Original Coordinates Research Articles

Robust unsupervised 5D seismic data reconstruction on regular and irregular grids

Seismic data reconstruction has become a central focus in seismic data processing, addressing challenges posed by sparse sampling due to physical and budgetary constraints. The advent of 5D acquisition methodologies marks a significant advancement in the quality and completeness of seismic data sets. Most traditional 5D reconstruction methods commonly use the fast Fourier transform (FFT), requiring regular grids and preliminary 4D binning before 5D interpolation. Discrete Fourier transform and nonequidistant FFT can honor the original irregular coordinates. However, when using exact locations, these methods become computationally expensive. We introduce an unsupervised deep-learning methodology to learn a continuous function across the sampling points in seismic data, facilitating reconstruction on regular and irregular grids. The network comprises a multilayer perceptron with linear layers and element-wise periodic activation functions. It excels at mapping the input coordinates to the corresponding seismic data amplitudes without relying on external training sets. The network’s intrinsic low-frequency bias is crucial in prioritizing acquiring self-similar features over high-frequency and incoherent ones during training. This characteristic mitigates incoherent noise in seismic data, such as random and erratic components. To assess the robustness of the unsupervised reconstruction technique, we conduct comprehensive evaluations using synthetic data examples sampled regularly and irregularly, as well as field-data examples with and without binning. The findings demonstrate the efficacy of our deep-learning framework in achieving resilient and accurate seismic data reconstruction across diverse sampling scenarios.

Rogue-wave structures for a generalized (3+1)-dimensional nonlinear wave equation in liquid with gas bubbles

This study explores the behavior of higher-order rogue waves within a (3+1)-dimensional generalized nonlinear wave equation in liquid-containing gas bubbles. It creates the investigated equation’s Hirota D-operator bilinear form. We employ a generalized formula with real parameters to obtain the rogue waves up to the third order using the direct symbolic technique. The analysis reveals that the second and third-order rogue solutions produce two and three-waves, respectively. To gain deeper insights, we use the Cole-Hopf transformation on the transformed variables ξ and η to produce a bilinear equation. Using the system software Mathematica, the dynamic analysis presents the graphics for the obtained solutions in transformed ξ, η, and original spatial-temporal coordinates x, y, z, t. These visualizations reveal rogue waves’ intricate structure and evolution, capturing their localized interactions and significant presence within nonlinear systems. We demonstrate that rogue waves, characterized by their substantial height and sudden appearance, are prevalent in various nonlinear events. The equation examined in this study offers valuable insights into the evolution of longer waves with smaller amplitudes, which is particularly relevant in fields such as fluid dynamics, dispersive media, and plasmas. The implications of this research extend across multiple scientific domains, including fiber optics, oceanography, dusty plasma, and nonlinear systems, where understanding the behavior of rogue waves is crucial for both theoretical and practical applications.

Using YOLOv5, SAHI, and GIS with Drone Mapping to Detect Giant Clams on the Great Barrier Reef

Despite the ecological importance of giant clams (Tridacninae), their effective management and conservation is challenging due to their widespread distribution and labour-intensive monitoring methods. In this study, we present an alternative approach to detecting and mapping clam density at Pioneer Bay on Goolboddi (Orpheus) Island on the Great Barrier Reef using drone data with a combination of deep learning tools and a geographic information system (GIS). We trained and evaluated 11 models using YOLOv5 (You Only Look Once, version 5) with varying numbers of input image tiles and augmentations (mean average precision—mAP: 63–83%). We incorporated the Slicing Aided Hyper Inference (SAHI) library to detect clams across orthomosaics, eliminating duplicate counts of clams straddling multiple tiles, and further, applied our models in three other geographic locations on the Great Barrier Reef, demonstrating transferability. Finally, by linking detections with their original geographic coordinates, we illustrate the workflow required to quantify animal densities, mapping up to seven clams per square meter in Pioneer Bay. Our workflow brings together several otherwise disparate steps to create an end-to-end approach for detecting and mapping animals with aerial drones. This provides ecologists and conservationists with actionable and clear quantitative and visual insights from drone mapping data.

IntrinsicNGP: Intrinsic Coordinate Based Hash Encoding for Human NeRF.

Recently, many works have been proposed to use the neural radiance field for novel view synthesis of human performers. However, most of these methods require hours of training, making them difficult for practical use. To address this challenging problem, we propose IntrinsicNGP, which can be trained from scratch and achieve high-fidelity results in a few minutes with videos of a human performer. To achieve this goal, we introduce a continuous and optimizable intrinsic coordinate instead of the original explicit euclidean coordinate in the hash encoding module of InstantNGP. With this novel intrinsic coordinate, IntrinsicNGP can aggregate interframe information for dynamic objects using proxy geometry shapes. Moreover, the results trained with the given rough geometry shapes can be further refined with an optimizable offset field based on the intrinsic coordinate. Extensive experimental results on several datasets demonstrate the effectiveness and efficiency of IntrinsicNGP. We also illustrate the ability of our approach to edit the shape of reconstructed objects.

An energy consumption field model considering motion position errors for energy efficient machining on CNC machines:CNC programming perspective

Motion position errors, which are caused by factors such as machine tool assembly accuracy and thermal effects, often result in deviations in both machining energy consumption and precision, compared to what is expected. Furthermore, the degree of deviations dynamically varies with the machining schemes. These issues hinder the implementation of high-quality energy-saving machining. To address this challenge, an energy consumption field model is proposed, reflecting the impact of motion position errors on energy consumption and precision variations in different machining scenarios. Firstly, by analysing the conversion process from process plans to programming instructions, a dynamic cascading mechanism is revealed, driven by motion position errors that impact tool cutting trajectory offset, machining energy consumption and precision deviation. Subsequently, a dynamic quantification model for the cutting trajectory offset at the programming origin is established by correlating static geometric errors and dynamic spindle rotation errors with the programming origin coordinates. Finally, a transformation function is established by using the cutting trajectory offset as an intermediate variable to correlate motion position error, machining energy consumption and precision deviation. A spatial energy consumption field model is developed. Experimental results indicate that, while meeting precision constraints in the XYZ directions, a 10.96% reduction in energy consumption is achieved through the correction of programming origin coordinates.

Challenges in Geocoding: An Analysis of R Packages and Web Scraping Approaches

Georeferenced data are crucial for addressing societal spatial challenges, as most corporate and governmental information is location-compatible. However, many open-source solutions lack automation in geocoding while ensuring quality. This study evaluates the functionalities of various R packages and their integration with external APIs for converting postal addresses into geographic coordinates. Among the fifteen R methods/packages reviewed, tidygeocoder stands out for its versatility, though discrepancies in processing times and missing values vary by provider. The accuracy was assessed by proximity to original dataset coordinates (Madrid street map) using a sample of 15,000 addresses. The results indicate significant variability in performance: MapQuest was the fastest, ArcGIS the most accurate, and Nominatim had the highest number of missing values. To address these issues, an alternative web scraping methodology is proposed, substantially reducing the error rates and missing values, but raising potential legal concerns. This comparative analysis highlights the strengths and limitations of different geocoding tools, facilitating better integration of geographic information into datasets for researchers and social agents.

Enhanced Security and Privacy via Fragmented Federated Learning.

In federated learning (FL), a set of participants share updates computed on their local data with an aggregator server that combines updates into a global model. However, reconciling accuracy with privacy and security is a challenge to FL. On the one hand, good updates sent by honest participants may reveal their private local information, whereas poisoned updates sent by malicious participants may compromise the model's availability and/or integrity. On the other hand, enhancing privacy via update distortion damages accuracy, whereas doing so via update aggregation damages security because it does not allow the server to filter out individual poisoned updates. To tackle the accuracy-privacy-security conflict, we propose fragmented FL (FFL), in which participants randomly exchange and mix fragments of their updates before sending them to the server. To achieve privacy, we design a lightweight protocol that allows participants to privately exchange and mix encrypted fragments of their updates so that the server can neither obtain individual updates nor link them to their originators. To achieve security, we design a reputation-based defense tailored for FFL that builds trust in participants and their mixed updates based on the quality of the fragments they exchange and the mixed updates they send. Since the exchanged fragments' parameters keep their original coordinates and attackers can be neutralized, the server can correctly reconstruct a global model from the received mixed updates without accuracy loss. Experiments on four real data sets show that FFL can prevent semi-honest servers from mounting privacy attacks, can effectively counter-poisoning attacks, and can keep the accuracy of the global model.

Adaptive module and accurate heatmap translator for multi-person human pose estimation

Human pose estimation is an important task in computer vision and an essential step for computers to understand human motion and behavior. However, accurate localization of keypoints for small individuals in multi-person pictures is often ignored by current methods, resulting in limited improvements in accuracy. In addition, the current mainstream methods of translating a predicted heatmap into a coordinate in the original image space is too coarse. This coarseness also affects the localization of keypoints. To address these challenges, we propose an adaptive human body size module(AHBZM), spatial selective attention module(SSAM) and more accurate heatmap translator(MAHT) for human pose estimation. The proposed AHBZM utilizes trainable parameters to select a more appropriate multi-scale fusion method to further refine the localization of keypoints for different body sizes. To further improve keypoints localization, SSAM is used to capture target spatial information during feature fusion. The proposed MAHT will more accurately add the pixel offsets when translating heatmap coordinates into original image coordinates, while more closely associating the global maximum value in the heatmap with the surrounding local maximum values. The experimental results show that the proposed method has achieved good results on the two benchmark datasets of COCO and MPII. Our code is available at: https://github.com/illusory2333/Adaptive-module-and-heatmap-translator.

A Charged Particle with Anisotropic Mass in a Perpendicular Magnetic Field–Landau Gauge

The loss of any symmetry in a system leads to quantum problems that are typically very difficult to solve. Such a situation arises for particles with anisotropic mass, like electrons in various semiconductor host materials, where it is known that they may have an anisotropic effective mass. In this work, we consider the quantum problem of a spinless charged particle with anisotropic mass in two dimensions and study the resulting energy and eigenstate spectrum in a uniform constant perpendicular magnetic field when a Landau gauge is adopted. The exact analytic solution to the problem is obtained for arbitrary values of the anisotropic mass using a mathematical technique that relies on the scaling of the original coordinates. The characteristic features of the energy spectrum and corresponding eigenstate wave functions are analyzed. The results of this study are expected to be of interest to quantum Hall effect theory.

Development of Higher Vocational Education in Shuangcheng Economic Circle of Chengdu-Chongqing area Evaluation and Research on Coupling and Coordination with Economic Growth

Objective: The Central Committee's meeting on the Chengdu-Chongqing economic plan highlights the role of higher vocational education in fostering technological progress and economic growth through skilled talent cultivation, aligning with the region's development opportunities. Methods: This paper uses entropy method and coupling coordination degree model to conduct empirical research on the collaborative development of higher vocational education and regional economy in Chengdu-Chongqing region from 2011 to 2020. Conclusions: 1) For Chengdu-Chongqing area, the coupling coordination degree has gradually changed from the original low level coupling coordination type to the good coordination degree.2) In order to maintain the balanced development of higher vocational education with economic and social development, our country must accelerate the transformation of government functions, promote the reform of vocational education, and promote the coordinated development of higher vocational education and regional economy.

Monte Carlo simulation study of an in vivo four-dimensional tracking system with a diverging collimator for monitoring radiation source (Ir-192) location during brachytherapy: proof of concept and feasibility.

Introduction: The aim of this study was to demonstrate the potential of an in vivo four-dimensional (4D) tracking system to accurately localize the radiation source, Iridium-192 (Ir-192) in high-dose rate brachytherapy. Methods: To achieve time-dependent 3D positioning of the Ir-192 source, we devised a 4D tracking system employing multiple compact detectors. During the system's design phase, we conducted comprehensive optimization and analytical evaluations of the diverging collimator employed for detection purposes. Subsequently, we executed 3D reconstruction and positioning procedures based on the 2D images obtained by six detectors, each equipped with an optimized diverging collimator. All simulations for designing and evaluating the 4D tracking system were performed using the open-source GATE (v9.1) Monte Carlo platform based on the GEANT4 (v10.7) toolkit. In addition, to evaluate the accuracy of the proposed 4D tracking system, we conducted simulations and 3D positioning using a solid phantom and patient data. Finally, the error between the reconstructed position coordinates determined by the tracking system and the original coordinates of the Ir-192 radiation source was analyzed. Results: The parameters for the optimized diverging collimator were a septal thickness of 0.3mm and a collimator height of 30mm. A tracking system comprising 6 compact detectors was designed and implemented utilizing this collimator. Analysis of the accuracy of the proposed Ir-192 source tracking system found that the average of the absolute values of the error between the 3D reconstructed and original positions for the simulation with the solid phantom were 0.440mm for the x coordinate, 0.423mm for the y coordinate, and 0.764mm for the z coordinate, and the average Euclidean distance was 1.146mm. Finally, in a simulation based on data from a patient who underwent brachytherapy, the average Euclidean distance between the original and reconstructed source position was 0.586mm. Discussion: These results indicated that the newly designed in vivo 4D tracking system for monitoring the Ir-192 source during brachytherapy could determine the 3D position of the radiation source in real time during treatment. We conclude that the proposed positioning system has the potential to make brachytherapy more accurate and reliable.

Hoverflies of the Timon-David collection (Diptera, Syrphidae).

Hoverflies are among the most important insect pollinators and there is documented evidence of a recent decline in their populations. To trace the past distributions of hoverfly species, verified records of historical collections are essential. Here, we provide data on 1071 specimens of hoverflies collected or received by Jean Timon-David and hosted at the Marseille Natural History Museum, France. Most of the specimens were collected by Timon-David himself and come from south-eastern France, mainly from the Departments of Bouches-du-Rhône, Var and Hautes-Alpes. Most of these specimens were checked for the accuracy of their identification according to the latest identification keys. This resulted in 85 additions to the known fauna of the French Departments, mostly for Var and Bouches-du-Rhône. The taxonomy of all specimens was checked against the latest available checklists and updated names added whenever necessary. Specimens received from entomologists working in other continents may also be valuable, as these are historic testimonies of the fauna of their own respective regions of origin and may, therefore, also be used as reference material. One paratype specimen from Australia is present in the collection. The holotype of Cheilosia vangaveri Timon-David, 1937 is absent from the collection and should be considered as lost. All but two of the specimens with locality labels had their geographical coordinates of origin added in the dataset.

Spatial–temporal feature-based End-to-end Fourier network for 3D sign language recognition

Most dynamic sign word misclassifications are caused by redundant spatial–temporal (SPT) feature pruning that lacks language semantic and temporal dependencies. SPT feature recognition is one of the important aspects for the evaluation of the misclassification of dynamic sign words. The redundant pruning of SPT feature space influences the language model of sign confusion, model complexity, and SPT feature similarity. The purpose of this article is to develop a new multi-scale SPT feature-based dynamic sign word recognition approach via a low-cost feature selection method (FS) and End-to-end Fourier convolution neural network (EFCNN). Instead of a sensor fusion technique for obtaining frame position alignment, in the EFCNN, new 3D frame position and coordinates are determined using a pixel weighting and alignment function of the first and succeeding 25 spatial intensities of the 3D video changes across hand motion. The new spatial weight and the original spatial coordinates are fused and truncated in the Fourier domain. We generate the temporal dependence of the fused features. A feature selection known as the FS-EFCNN is introduced to select compact features with a preserved language meaning. Five state-of-the-art feature selection methods, namely Infinite FS (InFS), Relief FS, Fisher, MIM, ILFS, and ensemble FS-EFCNN were deployed to guide and optimize the learning performance of EFCNN. The experimental result analysis highlighted the improved results of the FS-EFCNN method with the best accuracy of 99.86%, 99.89%, and 90.69% on 3D American Sign Language, British Sign Language, and Greek Sign Language data sets, respectively.

Integer multiple quantum image scaling based on NEQR and bicubic interpolation

As a branch of quantum image processing, quantum image scaling has been widely studied. However, most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolation, the quantum version of bicubic interpolation has not yet been studied. In this work, we present the first quantum image scaling scheme for bicubic interpolation based on the novel enhanced quantum representation (NEQR). Our scheme can realize synchronous enlargement and reduction of the image with the size of 2 n × 2 n by integral multiple. Firstly, the image is represented by NEQR and the original image coordinates are obtained through multiple CNOT modules. Then, 16 neighborhood pixels are obtained by quantum operation circuits, and the corresponding weights of these pixels are calculated by quantum arithmetic modules. Finally, a quantum matrix operation, instead of a classical convolution operation, is used to realize the sum of convolution of these pixels. Through simulation experiments and complexity analysis, we demonstrate that our scheme achieves exponential speedup over the classical bicubic interpolation algorithm, and has better effect than the quantum version of bilinear interpolation.

Bleustein-Gulyaev waves in topological piezoelectric crystals

A topological insulator with piezoelectric properties is considered, and an action is proposed to find the equations of motion and the constitutive relations of the generalized coordinates of electrodynamic and elastic origin, paying special attention to the restructuring induced by the topological properties. The results are used to demonstrate that the electromechanical factor of the Bleustein-Gulyaev waves on the surface of a topological piezoelectric crystal of class C6v in contact with vacuum undergoes a second-order correction in the fine structure constant, associated with the topological properties.

CO<sub>2</sub>-mediated conversion of physical pressure into chemical pressure to realize lattice strain

<p>Lattice strains often lead to novel phenomena, and they are used in a variety of applications, such as thermoelectricity, ferroelectricity, ferromagnetic, skyrmion and superconductivity. In this paper, we briefly summarize the novel phenomena brought about by lattice strain. An efficient method to realize lattice strain using supercritical CO<sub>2</sub> (SC CO<sub>2</sub>) is proposed. When CO<sub>2</sub> molecules shuttle through the confined space of the crystal structure, it can generate huge energy subsequently. Specifically, CO<sub>2</sub> carries MPa-level external physical pressure inside the crystal structure, forming localized defects or phase transitions. This alters the original chemical coordination environment and generates internal chemical pressures up to the GPa level. The crystal is stripped from three-dimensional to two-dimensional under high pressure, and lattice strain is realized at the same time. This work will provide new insights into the realization of lattice strain and give valuable guidance to broaden its application.</p>

The nonlocal solvability conditions for a system with constant terms and coefficients of the variable t

We consider the Cauchy problem for a system of quasilinear differential equations with constantterms and coefficients of the variablet.We investigate the solvability of the Cauchy problem fora system of quasilinear differential equations with constant terms and coefficients of the variabletusing the additional argument method. A theorem on the existence and uniqueness of the localsolution of the Cauchy problem for a system of quasilinear differential equations with constantterms and coefficients of the variabletis formulated. We obtain sufficient conditions for theexistence and uniqueness of a nonlocal solution of the Cauchy problem in original coordinates fora system of quasilinear differential equations with constant terms and coefficients of the variablet.A theorem on the existence and uniqueness of the nonlocal solution of the Cauchy problem fora system of quasilinear differential equations with constant terms and coefficients of the variabletis formulated. A theorem on the existence and uniqueness of the nonlocal solution of the Cauchyproblem for a system of quasilinear differential equations with constant terms and coefficients ofthe variabletis proved. The proof of the nonlocal solvability of the Cauchy problem for a systemof quasilinear differential equations with constant terms and coefficients of the variabletrelies onglobal estimates.

A general expression for vibrational Hamiltonians expressed in oblique coordinates

We examine the properties of oblique coordinates. The coordinates, introduced by Zúñiga et al. [J. Phys. B: At., Mol. Opt. Phys. 52, 055101, (2019)], reduce vibrational mode-mixing and enhance the quality of vibrational assignments in quantum mechanical investigations of two-dimensional model Hamiltonians. Oblique coordinates are obtained by making non-orthogonal rotations of the original coordinates that convert the matrix representation of the quadratic Hamiltonian operator into a block-diagonal matrix where the blocks are distinguished by the total quanta of vibrational excitation. Using techniques for the polar decomposition of matrices, we present a scheme for finding these coordinates for systems of arbitrary dimensions. Several molecular examples are presented that highlight the advantages of these coordinates.

Development of environmentally-friendly modified bioadsorbents for water treatment

As a result of scientific research, it was found that synthesized pure sorbents based on a composite of Fe3O4 nanoparticles and AlgBT have an increased adsorption capacity due to the inclusion of double hydroxides and an alginate matrix. The processes of complex formation occur according to the principle of maximum inheritance of the structural features of the original coordination compounds, which make it possible to predict and implement the hypothetical structures of new compounds. All this significantly improves the adsorption capacity of the developed adsorbents with respect to phosphate ions. Modified sorbents with a clay basis are therefore a particularly intriguing field. The current research constructed and described modified sorbents, and then conducted tests in the laboratory to determine how well they absorbed phosphate. This study used spectroscopic techniques (SEM, FTIR, X-ray diffraction, and XRD analytical methods) to examine the structure and physicochemical characteristics of improved ecologically friendly sorbents based on alginates, bentonite, and nanoparticles. The alginate core may be physically and chemically modified and can take part in a variety of phosphate anion adsorption methods thanks to the active COOH and OH groups that are present there. The sorption efficiency was established for a modified Fe3O4NPs@AlgBT. Equilibrium in the system sorbent-an aqueous solution of Na2HPO4 is established in 10 hours after the start of sorption, while two-thirds of all sobbed anions pass into the solid phase during the first two hours. The limiting sorption of phosphate ions on modified Fe3O4NPs@AlgBT reaches 410 mg/g, which makes it possible to offer it as an effective sorbent for industrial wastewater treatment

Quantum Dynamics of Oblique Vibrational States in the Hénon-Heiles System.

In this paper, we study the quantum time evolution of oblique nonstationary vibrational states in a Hénon-Heiles oscillator system with two dissociation channels, which models the stretching vibrational motions of triatomic molecules. The oblique nonstationary states we are interested in are the eigenfunctions of the anharmonic zero-order Hamiltonian operator resulting from the transformation to oblique coordinates, which are defined as those coming from nonorthogonal coordinate rotations that express the matrix representation of the second-order Hamiltonian in a block diagonal form characterized by the polyadic quantum number n = n1 + n2. The survival probabilities calculated show that the oblique nonstationary states evolve within their polyadic group with a high degree of coherence up to the dissociation limits on the short time scale. The degree of coherence is certainly much higher than that exhibited by the local nonstationary states extracted from the conventional orthogonal rotation of the original normal coordinates. We also show that energy exchange between the oblique vibrational modes occurs in a much more regular way than the exchange between the local modes.