10−1–107 Hz). The presence of characteristic temperature points of changes of system properties, whose values depend on the quantity of water molecules in the polymer, was identified. It was found that the mechanism of temperature influence and water concentrations changes the characteristics of hydrogen bonds.

Hadron production and phase changes in relativistic heavy-ion collisions

We study soft hadron production in relativistic heavy-ion collisions in a wide range of reaction energy, 4.8 GeV \( \sqrt{{s_{{\rm NN}}}}\)≥200 GeV, we use continuity of particle yields and statistical parameters to predict the hadron production at \( \sqrt{{s_{{\rm NN}}}}\) = 62.4 GeV, and obtain total yields of hadrons at \( \sqrt{{s_{{\rm NN}}}}\) = 130 GeV. We consider, in depth, the pattern we uncover within the hadronization condition, and discuss possible mechanisms associated with the identified rapid change in system properties at \( \sqrt{{s_{{\rm NN}}^{{\rm cr}}}}\) . We propose that the chemically over-saturated 2 + 1 flavor hadron matter system undergoes a 1st-order phase transition.

Determining the random time step in a constant spatial step particle tracking algorithm

In some cases, the accuracy and efficiency of a particle tracking model may be greatly enhanced by determining the time for a particle to travel a specified distance rather than the distance traveled during some time interval. For instance, it may be desirable to know when a particle reaches a boundary or interface or a location where the system properties change. In this work, we derive an analytical expression in the form of a probability function describing the distribution of random times necessary for a particle to diffusively travel a specified distance. Upon substitution of the specified distance and a random number for the probability, the expression may be solved for the necessary time. Comparison of the results from this equation with an empirical expression determined by James and Chrysikopoulos (Chem. Eng. Sci. 56(23)(2001)6535) shows excellent agreement. Recommendations for implementing the analytical solution into particle tracking algorithms with or without a deterministic velocity component are included. This general equation is amenable to use in modeling both fractured and porous media systems.

Adaptive control of cyclic movements as muscles fatigue using functional neuromuscular stimulation.

For individuals with spinal cord injuries, functional neuromuscular stimulation (FNS) systems can be used to activate paralyzed muscles in order to restore function, provide exercise, or assist in movement therapy. In previous work, the pattern generator/pattern shaper (PG/PS) adaptive controller was evaluated on subjects with spinal cord injuries and was able to automatically adjust stimulation parameters to account for individual subject differences and system response nonlinearities. In this study, the PG/PS control system was utilized in extended trials. Results indicated that the controller adapted stimulation patterns in an online manner to account for changes in system properties due to fatigue.

A LOCAL MODAL/PERTURBATIONAL METHOD FOR ESTIMATING FREQUENCY RESPONSE STATISTICS OF BUILT-UP STRUCTURES WITH UNCERTAIN PROPERTIES

A local modal/perturbational method is described which enables estimates to be made of the statistics of frequency response functions of a system whose properties are uncertain. The method is computationally very efficient, providing these estimates at little cost above that required to perform a single deterministic frequency response prediction. Such an approach is typically required when there is significant uncertainty or variability in the properties of the system under consideration. This would often be at higher frequencies, where the dynamic behaviour becomes increasingly sensitive to small changes in system properties, but not at frequencies high enough such that broad-brush statistical methods, such as statistical energy analysis, are appropriate.In the approach the system is divided into subsystems. The frequency response of the baseline system is found using modal analysis. The global modes of the baseline system are found in terms of the subsystem modes using component mode synthesis. Uncertainty is then assumed to exist in the local modal properties of the subsystems. A perturbation is found which relates small changes in the local modal properties to those in the global modal properties, enabling the frequency response of the perturbed system to be estimated. Finally, a Monte Carlo simulation is used to estimate the frequency response function statistics. Numerical results are presented for a system comprising two spring-coupled rods.

Joint features of pressure effects and specific heat of RBa 2Cu 3Ox at distinct nh values

Investigations of specific heat and T c under pressure are presented for YBa 2Cu 3O x (Y123), NdBa 2Cu 3O x (Nd123) and Y 1−yCa yBa 2Cu 3O x (YCa123) for various oxygen contents. In Y123, at the maximum of the specific-heat jump ΔC/T c the pressure dependence of the transition temperature dT c/dp shows a zero crossing. Inversely, at the maximum of dT c/dp the jump in the specific heat becomes minimal. With Ca doping these joint features shift to lower oxygen contents x, whereas Nd123 causes a shift into the opposite direction. Considering the hole doping by Ca and the larger chain fragmentation in Nd123, we rescaled our results with respect to the hole content n h in the CuO 2 planes. In this plot features coalesce in two fixed hole concentrations, n h≈0.11 and n h0.17, irrespective of the substitution and doping. The maximum in ΔC/T c may be related to the appearance of a quantum critical point due to the disappearance of a pseudogap for hole contents above n h≈0.17. The features at n h≈0.11 point to a drastic change in system properties at this hole content that may be connected to various anomalies found in other properties reported in the literature.

Shear-induced disappearances of energy minima and plastic deformation in polymer glasses

The potential energy landscape of a polymer glass is examined with regard to plastic deformation under shear strain. Shear strain is found to cause the disappearance of local potential energy minima, as determined by the decrease to zero of the curvature of the local minima. If the local energy minimum which the system is in disappears, the system becomes mechanically unstable and is forced to relax to an alternate energy minimum. This mechanical instability, which leads to a discontinuous change in system properties, is inherently irreversible—the new local minimum will not disappear, in general, when the strains are reversed. These disappearances of local energy minima and the associated irreversible relaxations lead to plastic deformation in polymer glasses.

Fuzzy model reference learning control: a new control paradigm for smart structures

The overall goal of this study lies in the synergistic combination of intelligent control and smart materials to produce an adaptive and robust controlled system. In order to accomplish this task, steel cantilever beam (the plant) was augmented with a lead zirconate titanate (PZT) actuator pair and a PZT sensor. A controller was developed using algorithms produced from fuzzy logic controls and adaptive fuzzy controls. The expected goal is to dampen the fundamental vibration mode of the system in the presence of modeling uncertainties. Fuzzy model reference learning control (FMRLC) is a learning system with the capability to improve its performance over a period of time when various plant uncertainties are introduced. First, the controller will be employed on unseen plant disturbances. The robustness of the system will be examined when the cantilever beam system properties change. Extra masses will be added to account for variations in system parameters. Controllers such as positive position feedback and direct fuzzy will be developed and compared to the adaptive fuzzy controller.