Miracle-dz/UniFAR-FTUs huggingface dataset:
Altimetry‐Derived Gravity Gradients Using Spectral Method and Their Performance in Bathymetry Inversion Using Back‐Propagation Neural Network

Variations in bathymetry produce gravity gradients; therefore, gravity gradients should be suitable for inverting bathymetry. However, classical bathymetry inversion methods often use gravity anomalies. Studies wherein gravity gradients are employed always use only vertical gravity gradients, Tzz ${T}_{zz}$ ; however, the remaining five gravity gradients also contain bathymetric information. This study presents a spectral method of inverting gravity gradients from altimetry‐derived deflection of the vertical. The accuracy of derived gravity gradients is first evaluated by Laplace's equation. Results show that, except the Arctic region, the mean and standard deviation (STD) of the Laplace operator are, respectively, less than 0.001 and 0.06 E in the Atlantic, Indian and Pacific oceans. Computed Tzz ${T}_{zz}$ was compared with Tzz ${T}_{zz}$ from Scripps Institution of Oceanography. The differences have means and STDs smaller than 0.06 and 6.7 E, respectively, in all study areas, except the Arctic which registered an STD of 13.81 E. All six tensors were then fed into a back‐propagation neural network to predict bathymetries of each study area. The resultant bathymetries compare well with reference models from ship‐borne depths, SRTM15+V2 and GEBCO_2021. Relative to ship‐borne depths, the Atlantic, Pacific, Indian and Arctic study areas yielded mean errors, error STDs and correlation coefficients of 5.40, 3.28, 0.92, 3.07 m; 110.03, 76.23, 104.58, 132.41 m; and 0.9861, 0.9615, 0.9760, 0.9803; respectively. The bathymetries were inverted again, however, with each gravity gradient component omitted. Analysis showed that Tzz ${T}_{zz}$ was not the most influential component across the study regions; rather, each gravity gradient component can significantly contribute to bathymetry inversion.
Deep Reinforcement Learning for the Co-Optimization of Vehicular Flow Direction Design and Signal Control Policy for a Road Network

Reinforcement Learning (RL) is a popular approach for deciding on an optimum traffic signal control policy to alleviate congestion in a road network. However, the traffic signal control policy can also be optimized in conjunction with the design of vehicular flow directions to further improve traffic performance. The design of vehicular flow directions refers to the right of way or directional restriction imposed in a road network. Here, a new RL-based technique is presented for co-optimization of the design of vehicular flow directions and control policy for traffic signals. This technique consists of a two-step iterative process, wherein a set of vehicular flow directions for a road network is generated, then a RL-based approach is used to train the traffic signal control policy over the given set of vehicular flow directions. Following the proposed technique, the vehicular flow directions with poor traffic performance are iteratively eliminated, while new vehicular flow directions are generated to achieve better traffic performance and realize convergence to a maximum possible expected traffic performance. The proposed RL-based technique is evaluated by using two examples under rush hour and non-rush hour traffic conditions. It is found that, compared to a RL-based approach in which only traffic signal control policy is considered, the proposed approach can be used to obtain a better traffic performance in terms of vehicular queue length and throughput.
Stably Stratified Atmospheric Boundary Layers

Atmospheric boundary layers with weak stratification are relatively well described by similarity theory and numerical models for stationary horizontally homogeneous conditions. With common strong stratification, similarity theory becomes unreliable. The turbulence structure and interactions with the mean flow and small-scale nonturbulent motions assume a variety of scenarios. The turbulence is intermittent and may no longer fully satisfy the usual conditions for the definition of turbulence. Nonturbulent motions include wave-like motions and solitary modes, two-dimensional vortical modes, microfronts, intermittent drainage flows, and a host of more complex structures. The main source of turbulence may not be at the surface, but rather may result from shear above the surface inversion. The turbulence is typically not in equilibrium with the nonturbulent motions, sometimes preventing the formation of an inertial subrange. New observational and analysis techniques are expected to advance our understanding of.
MWI Representation of the Number of Curve-Crossings by a Differentiable Gaussian Process, with Applications

Let X=(X t , t≥0) be a stationary Gaussian process with zero mean, continuous spectral distribution and twice-differentiable correlation function. An explicit representation is given for the number N ψ (T) of crossings of a C 1 curve ψ by X on the bounded interval [0, T], in a multiple Wiener-Ito integral expansion. This continues work of the author in which the result was given for ψ≡0. The representation is applied to prove new central and noncentral limit theorems for numbers of crossings of constant levels, and some consequences for asymptotic variances are given in fixed-spectrum settings
Sensor Fusion with Asynchronous Decentralized Processing for 3D Target Tracking with a Wireless Camera Network

We present a method to acquire 3D position measurements for decentralized target tracking with an asynchronous camera network. Cameras with known poses have fields of view with overlapping projections on the ground and 3D volumes above a reference ground plane. The purpose is to track targets in 3D space without constraining motion to a reference ground plane. Cameras exchange line-of-sight vectors and respective time tags asynchronously. From stereoscopy, we obtain the fused 3D measurement at the local frame capture instant. We use local decentralized Kalman information filtering and particle filtering for target state estimation to test our approach with only local estimation. Monte Carlo simulation includes communication losses due to frame processing delays. We measure performance with the average root mean square error of 3D position estimates projected on the image planes of the cameras. We then compare only local estimation to exchanging additional asynchronous communications using the Batch Asynchronous Filter and the Sequential Asynchronous Particle Filter for further fusion of information pairs’ estimates and fused 3D position measurements, respectively. Similar performance occurs in spite of the additional communication load relative to our local estimation approach, which exchanges just line-of-sight vectors.
Nonlinear vibration characteristics of a flexible blade with friction damping due to tip-rub

An approximate approach is proposed in this paper for analyzing the two-dimensional friction contact problem so as to compute the dynamic response of a structure constrained by friction interfaces due to tip-rub. The dynamical equation of motion for a rotational cantilever blade in a centrifugal fo rce field is established. Flow-induced distributed periodi c forces and the internal material damping in the blade are accounted for in the governing equation of motion. The Galerkin method is employed to obtain a three-degree-of-freedom oscillator with frict ion damping due to tip-rub. The combined motion of impact and friction due to tip-rub produced a piecewise linear vibration which is actually nonlinear. Thus, a complete vibration cycle is divided into successive intervals. The system possesses linear vibrati on characteristic during each of these intervals, which can be determined using analytical solution forms. Numerical simulation shows that the parameters such as gap of the tip and the rotational speed of the blades have significant effects on the dynamical respons es of the system. Finally, the nonlinear vibration characte ristics of the blade are investigated in terms of the Poincare graph, and the frequency spectrum of the responses and the amplitude-frequency curves.
Comparison of Chayote (Sechium edule (Jacq.) Sw.) Accessions from Mexico, Japan, and Myanmar Using Reproductive Characters and Microsatellite Markers

Promoting neglected and underutilized crop species is a possible solution to deal with the complex challenges of global food security. Chayote is a Neglected and Underutilized Cucurbit Species (NUCuS), which is recognized as a fruit vegetable in Latin America and is widely grown in Asia and Africa. However, basic biological knowledge about the crop is insufficient in scientific sources, especially outside of its center of origin. In this study, limited observations on reproductive characters were conducted, differentiating accessions from Mexico, Japan, and Myanmar. Cytological evaluation among Mexican and Japanese accessions showed that the relative nuclear DNA content is 1.55 ± 0.05 pg, the estimated genome size is 1511 at 2C/Mbp, and the observed mitotic chromosomal number is 2n = 28. The genetic diversity of 21 chayote accessions was also examined using six microsatellite markers. A global low genetic heterozygosity (Ho = 0.286 and He = 0.408) and three genetic groups were detected. The results established the basis to provide insights into chayote arrival history in Asia by looking at the crop’s reproductive morphology, cytology, and genetic diversity status outside its origin center. This could help in developing sustainable utilization and conservation programs for chayote.
Pepper Mild Mottle Virus: An Infectious Pathogen in Pepper Production and a Potential Indicator of Domestic Water Quality

Pepper (Capsicum spp.; Family: Solanaceae; 2n = 24) is an important crop cultivated worldwide for the consumption of its fresh and dried processed fruits. Pepper fruits are used as raw materials in a wide variety of industrial processes. As a multipurpose vegetable crop, there is a need to increase the yield. However, yield productivity of pepper is severely constrained by infectious plant pathogens, including viruses, bacteria, fungi, and oomycetes. The pepper mild mottle virus (PMMoV) is currently one of the most damaging pathogens associated with yield losses in pepper production worldwide. In addition to impacts on pepper productivity, PMMoV has been detected in domestic and aquatic water resources, as well as in the excreta of animals, including humans. Therefore, PMMoV has been suggested as a potential indicator of domestic water quality. These findings present additional concerns and trigger the need to control the infectious pathogen in crop production. This review provides an overview of the distribution, economic impacts, management, and genome sequence variation of some isolates of PMMoV. We also describe genetic resources available for crop breeding against PMMoV.
ISAR image reconstruction and autofocusing procedure over phase modulated signals

A model of inverse synthetic aperture radar (ISAR) signal with Barker's code phase modulation (PCM) is developed. To cope with the image blurring due to the range migration of object's point scatterers an autofocusing technique for ISAR signal processing is performed. The correlation algorithm for range compression and spectral fast Fourier transform (FFT) for azimuth compression are exploited. The presented image reconstruction procedures are invariant to the object's trajectory parameters. Numerical experiment over the simulated ISAR data is accomplished.
On the Polar Bias in Ice Core 10Be Data

Cosmogenic radionuclide records from polar ice cores provide unique insights into past cosmic ray flux variations. They allow reconstructions of past solar activity, space weather, and geomagnetic field changes, and provide insights into past carbon cycle changes. However, all these applications rely on the proportionality of the ice core radionuclide records to the global mean production rate changes. This premise has been long debated from a model and data‐perspective. Here, we address this issue through atmospheric mixing model experiments and comparison to independent data. We find that all mixing scenarios, which do not assume complete tropospheric mixing, result in a polar bias. This bias is more prominent for geomagnetic field changes than solar modulation changes. The most likely scenario, supported by independent geomagnetic field records and marine 10Be during the Laschamps geomagnetic field minimum, results in a dampening of geomagnetic field induced changes by 23%–37% and an enhancement of solar‐induced changes by 7%–8%. During the Holocene, we do not find conclusive evidence for a polar bias. We propose a correction function that allows deconvolving the glacial ice core record in order to restore proportionality to the global mean signal.
3-D analysis of induction motor with skewed slots using regular coupling mesh

A new method using a regular coupling mesh is proposed for problems involving movement in the FEM analysis of electric machines using edge elements. The fixed and moving regions are coupled through the mesh. The approach allows simple and independent generation of rotor and stator meshes. An induction motor with skewed slots is analyzed in 3-D by this method and the results are compared to measurements. The authors investigated the effects of the skewed slots and the end-rings on the characteristics of the induction motor, which are difficult to analyze in 2-D analysis. The good agreements between the numerical results and experimental data validate the applicability of the proposed method.
A robust transfer matrix formulation for the ultrasonic response of multilayered absorbing media

An improved version of the transfer matrix approach is presented for ultrasonic wave interaction in multilayered media. Generalized expressions are obtained for reflection and transmission coefficients in either fluid or solid half‐space and problems associated with numerical stability are solved efficiently. The formulation is applicable to longitudinal and shear input waves alike, at arbitrary incidence angles and for any sequence of solid or fluid layers. Also, allowance is made for viscoelastic behavior by means of relaxation functions in the Laplace transform domain. Finally, the response to arbitrary incident pulse shapes and beam profiles is described through application of two‐dimensional numerical Laplace inversion.
Eddy currents modeling in solid iron by using analytic elements

The numerical analysis of problems involving eddy currents developed in thin skin effect depths, based on the classical finite element method, is extremely laborious and time consuming. Furthermore, the related geometries are not, usually, simple enough to permit an analytical solution. The present work is based on a new type of element enabling efficient modelling in such cases. It combines the increased accuracy and speed of analytical solutions for large subdomains, a reduced number of unknowns and the advantages of functional minimization procedures. An example concerning eddy currents calculation in a solid iron salient part is used to test the method's performance. >
Polyelectrolyte model of DNA

The present state of the theory of strongly charged polyelectrolytes of the DNA type is reviewed. An infinitely long, uniformly charged cylinder immersed in a dielectric continuum is adopted as a model of DNA. Small mobile ions are treated as impermeable spheres. A comparison of the results of rigorous and approximate theoretical approaches to the description of this model shows that the self-consistent-field method, i.e., the Poisson-Boltzmann equation, is a reliable basis for deriving quantitative results. The theory of polyelectrolytes based on a solution of the nonlinear Poisson-Boltzmann equation is used to analyze the role played by electrostatic interactions in conformational changes in DNA. Transitions of two types are considered: a helix-coil transition and a transition between the ordinary right-hand-helix DNA (the B form) and the recently discovered left-hand-helix (the Z form). In the latter case the theory predicts a nonmonotonic behavior of the difference between the free energies of these conformations as a function of the salt concentration. It also predicts the existence of a critical point of a B-Z equilibrium for ionic strengths in the physiological region.
Fundamental parameters of the moderately young open clusters NGC 5999, NGC 6031, Ruprecht 115 and Ruprecht 120

We present CCD BVI Johnson--Cousins photometry for the southern open clusters NGC 5999, NGC 6031, Ruprecht 115 and Ruprecht 120. The sample consists of about 1160 stars reaching down to V∼ 19 mag. From the analysis of the colour--magnitude diagrams, we confirm the reality of the clusters and derive their fundamental parameters (reddening, distance and age). We also present integrated spectra for NGC 6031, Ruprecht 115 and Ruprecht 120, covering a range from 3500 to 9200 A. From the equivalent widths of Balmer and infrared Ca ii triplet lines, as well as from a comparison of the obtained spectra with those of template clusters, we derive reddening, age and metallicity. The photometric and spectroscopic results allow us to conclude that the four clusters are moderately young (age ∼100--500 Myr) and are located approximately towards the Galactic Centre at ∼ 2.3 kpc from the Sun. NGC 6031 and Ruprecht 120 have nearly solar metal content, while Ruprecht 115 appears to be slightly metal-rich.
Visual Search Processes Used in Map Reading

This paper discusses visual search theories that explain how humans search for objects on maps. A mapreading experiment considered variations in visual search processes ref ated to searching for targets with unique features and mrgets that share features with other objects. Experimental objects differing in colour, shape, size, and orientation were constructed. The importance of these characteristics was evaluated, as was the effect of the location of the target on the map. The time needed to find a target in a display and the proportion of incorrect decisions were measures of efficiency in spatialsearch studies. The most efficient spatial searches occur when targeu 'pop out' of the map. These searches use parallel processes and are indicated bv reaction times being independent of the number of symbols on the map. 'Pop-out' effecu occur when targets have some unique charact~ristics that distinguish them from other symbols. Results indicated that 'pop-out' effects could he produced by colour differences be.
The Role of Microsphere Structures in Bottom-Up Bone Tissue Engineering

Bone defects have caused immense healthcare concerns and economic burdens throughout the world. Traditional autologous allogeneic bone grafts have many drawbacks, so the emergence of bone tissue engineering brings new hope. Bone tissue engineering is an interdisciplinary biomedical engineering method that involves scaffold materials, seed cells, and “growth factors”. However, the traditional construction approach is not flexible and is unable to adapt to the specific shape of the defect, causing the cells inside the bone to be unable to receive adequate nourishment. Therefore, a simple but effective solution using the “bottom-up” method is proposed. Microspheres are structures with diameters ranging from 1 to 1000 µm that can be used as supports for cell growth, either in the form of a scaffold or in the form of a drug delivery system. Herein, we address a variety of strategies for the production of microspheres, the classification of raw materials, and drug loading, as well as analyze new strategies for the use of microspheres in bone tissue engineering. We also consider new perspectives and possible directions for future development.
Principles Of The Radiosity Method For Canopy Reflectance Modeling

The radiosity method is introduced to plant canopy reflectance modeling. We review the physics principles of the radiosity method which originates in thermal radiative transfer analyses when hot and cold surfaces are considered within a given enclosure. The radiosity equation, which is an energy balance equation for discrete surfaces, is described and contrasted with the radiative transfer equation, which is a volumetric energy balance equation. Comparing the strengths and weaknesses of the radiosity method and the radiative transfer method, we conclude that both methods are complementary to each other. Results of sample calculations are given for canopy models with up to 20,000 discrete leaves. 16 refs.
A Novel Structural Damage Detection Method via Multisensor Spatial–Temporal Graph-Based Features and Deep Graph Convolutional Network

Structural damage detection plays an important part in structural health monitoring for engineering structures. However, monitored signals are easily polluted by noise and the damaged data are difficult to obtain. In this work, a novel structural damage detection approach using multisensor spatial–temporal graph-based features and deep graph convolutional networks (DGCNs) is presented. The spatial–temporal graph is constructed by the graph theory based on continuous wavelet transform (CWT) of vibration signals. Then, the multisensor spatial–temporal graph-based feature is extracted based on the Laplacian matrix derived from the spatial–temporal graph of the multisensor data. To overcome the limitation of small data size which obstructed the use of the artificial neural network and convolutional neural network, a DGCN is utilized to classify the damage type of the monitored structure. The extracted multisensor spatial–temporal graph-based feature vector is used to represent the node of the global graph as the input of the DGCN. The node with the same condition of the structure can be classified by using the well-trained DGCN. Experiments of the International Association for Structural Control (IASC)-American Society of Civil Engineers (ASCE) SHM benchmark structure and Qatar steel frame structure in the laboratory are performed to verify the effectiveness of the proposed approach. The experimental results show that the DGCN method can be used to detect structural damage by learning from the constructed global graphs. Comparative experiments demonstrate that the proposed approach performs better than the conventional approach, especially for the limited dataset and noise-polluted case.
Robust H∞ control of uncertain linear impulsive stochastic systems

This paper develops robust stability theorems and robust H∞ control theory for uncertain impulsive stochastic systems. The parametric uncertainties are assumed to be time varying and norm bounded. Impulsive stochastic systems can be divided into three cases, namely, the systems with stable/stabilizable continuous‐time stochastic dynamics and unstable/unstabilizable discrete‐time dynamics, the systems with unstable/unstabilizable continuous dynamics and stable/stabilizable discrete‐time dynamics, and the systems in which both the continuous‐time stochastic dynamics and the discrete‐time dynamics are stable/stabilizable. Sufficient conditions for robust exponential stability and robust stabilization for uncertain impulsive stochastic systems are derived in terms of an average dwell‐time condition. Then, a linear matrix inequality‐based approach to the design of a robust H∞ controller for each system is presented. Finally, the numerical examples are provided to demonstrate the effectiveness of the proposed approach. Copyright © 2007 John Wiley & Sons, Ltd.