Parameter Constraints Research Articles

Distributed adaptive coordinative control for virtually coupled train set with considering parametric uncertainty and state constraints

Distributed adaptive coordinative control for virtually coupled train set with considering parametric uncertainty and state constraints

Unveiling the Effects of Coupling Extended Proca-Nuevo Gravity on Cosmic Expansion with Recent Observations

Abstract We study Coupling Extended Proca-Nuevo gravity, a non-linear theory extending from dRGT massive gravity with a spin-1 field. This theory is shown to yield reliable, ghost-free cosmological solutions, modeling both the Universe’s thermal history and late-time acceleration. By analyzing data from Dark energy spectroscopic instruments (DESI), Cosmic Chronometer (CCh), Gamma Ray Bursts (GRBs), and Type Ia Supernova (SNeIa), we derive parameter constraints with up to 3σ confidence, demonstrating good agreement with observations. Our comparison of BAO data from WiggleZ and DESI highlights its constraining power on the Hubble constant. The analysis of the cosmographic parameter, q shows the statistical compatibility with the recent data. Further, this indicates that Universe’s current accelerated expansion aligns with quintessential behavior.

Power spectrum multipoles and clustering wedges during the Epoch of Reionization

Abstract We study the viability of using power spectrum clustering wedges as summary statistics of 21 cm surveys during the Epoch of Reionization (EoR). For observations in a wide redshift range z ∼ 7 − 9 corresponding to a line-of-sight scale of ∼500 Mpc, the power spectrum is subject to anisotropic effects due to the evolution along the light-of-sight. Information on the physics of reionization can be extracted from the anisotropy using the power spectrum multipoles. Signals of the power spectrum monopole are highly correlated at scales smaller than the typical ionization bubble, which can be disentangled by including higher-order multipoles. By simulating observations of the low frequency part of the Square Kilometre Array (SKA) Observatory, we find that the sampling of the cylindrical wavenumber k-space is highly non-uniform due to the baseline distribution, i.e. the distribution of antenna pairs sampling different transverse k⊥ scales. Measurements in clustering wedges partition the cylindrical k-space into different radial k∥ scales, and can be used for isolating parts of k-space with relatively uniform sampling, allowing for more precise parameter inference. Using Fisher Matrix forecasts, we find that the reionization model can be inferred with per-cent level precision with ∼120 hrs of integration time using SKA-Low. Compared to model inference using only the power spectrum monopole above the foreground wedge, model inference using multipole power spectra in clustering wedges yields a factor of ∼3 improvement on the marginalised 1D parameter constraints.

Joint Observations of Late Universe Probes: Cosmological Parameter Constraints from Gravitational Wave and Type Ia Supernova Data

The growing tensions between the early Universe and the late Universe increasingly highlight the importance of developing precise probes for late cosmology. As significant late-Universe probes, Type Ia supernovae (SNe Ia) and gravitational waves (GWs) can provide measurements of relative and absolute distances, respectively. Their complementary nature is likely to break the degeneracies among cosmological parameters, thereby yielding more precise constraints. In this study, we use 43 gravitational-wave sources from the Third LIGO–Virgo–KAGRA Gravitational-Wave Transient Catalog (GWTC-3) and 1590 light curves from Pantheon+ compilation to constrain the dark energy models, as an attempt to achieve precise late-Universe cosmological constraints. For the dark siren GW event, we estimate the corresponding redshift using the binary black hole redshift distribution model. The combination of GW and SNe Ia data could provide the precision on the Hubble constant H 0 and the present matter density Ω m of approximately 16% and 8% for the ΛCDM model. If we consider the equation of state of dark energy w, the combination sample constrains the precision of w to approximately 24%. Although the combination of GWs and SNe Ia observations effectively breaks degeneracies among various cosmological parameters, yielding more stringent constraints, the precision of these constraints still does not meet the stringent standards required by precision cosmology. However, it is reasonable to anticipate that, in the near future, the joint observations of GWs and SNe Ia will become a powerful tool, particularly in the late Universe, for the precise measurement of cosmological parameters.

Stress and Strain Analysis for a Topological Optimized Beam

This paper presents a study of a beam manufactured using fused deposition modeling (FDM) which was topologically optimized and subjected to 3-point bending. In this paper polylactic acid (PLA) was used as a material in order to obtain the beams. Topology optimization is a method widely used in the additive manufacturing (AM) field, that uses algorithmic models to optimize the material layout within some parametric restrictions, like conditions, constraints, or sets of loads and it maximizes the performance and capability of the design by extracting material from different zones that are insignificant in terms of carrying loads to reduce the weight of the model. In the first step, the stress and strain state of the simple beam was numerically and analytically calculated, likewise, the experimental test of the beam subjected to 3-point bending was achieved. After the calculus for the simple beam, the next phase aims at the topological optimization process of the beam subjected to 3-point bending. For all the numerical investigations a calibrated material determined experimentally was used. Following calculations and experimental tests, a final version of the beam topologically optimized was reached, with a minimization of the cost regarding the mass of the beam and the material required for its reproduction.

Third-order intrinsic alignment of SDSS BOSS LOWZ galaxies

Cosmic shear is a powerful probe of cosmology, but it is affected by the intrinsic alignment (IA) of galaxy shapes with the large-scale structure. Upcoming surveys such as Euclid and Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) require an accurate understanding of IA, particularly for higher-order cosmic shear statistics that are vital for extracting the most cosmological information. In this paper, we report the first detection of third-order IA correlations using the LOWZ galaxy sample from the Sloan Digital Sky Survey (SDSS) Baryon Oscillation Spectroscopic Survey (BOSS). We compare our measurements with predictions from the MICE cosmological simulation and an analytical model inspired by the Non-linear Linear Alignment (NLA) model and informed by second-order correlations. We also explore the dependence of the third-order correlation on the galaxies' luminosity. We find that the amplitude $A_ IA $ of the IA signal is non-zero at the $4.7 level for scales between Mpc Mpc Mpc Mpc $ the inferred $A_ IA $ agrees both with the prediction from the simulation and estimates from second-order statistics within 1sigma but deviations arise at smaller scales. Our results demonstrate the feasibility of measuring third-order IA correlations and using them for constraining IA models. The agreement between second- and third-order IA constraints also opens the opportunity for a consistent joint analysis and IA self-calibration, promising tighter parameter constraints for upcoming cosmological surveys.

Probing barrow entropy models with future event horizon as IR cutoff

We develop formulations for barrow holographic dark energy (BHDE) in both non-interacting and interacting scenarios within a cosmological framework, applying the conventional holographic principle. Model parameter constraints are determined through the Markov Chain Monte Carlo (MCMC) method, utilizing different datasets. The investigation excavates into the models' kinematic behavior, exploring the transition from deceleration to acceleration and tracking the evolution of the equation of state parameters. Further, these models can pretend the evolution of dark energy and matter in the Universe. Additionally, a thermodynamic analysis employing future event horizons is conducted, confirming the validation of the generalized second law of thermodynamics. The resultant of the BHDE models strongly suggests that the Universe is presently experiencing an accelerated phase attributed to dark energy.

An explicit solution to harvesting behaviors in a predator–prey system

AbstractThis paper derives closed‐form solutions for a strategic, simultaneous harvesting in a predator–prey system. Using a parametric constraint, it establishes the existence and uniqueness of a linear feedback‐Nash equilibrium involving two specialized fleets and allows for continuous time results for a class of payoffs that have constant elasticity of the marginal utility. These results contribute to the scarce literature on analytically tractable predator–prey models with endogenous harvesting. A discussion based on industry size effects is provided to highlight the role played by biological versus strategic interactions in the multispecies context.Recommendations for Resource Managers This model presents a thorough examination of the economic inefficiencies inherent in the exploitation dynamics of two interdependent species, elucidating the complex interplay between ecological interactions and economic outcomes. The size of the fishing industries constitutes a significant variable that must be integrated into the formulation of pertinent policy recommendations. This constitutes an advancement towards a more time‐consistent approach to Ecosystem‐Based Fishery Management (EBFM).

A Parameter-Adaptive Method for Primary Frequency Regulation of Grid-Forming Direct-Drive Wind Turbines

When wind turbines contribute to system frequency support using virtual synchronous generator (VSG) control, conventional VSG methods often fall short of meeting operational demands, particularly in terms of inertia and frequency support. In this study, considering both the frequency regulation and dynamic performance of VSG, a novel parameter design method that enhances frequency modulation capabilities is proposed in this paper. Initially, VSG control is integrated into the grid-side converter of a direct-drive permanent magnet synchronous generator (D-DPMSG) wind turbine. A small-signal model of the D-DPMSG-VSG active power is then formulated to analyze how the moment of inertia and damping coefficient impact system stability. Subsequently, ensuring that system parameter constraints are met, the key parameters of VSG are adaptively designed to dynamically adjust the system’s frequency and output power during transient responses. Finally, simulation results based on D-DPMSG-VSG in MATLAB/Simulink validated the feasibility, effectiveness, and advantages of the proposed parameter-adaptive VSG control strategy for enhancing the frequency modulation (FM) performance of wind turbines.

High precision DSRC and LiDAR data integration positioning method for autonomous vehicles based on CNN

In order to improve the safe driving and automatic positioning capability of autonomous vehicles, a high-precision DSRC and LiDAR data integration positioning technology for autonomous vehicles based on CNN is proposed. Import the data of Dedicated Short Range Communications and Light Detection and Ranging for automatic driving vehicle positioning, carry out kinematic analysis of autonomous driving vehicles under multi-sensor fusion, and transform the data of DSRC and LiDAR sensors into tightly coupled coordinate systems; The CNN depth learning method is used to compensate the position and attitude tracking estimation error under the overall time stamp synchronization of the sensor through adaptive information tracking; The first and second order feedforward compensation is made for the positioning parameters of the autonomous driving vehicle using the PID model, and the point cloud feature matching model is fused to complete the estimation of the positioning attitude parameters of the autonomous driving vehicle. In order to eliminate the noise interference under the DSRC communication mechanism, the Kalman filter function is used to automatically optimize the constraint parameters in the point cloud feature detection model, and the positioning error parameters are dynamically filtered and adjusted; Kinematics analysis is carried out for the driving state of the vehicle, and the positioning error in the vehicle movement is controlled through the difference technology to achieve high-precision DSRC and LiDAR data integration positioning. The simulation results show that this method can integrate and locate the high-precision DSRC and LiDAR data of the autonomous vehicle, and the attitude estimation and positioning accuracy of the vehicle is good, while the error of the attitude parameter estimation of the autonomous vehicle is low.

Computer aided diagnoses for detecting the severity of Keratoconus

Abstract Problem Corneal topography instruments have limited parameter constraints for calculating precise defect ratios on the basis of the cone base area of the anterior axial curvature map for patients with Keratoconus (KC). Aim The aim of this study is to use thresholding-based segmentation and morphological techniques to calculate the pathological ratio of the keratoconic cornea through cone base area extraction for the detection of KC severity and tracking of disease development. Methods Data were collected from February 2022 to March 2023, comprising 97 cases from private clinics in southern Iraq. Disease severity was categorized into three stages, namely, mild, moderate, and severe, according to the topographic KC classification by a senior ophthalmologist. The Galilei system was used in obtaining the corneal topography images. The study proposed an image analysis method for corneal topography images using MATLAB R2020a. The method had four main steps: preprocessing, image segmentation, morphological processing, and pathological ratio calculation. Moreover, pathological ratio was compared with the KC severity through statistical analysis. A P-value less than 0.05 indicated statistically significant results. Results The majority of the cases in the mild category had a pathological ratio of ≤20%, and the moderate category had a higher prevalence ranging from 21 to 40%. The severe category had the highest distribution (<40%). A P-value of <0.001 indicated significant and clear link between KC stages and pathologic ratio. Conclusion The algorithm used for extracting the cone base area of the keratoconic cornea at different stages was validated by an ophthalmic specialist to ensure that the cone base area was appropriately extracted. The findings may help ophthalmologists to make informed decisions for patients with severe KC and assessments based on the percentage of corneal defects.

A real-time dual NURBS interpolator with optimised control of flexible acceleration and deceleration for five-axis CNC machining

The limited computing capacity makes it difficult to plan a suitable feedrate profile in real-time for high speed and high accuracy machining of five-axis parametric toolpaths. In this paper, a real-time interpolation algorithm with optimised control of flexible acceleration and deceleration (acc-dec) for the dual NURBS toolpath is proposed. The toolpath is marked as subsegments with similar geometric properties by introducing the five-axis curvature. Machine kinematic and toolpath geometry constraints are considered in the kinematic parameter constraint model. Initial feedrate profiles are solved in a dynamic 3D window which preserves the motion performance of machine tools to a great extent. Convolution is used to smooth the initial feedrate profile to achieve a higher order continuity over the global range. Feedrate fluctuations caused by imprecise parameter interpolation are eliminated through modifying each interpolation periods. Resampling adjusts the position of interpolation points and unify the interpolation periods. All operations mentioned are in series and real-time is strictly guaranteed. Effectiveness of the developed algorithm is validated in simulations and also experimentally on a Self-developed-NC controlled 5-axis machine tool.

Full-field three-dimensional system calibration for composite surfaces reconstruction

The accurate calibration of composite surface measurement systems for specular and diffused surface is of great importance in a number of industrial applications. This paper addresses the challenges in calibrating composite surface reconstruction by proposing a comprehensive full-field calibration method. The principal innovation is the construction of a comprehensive reference phase and the pixel-by-pixel calibration of system parameters within the same coordinate system. The details are as follows: (1) construct a complete reference phase for the composite surfaces through external parameter constraints phase fusion and interpolation; (2) calibrate the mapping relationship coefficients, compensate the accuracy degradation of the partial reflection. Experimental results validate the accuracy of the full-field calibration data, demonstrating the effectiveness and feasibility.

A collaborative navigation algorithm for UAV Ad Hoc network based on improved sequence quadratic programming and unscented Kalman filtering in GNSS denied area

In global navigation satellite system (GNSS) denied area, collaborative positioning precision is important for unmanned aerial vehicle (UAV) to perform collaborative tasks in Ad Hoc network. Continuous optimization of algorithm complexity and parameter setting has long been a focal point in the field of collaborative positioning research. An algorithm of UAVs collaborative positioning based on improved sequential quadratic programming (SQP) and unscented kalman filter (UKF) is proposed. By optimizing the parameter constraints of SQP, parameters are controlled within certain conditions. The convergence speed of SQP is improved, and more accurate filtering parameters are obtained. The improved SQP and UKF are combined to optimize the location data of UAVs, which improves the precision of collaborative positioning. The simulation results show that the positioning precision can be greatly enhanced by approximately 25% when using the proposed algorithm, as compared to the traditional algorithm. The influence of the collaborative UAV number also is simulated. The positioning performance improve slowly when more than five UAVs are used for collaborative positioning. Therefore, the positioning performance cannot be improved only by increasing the number of UAVs, but also by improving the performance of collaborative positioning algorithm.

Dose-Volume Constraints Parameters for Lung Tissue in Thoracic Radiotherapy Following Immune Checkpoint Inhibitor Treatment.

This study aims to identify risk factors associated with symptomatic radiation pneumonitis (RP, Grade ≥ 2) following immunotherapy preceding thoracic radiotherapy (ICI-TRT) and establish safe dose constraints. This retrospective study enrolled patients diagnosed with non-small-cell lung cancer (NSCLC) who underwent thoracic radiotherapy (TRT) following immune checkpoint inhibitors (ICIs) treatment. The primary endpoint was the occurrence of symptomatic RP (Grade ≥ 2), as defined by the Common Terminology Criteria for Adverse Events version 5.0. Clinical and lung dosimetric parameters were analyzed to determine their associations with symptomatic RP. Dosimetric parameters included mean lung dose (MLD) and the percentage of lung volume receiving ≥10 Gy (V10), ≥20 Gy (V20), ≥30 Gy (V30), and ≥40 Gy (V40). Receiver operating characteristic curves were used to predict the risk of developing symptomatic RP to establish optimal threshold values for each dosimetric predictor. Among the 118 patients included, the incidence of symptomatic RP was 25.4%. Tumor locations, intervals between immunotherapy and radiotherapy, and MLD, V10, V20, V30, and V40 were identified as independent risk factors for symptomatic RP. The area under the curve (AUC) values for MLD, V10, V20, V30, and V40 were 0.788 (95% confidence interval [CI] 0.704-0.873), 0.789 (95% CI 0.705-0.874), 0.791 (95% CI 0.706-0.876), 0.784 (95% CI 0.697-0.871), and 0.749 (95% CI 0.656-0.842), respectively. The optimal threshold values for MLD, V10, V20, V30, and V40 were 9.7 Gy, 26.3%, 15.9%, 13.3%, and 8.6%, respectively. These thresholds are lower than current guideline recommendations, and maintaining dosimetric parameters below these values resulted in a cumulative symptomatic RP incidence of <12%. The recommended dose thresholds for MLD, V10, V20, V30, and V40 are lower than the current guidelines, underscoring the importance of radiotherapy planning to minimize symptomatic RP occurrence in patients receiving ICI-TRT.

Modeling ground motions and crustal deformation from tsunami earthquakes: Rupture parameter constraints from the 2010 Mentawai event

Modeling ground motions and crustal deformation from tsunami earthquakes: Rupture parameter constraints from the 2010 Mentawai event

Sequel to “Highly dispersive optical solitons with differential group delay for kerr law of self—phase modulation by sardar sub—equation approach”: non—local law of self—phase modulation

AbstractThe paper obtains highly dispersive optical solitons with nonlocal law of self—phase modulation with differential group delay. The Sardar sub equation approach is the integration algorithm that makes this retrieval possible. The parameter constraints that naturally emerge from the scheme are also enlisted. The current work is thus a sequel to the previous paper that is with Kerr law of self—phase modulation structure.

Detection of gamma-ray burst Amati relation based on Hubble data set and Pantheon+ samples

Using gamma-ray bursts as standard candles for cosmological parameter constraints rely on their empirical luminosity relations and low-redshift calibration. In this paper, we examine the Amati relation and its potential corrections based on the A118 sample of higher-quality gamma-ray bursts, using both Hubble data set and Pantheon+ samples as calibration samples in the redshift range of z<1.965\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$z<1.965$$\\end{document}. In calibrating gamma-ray bursts using these two datasets, we employ Gaussian processes to obtain corresponding Hubble diagrams to avoid the dependence on cosmological models in the calibration process. We first divided the low-redshift sample of GRBs into two bins and examined the Amati relation and its potential modifications. We found that under both calibrations, the Amati relation did not show evidence of redshift evolution (68%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} confidence level). For the other two Amati relations that include redshift evolution terms, the central values of the redshift evolution coefficients deviated from 0, but due to the limitations of the sample size and the increase in the number of parameters, most of the redshift evolution coefficients were not able to be excluded from 0 at the 1σ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sigma $$\\end{document} level. Therefore, to assess their situation across the entire redshift range, we employed MCMC to globally fit three types of Amati relations. By computing AIC and BIC, we found that for the GRB A118 sample, the standard Amati relation remains the most fitting empirical luminosity formula, and no potential redshift evolution trend was observed for two different low-redshift calibrating sources.

Are light curve classification metrics good proxies for SN Ia cosmological constraining power?

When selecting a lc classifier for use as part of a photometric supernova Ia (SN Ia) cosmological analysis, it is common to make decisions based on metrics of classification performance, such as the contamination within the photometrically classified SN Ia sample, rather than a measure of cosmological constraining power. If the former is an appropriate proxy for the latter, this practice would save those designing an analysis pipeline from eliminate the computational expense of a full cosmology forecast in the analysis pipeline design process This study tests the assumption that lc classification metrics are an appropriate proxy for cosmology metrics. We emulated photometric SN Ia cosmology lc samples with controlled contamination rates of individual contaminant classes and evaluated each of them under a set of classification metrics. We then derived cosmological parameter constraints from all samples under two common analysis approaches and quantified the impact of contamination by each contaminant class on the resulting cosmological parameter estimates. We observe that cosmology metrics are sensitive to both the contamination rate and the class of the contaminating population, whereas the classification metrics are shown to be insensitive to the latter. Based on these findings, we discourage any exclusive reliance on classification-based metrics for analysis design decisions, which (counterintuitively) include but are not limited to the classifier choice. Instead, we recommend optimising science analysis pipeline design choices using a metric of the information gained about the physical parameters of interest.

Solitons in magneto-optic waveguides with generalized Kudryashov’s form of self-phase modulation structure

AbstractThe current paper recovers soliton solutions in magneto-optic waveguides having generalized form of Kudryashov’s self-phase modulation structure. The retrieval of soliton solutions is achieved by the well-known and primitive $$G^{\prime }/G$$ G ′ / G -expansion scheme. The intermediary functions that made this retrieval possible are Jacobi’s elliptic functions and Weierstrass’ elliptic functions. The parameter constraints for the solitons to exist are also presented.