Search Results (19)

Although data-driven machine learning methods have been successfully applied to predict complex nonlinear dynamics, forecasting future evolution based on incomplete past information remains a significant challenge. This paper proposes a novel data-driven approach that leverages the dynamical relationships among variables. By integrating Non-Stationary Transformers with LightGBM, we construct a robust model where LightGBM builds a fitting function to capture and simulate the complex coupling relationships among variables in dynamically evolving chaotic systems. This approach enables the reconstruction of missing data, restoring sequence completeness and overcoming the limitations of existing chaotic time series prediction methods in handling missing data. We validate the proposed method by predicting the future evolution of variables with missing data in both dissipative and conservative chaotic systems. Experimental results demonstrate that the model maintains stability and effectiveness even with increasing missing rates, particularly in the range of 30% to 50%, where prediction errors remain relatively low. Furthermore, the feature importance extracted by the model aligns closely with the underlying dynamic characteristics of the chaotic system, enhancing the method’s interpretability and reliability. This research offers a practical and theoretically sound solution to the challenges of predicting chaotic systems with incomplete datasets. Full article

Real-life time series datasets exhibit complications that hinder the study of time series forecasting (TSF). These datasets inherently exhibit non-stationarity as their distributions vary over time. Furthermore, the intricate inter- and intra-series relationships among data points pose challenges for modeling. Many existing TSF models overlook one or both of these issues, resulting in inaccurate forecasts. This study proposes a novel TSF model designed to address the challenges posed by real-life data, delivering accurate forecasts in both multivariate and univariate settings. First, we propose methods termed “weak-stationarizing” and “non-stationarity restoring” to mitigate distributional shift. These methods enable the removal and restoration of non-stationary components from individual data points as needed. Second, we utilize the spectral decomposition of weak-stationary time series to extract informative features for forecasting. To learn features from the spectral decomposition of weak-stationary time series, we exploit a mixer architecture to find inter- and intra-series dependencies from the unraveled representation of the overall time series. To ensure the efficacy of our model, we conduct comparative evaluations against state-of-the-art models using six real-world datasets spanning diverse fields. Across each dataset, our model consistently outperforms or yields comparable results to existing models. Full article

Introduction: Achieving restorative sleep is crucial for overall well-being, yet sleep difficulties affect a substantial portion of the adult population. Sleep disturbances are associated with diminished quality of life, physical complaints, cognitive impairment, and emotional regulation challenges. Objective: This study explores the influence of an innovative experimental bed designed to generate rocking motions on sleep parameters. Methods: A prospective observational study enrolled 60 adult participants, assessing their sleep on a regular stationary bed and the Inoveris bed, providing gentle rocking movements. Polysomnography was conducted, recording electroencephalography, electrooculogram, electromyogram, respiratory effort, and other parameters. Results: The rocking bed significantly increased total sleep time (TST) and reduced N1 sleep stage duration (p < 0.001). Participants also experienced a quicker transition to the N2 sleep stage (p = 0.01), indicative of a faster shift from wakefulness to deeper sleep. Additionally, rocking led to a higher percentage of N1 sleep stages (p = 0.01) and a significant increase in N3 sleep stage duration (p = 0.004). While some results lacked statistical significance, notable trends in the rocking bed group have clinical relevance, consistently improving sleep parameters, including increased TST. The rocking bed also showed a trend towards higher sleep efficiency (SE) and sleep duration percentage, hinting at a potential overall enhancement in sleep quality. Conclusion: This study contributes valuable insights into the potential benefits of rocking motions on sleep architecture. Despite variations in outcomes across studies, our results underscore the potential of rocking beds as a non-pharmacological intervention for enhancing sleep quality. Notable improvements in total sleep time (TST), N1 sleep stage reduction, and accelerated transitions to deeper sleep stages highlight the clinical relevance of rocking interventions. Further research, collaboration, and addressing the identified limitations will advance our understanding of the therapeutic applications of rocking motions in sleep science. Full article

The reconstruction in MRI assumes a uniform radio-frequency field. However, this is violated due to coil field nonuniformity and sensitivity variations. In whole-body MRI, the nonuniformities are more complex due to the imaging with multiple coils that typically have different overall sensitivities that result in sharp sensitivity changes at the junctions between adjacent coils. These lead to images with anatomically inconsequential intensity nonuniformities that include jump discontinuities of the intensity nonuniformities at the junctions corresponding to adjacent coils. The body is also imaged with multiple contrasts that result in images with different nonuniformities. A method is presented for the joint intensity uniformity restoration of two such images to achieve intensity homogenization. The effect of the spatial intensity distortion on the auto-co-occurrence statistics of each image as well as on the joint-co-occurrence statistics of the two images is modeled in terms of Point Spread Function (PSF). The PSFs and the non-stationary deconvolution of these PSFs from the statistics offer posterior Bayesian expectation estimates of the nonuniformity with Bayesian coring. Subsequently, a piecewise smoothness constraint is imposed for nonuniformity. This uses non-isotropic smoothing of the restoration field to allow the modeling of junction discontinuities. The implementation of the restoration method is iterative and imposes stability and validity constraints of the nonuniformity estimates. The effectiveness and accuracy of the method is demonstrated extensively with whole-body MRI image pairs of thirty-one cancer patients. Full article

Natural ecosystems are changing more quickly because of human activities, the type and intensity of which are directly correlated with vegetation greenness. To effectively determine how human activities affect trends in vegetation under climate change, we must differentiate between various types of human activities. The GTWR model can study the spatiotemporal non-stationary relationship between the NDVI trend and climate change. The GTWR model was incorporated into multiple climate variables and improved residual analysis to quantify the contributions of climate change and human activities on vegetation change trends in the Hexi region during different periods. This study divides human activities into four groups based on land use change: urbanization, agricultural expansion, desertification, and ecological restoration to further investigate their contribution to vegetation greenness change. The results showed that in 56.9% of the significant vegetation greening trends between 1982 and 2015, climate factors contributed only 7.4%, while human factors contributed a significant 22.7%. Since the ecological restoration project implemented in 2000, the expansion intensity of ecological restoration and urbanization increased significantly, followed by agricultural expansion and desertification. For the considerable greening trends in the Hexi region, the ecological restoration project contributed 26.7%, while agricultural expansion and urbanization contributed 17.5% and 4.6%, respectively. This study aims to provide new insights for more accurate simulation and evaluation of the interaction effects of climate change and human socio-economic development on vegetation growth. Full article

Large-scale vegetation restoration can significantly affect catchment hydrology. Assessing the impact of vegetation restoration on hydrological regimes is important for water resource management. We chose three less-forested catchments (LFCs, forested area <30%) undergoing major vegetation restoration, i.e., Wuqi, Zhidan, and Liujiahe, and two forested reference catchments (FCs, forested area >77%) that have had secondary forests for more than 150 years, i.e., Zhangcunyi and Huangling, of the Beiluo River basin located in the Loess Plateau (LP) to compare and analyze the stationary and variation characteristics of streamflow and its components from 1958 to 2019. Results show that the mean annual streamflows were 25.07~34.21 and 21.62~48.02 mm in the LFCs and FCs, respectively. The mean streamflow in the LFCs decreased by 50% on average from before the year 2000 to after. The decreasing trend of high flows and increasing trend of low flows is represented in the daily flow duration curves of the LFCs. The result of baseflow separation shows that the average percentages of baseflow in the streamflow were 31.89~43.36% in the LFCs and 58.23~60.14% in the FCs. The Mann–Kendall tests showed significant decreasing trends in annual streamflow (−0.27~−0.70 mm/a) and stormflow (−0.29~−0.64 mm/a) in the LFCs from 1958 to 2019, while the baseflow exhibited increasing trends except for in the Zhidan catchment. The seasonal streamflow and stormflow showed significant decreasing trends in the summer and non-flood season, while the winter and non-flood season’s baseflow increased in LFCs. In FCs, however, the streamflow and its components showed only slight fluctuations over the study period in annual trends, decadal variability, and seasonal trends over the study period, suggesting that FCs have stable hydrological regimes. These results indicate that 20 years of large-scale vegetation restoration greatly influenced hydrological regimes by reducing stormflow and increasing baseflow, and played an important role in streamflow regulation. Conversely, areas with well-preserved vegetation can effectively mitigate the effects of weather and other factors on runoff with stable hydrological regimes. This study can help vegetation restoration and water resource management on the LP. Full article

As an important ecological barrier in northern China, the ecological environment of the Yellow River Basin (YRB) has been greatly improved in recent decades. However, due to spatially non-stationarity, the contribution of human activities and natural factors to vegetation restoration may exhibit different coupling effects in various areas. In this paper, the Normalized Difference Vegetation Index (NDVI) of the YRB from 1986 to 2021 was used as the dependent variable, and terrain, meteorological, and socioeconomic factors were used as independent variables. With the help of Multiscale Geographically Weighted Regression (MGWR), which could handle the scale difference well, combined with Ordinary Least Squares (OLS) and traditional Geographically Weighted Regression (GWR), the spatial non-stationary relationship between vegetation and related factors was discussed. The results showed that: (1) The vegetation was subject to fluctuating changes from 1986 to 2021, mainly improving, with a growth rate of 0.0018/year; the spatial distribution pattern of vegetation in the basin was high in the southeast and low in the northwest. (2) Compared with the OLS and GWR, the MGWR could better explain the relationship between vegetation and various factors. (3) The response scale of vegetation and related factors was significantly variant, and this scale changed with time. The effect scale of terrain factor is lower than climate and social factors. (4) There was obvious spatial heterogeneity in the effects of various influencing factors on vegetation. The vegetation of the upstream was mainly positively affected by mean annual temperature (coefficients ∈ [1.507, 1.784]); while potential evapotranspiration was the dominant factor of vegetation in the middle and lower reaches of the basin (coefficients ∈ [−1.724, −1.704]); it was worth noting that the influence of social factors on vegetation was relatively small. This study deeply explores the spatial non-stationarity of vegetation and various related factors, thereby revealing the evolution law of vegetation pattern and providing scientific support for monitoring and improving the ecological environment quality of the YRB. Full article

Accidents on gas pipelines cause significant damage to the national economy and the economy of the state. Thus, it is necessary to always be prepared for such situations in order to restore the normal operation of the gas pipeline as soon as possible. An important role is played by the execution time of the control actions to localize the accident, pump out the gas, and change the operating modes. It is essential that such control be undertaken, especially if such a situation occurs near a gas-measuring installation for measuring the amount of vented gas. Therefore, the control actions must be error-free in order to quickly stop the non-stationary process, which can lead to undesirable consequences. The paper presents a mathematical model of the operation of the pipeline, developed for the management of the pipeline in an emergency. The analysis of the problem of the occurrence of accidents was carried out, and the effect of liquid on its walls was modeled when the operating mode of the pipeline changed. An example is presented using a numerical model carried out in ANSYS, as well as being analyzed analytically. The results of the calculations are presented, and special attention is paid to the parameters influencing the change in the operating mode of the pipeline. Full article

A study about the effect of different configurations of stationary and movable appendages on the dynamic stability of an autonomous underwater vehicle (AUV) is presented. A new stability index that can be used to assess dynamic stability in the vertical plane is derived. It improves upon the vertical plane stability index by accurately accounting for the contribution of hydrostatic forces to dynamic stability, even at low speeds. The use of the new stability index is illustrated by applying it to a set of AUV configurations based on an AUV initially designed at Virginia Tech and built by Dive Technologies. The applicability of this index depends on the speed of the craft. The range of applicability in terms of speed is presented for the DIVE craft as an example. The baseline design of the DIVE craft has asymmetry in the vertical plane and symmetry in the horizontal plane. A virtual planar motion mechanism (VPMM) is used to obtain the hydrodynamic coefficients of the hull. Design iterations are performed on the baseline design by varying the appendages in shape and size, adding appendages and adding features on appendages. The best and the baseline design from this effort are incorporated in a 6 DOF lumped-parameter model (LPM) to compare results of a straight line maneuver. A computational fluid dynamic (CFD) tool is used to obtain the trajectory comparison of turn-circle maneuver for these two designs. A principal conclusion is the important contribution of a hydrostatic restoring force at low-moderate speeds by using GVgrav and the influence of design of control surfaces, both stationary and non-stationary, in the achievement of control-fixed course stability. Full article

On the modern battlefield, fighting capabilities, such as speed, target detection range, target identification capabilities, and shooting effectiveness, of short-range artillery rocket sets (ARSs) are constantly being improved. Problems arise when attempting to successfully fire such kits in the face of disruption from both the cannon and the moving platform on which the cannon is mounted. Furthermore, the set is a variable mass system since it can fire anywhere from a few to dozens or even hundreds of missiles in a brief period of time, implying that the ARS is a highly nonlinear system of variable parameters (non-stationary). This work shows how to control such a system. If the ARS is placed on a moving basis where there is both a system and measurement noise, the state variables must be restored, and the ARS data must be filtered. Therefore, in addition to the LQR regulator, an extended Kalman filter was used. As a consequence of this synthesis, an LQG (linear quadratic Gaussian) regulator of ARS was obtained, which was used to follow the target along the line of sight. The key goal of this paper is to develop control algorithms that will increase the performance of ARS control in elevation and azimuth, as well as the accuracy of achieving and eliminating maneuverable air targets. Moreover, through the quality criterion adopted, we hope to affect control energy costs while maintaining control precision. Graphical representations of certain computational simulation results are provided. Full article

The application of pulsed electric field (PEF) in electrodialysis has been proven to be efficient for a number of effects: increasing mass transfer rate, mitigation of scaling and fouling, reducing water splitting. Recently, the improvement of the membrane permselectivity for specific counterions was discovered experimentally by the group of Laurent Bazinet (N. Lemay et al. J. Memb. Sci. 604, 117878 (2020)). To better understanding the effect of PEF in electrodialysis, simulations were performed using a non-stationary mathematical model based on the Nernst–Planck and Poisson equations. For the first time, it was not only the condition used when the current density is specified but also the condition when the voltage is set. A membrane and two adjacent diffusion layers are considered. It is shown that when applying the regime used by Lemay et al. (the same current density in conventional continuous current (CC) mode and during the pulses in PEF mode), there is a significant gain in specific permselectivity. It is explained by a reduction in the membrane concentration polarization in PEF mode. In the CC mode of electrodialysis, increasing current density leads to a loss in specific permselectivity: concentration profiles in the diffusion layers and membrane are formed in such a way that ion diffusion reduces the migration flux of the preferentially transferred ion and increases that of the poorly transferred ion. In PEF mode, the concentration profiles are partially restored during the pauses when the current is zero. However, if a different condition is used than the condition applied by Lemay et al., that is, when the same average current density is applied in both the PEF and CC modes, there is no gain in specific permeability. It is shown that within the framework of the applied mathematical model, the specific selectivity depends only on the average current density and does not depend on the mode of its application (CC or PEF mode). Full article

In order to verify the technology of the membrane diffractive imaging system for Chinese next generation geo-stationary earth orbit (GEO) satellite, a series of ground experiments have been carried out using a membrane optical camera with 80 mm aperture (Φ80) lens. The inherent chromatic aberration due to diffractive imaging appears in the obtained data. To address the issue, an effective color restoration algorithm framework by matching, tailoring, and non-linearly stretching the image histograms is proposed in this letter. Experimental results show the proposed approach has good performances in color restoration of the diffractive optical images than previous methods. The effectiveness and robustness of the algorithm are also quantitatively assessed using various color deviation indexes. The results indicate that the chromatic aberration of diffractive images can be effectively removed by about 85%. Also, the proposed method presents reasonable computational efficiency. Full article

The conventional approaches of the design flood calculation are based on the assumption that the hydrological time series is subject to the same distribution in the past, present, and future, i.e., the series should be consistent. However, the traditional methods may result in overdesign in the water conservancy project since the series has non-stationary variations due to climate change and human activities. Therefore, it is necessary to develop a new approach for frequency estimation of non-stationary time series of extreme values. This study used four kinds of mutation test methods (the linear trend correlation coefficient, Mann–Kendall test, sliding t-test, and Pettitt test) to identify the trend and mutation of the annual maximum flow series (1950–2006) of three hydrological stations in the Yiluo River Basin. Then we evaluated the performance of two types of design flood methods (the time series decomposition-synthesis method, the mixed distribution model) under the impacts of climate change and human activities on hydro-meteorological conditions. The results showed that (a) the design flood value obtained by the time series decomposition-synthesis method based on the series of the backward restore is larger than that obtained by the decomposition synthesis method based on the series of the forward restore; (b) when the return period is 100 years or less, the design flood value obtained by the mixed distribution model using the capacity ratio parameter estimation method is less than that obtained by the hybrid distribution model with simulated annealing parameter estimation method; and (c) both methods can overcome sequence inconsistency in design frequencies. This study provides insight into the frequency estimation of non-stationary time series of extreme values under the impacts of climate change and human activities on hydro-meteorological conditions. Full article

We are interested in fast and stable iterative regularization methods for image deblurring problems with space invariant blur. The associated coefficient matrix has a Block Toeplitz Toeplitz Blocks (BTTB) like structure plus a small rank correction depending on the boundary conditions imposed on the imaging model. In the literature, several strategies have been proposed in the attempt to define proper preconditioner for iterative regularization methods that involve such linear systems. Usually, the preconditioner is chosen to be a Block Circulant with Circulant Blocks (BCCB) matrix because it can efficiently exploit Fast Fourier Transform (FFT) for any computation, including the (pseudo-)inversion. Nevertheless, for ill-conditioned problems, it is well known that BCCB preconditioners cannot provide a strong clustering of the eigenvalues. Moreover, in order to get an effective preconditioner, it is crucial to preserve the structure of the coefficient matrix. On the other hand, thresholding iterative methods have been recently successfully applied to image deblurring problems, exploiting the sparsity of the image in a proper wavelet domain. Motivated by the results of recent papers, the main novelty of this work is combining nonstationary structure preserving preconditioners with general regularizing operators which hold in their kernel the key features of the true solution that we wish to preserve. Several numerical experiments shows the performances of our methods in terms of quality of the restorations. Full article

This article starts with an introductory survey of previous work on breaking and restoring the electronic structure symmetry of atoms and molecules by means of two laser pulses. Accordingly, the first pulse breaks the symmetry of the system in its ground state with irreducible representation $IRRE{P}_g$ by exciting it to a superposition of the ground state and an excited state with different $IRRE{P}_e$ . The superposition state is non-stationary, representing charge migration with period T in the sub- to few femtosecond time domains. The second pulse stops charge migration and restores symmetry by de-exciting the superposition state back to the ground state. Here, we present a new strategy for symmetry restoration: The second laser pulse excites the superposition state to the excited state, which has the same symmetry as the ground state, but different $IRRE{P}_e$ . The success depends on perfect time delay between the laser pulses, with precision of few attoseconds. The new strategy is demonstrated by quantum dynamics simulation for an oriented model system, benzene. Full article