Search Results (822)

Accurate segmentation of abdominal aortic aneurysm (AAA) from computed tomography (CT) images is critical for early diagnosis and treatment planning of vascular diseases. However, noise in CT images obscures vessel boundaries, reducing segmentation accuracy. U-Net is widely used for medical image segmentation, where noise removal is critical. This study applied various denoising filters for U-Net segmentation and classified the severity of segmented AAA images to evaluate accuracy. Poisson–Gaussian noise was added to AAA CT images, and then average, median, Wiener, and median-modified Wiener filters (MMWF) were applied. U-Net-based segmentation was performed, and the segmentation accuracy of the output images obtained per filter was quantitatively assessed. Furthermore, the Hough circle algorithm was applied to the segmented images for diameter measurement, enabling severity classification and evaluation of classification accuracy. MMWF application improved the Matthews correlation coefficient, Dice score, Jaccard coefficient, and mean surface distance by 31.09%, 34.25%, 53.99%, and 3.70%, respectively, compared with images with added noise. Moreover, classification based on the output images obtained after MMWF application demonstrated the highest accuracy, with sensitivity, precision, and accuracy reaching 100%. Thus, U-Net-based segmentation yields more accurate results when images are processed with the MMWF and analyzed using the Hough circle algorithm. Full article

Metamaterials are artificial materials composed of special microstructures that have properties with unusual and useful features and can be applied to many fields. With their unique properties and sensitivity to external stimuli, metamaterials offer design flexibility to users. Traditional manufacturing is often not up to the task of creating metamaterials, which are now more accurately and more effectively analyzed than they were in the past. Recent advances in additive manufacturing (AM) have achieved remarkable success, with ensemble machine learning models demonstrating R² values exceeding 0.97 and accuracy improvements of 9.6% over individual approaches. State-of-the-art multiphoton polymerization (MPP) techniques now reach submicron resolution (<1 μm), while selective laser melting (SLM) processes provide 20–100 μm precision for metallic metamaterials. This work offers a comprehensive review of additively manufactured 3D metamaterials, focusing on three categories of their fabrication: electromagnetic (achieving bandgaps up to 470 GHz), acoustic (providing 90% sound suppression at targeted frequencies), and mechanical (demonstrating Poisson’s ratios from −0.8 to +0.8). The relationship between different types of AM processes used in creating 3D objects and the properties of the resulting materials has been systematically reviewed. This research aims to address gaps and develop new applications to meet the modern demand for the broader use of metamaterials in advanced devices and systems that require high efficiency for sophisticated, high-performance applications. Full article

Stochastic geometry provides a powerful analytical framework for evaluating interference-limited cellular networks with randomly deployed base stations (BSs). While prior studies have examined limited channel state information at the transmitter (CSIT) and low-resolution analog-to-digital converters (ADCs) separately, their joint impact in multi-user multiple-input multiple-output (MIMO) systems remains largely unexplored. This paper investigates a downlink cellular network in which BSs are distributed according to a homogeneous Poisson point process (PPP), employing zero-forcing beamforming (ZFBF) with limited feedback, and receivers are equipped with one-bit ADCs. We derive a tractable approximation for the achievable spectral efficiency that explicitly accounts for both the quantization error from limited feedback and the receiver distortion caused by coarse ADCs. Based on this approximation, we determine the optimal feedback rate that maximizes the net spectral efficiency. Our analysis reveals that the optimal number of feedback bits scales logarithmically with the channel coherence time but its absolute value decreases due to coarse quantization. Simulation results validate the accuracy of the proposed approximation and confirm the predicted scaling behavior, demonstrating its effectiveness for interference-limited multi-user MIMO networks. Full article

The manufacturing industry, in general, and the plastic industry, in particular, have been developing new materials and process methods that need a correct study and optimization. Nowadays, the main approach to optimize these processes is using numerical methods and, in the case of particulate materials, the Discrete Elements Method to estimate the particles interactions. But those mathematical models use some parameters that depend on the material and must be calibrated, thus requiring an important computational and experimental cost. In this study, we integrate different speed-up procedures and present a general calibration method of Low-Density Polyethylene particles, to obtain the calibrated solid density and Poisson’s ratio of the material, the restitution, static and rolling friction factors in the particle-to-particle and particle-to-wall interactions, and the contact model variables (damping factor, stiffness factor, and energy density). For this calibration, four different tests were carried out, both experimentally and with simulations, obtaining the bulk density, the repose and shear angles, and the dropped powder. All these response variables were compared between simulations and experimental tests, and using genetic algorithms, the input parameters (design variables) were calibrated after 85 iterations, obtaining a Mean Absolute Percentage Error of the response variables lower than 2% compared to the experimental results. Full article

In Bayesian statistics, the prior distributions play a key role in the inference, and there are procedures for finding prior distributions. An important problem is that these procedures often lead to improper prior distributions that cannot be normalized to probability measures. Such improper prior distributions lead to technical problems, in that certain calculations are only fully justified in the literature for probability measures or perhaps for finite measures. Recently, expectation measures were introduced as an alternative to probability measures as a foundation for a theory of uncertainty. Using expectation theory and point processes, it is possible to give a probabilistic interpretation of an improper prior distribution. This will provide us with a rigid formalism for calculating posterior distributions in cases where the prior distributions are not proper without relying on approximation arguments. Full article

The durations of wars fought between 1480 and 1941 A.D. were found to be well represented by random numbers chosen from a single-event Poisson distribution with a half-life of (1.25 ± 0.1) years. This result complements the work of L.F. Richardson who found that the frequency of outbreaks of wars can be described as a Poisson process. This result suggests that a quick return on investment requires a distillation of the many stressors of the day, each one of which has a small probability of being included in a convincing well-orchestrated simple call-to-arms. The half-life is a measure of how this call wanes with time. Full article

This paper considers a heterogeneous queuing system with an unlimited number of servers, where the parameters are determined by a random environment. A distinctive feature is that the parameters of the exponential distribution of the request processing time do not change their values until the end of service. Thus, the devices in the system under consideration are heterogeneous. For the study, a method of asymptotic analysis is proposed under the condition of extremely rare changes in the states of the random environment. We consider the following problem. Cloud node accepts requests of one type that have a similar intensity of arrival and duration of processing. Sometimes an input scheduler switches to accept requests of another type with other intensity and duration of processing. We model the system as an infinite-server queue in a random environment, which influences the arrival intensity and service time of new requests. The random environment is modeled by a Markov chain with a finite number of states. Arrivals are modeled as a Poisson process with intensity dependent on the state of the random environment. Service times are exponentially distributed with rates also dependent on the state of the random environment at the time moment when the request arrived. When the environment changes its state, requests that are already in the system do not change their service times. So, we have requests of different types (serviced with different rates) present in the system at the same time. For the study, we consider a situation where changes of the random environment are made rarely. The method of asymptotic analysis is used for the study. The asymptotic condition of a rarely changing random environment (entries of the generator of the corresponding Markov chain tend to zero) is used. A multi-dimensional joint steady-state probability distribution of the number of requests of different types present in the system is obtained. Several numerical examples illustrate the comparisons of asymptotic results to simulations. Full article

Land Surface Temperature (LST) is a critical variable for understanding land–atmosphere interactions and is widely applied in urban heat monitoring, evapotranspiration estimation, near-surface air temperature modeling, soil moisture assessment, and climate studies. MODIS LST products, with their global coverage, long-term consistency, and radiometric calibration, are a major source of LST data. However, frequent data gaps caused by cloud contamination and atmospheric interference severely limit their applicability in analyses requiring high spatiotemporal continuity. This study presents a seamless MODIS LST reconstruction framework that integrates multi-source data fusion and a multi-stage optimization strategy. The method consists of three key components: (1) topography- and land cover-constrained spatial interpolation, which preliminarily fills orbit-induced gaps using elevation and land cover similarity criteria; (2) pixel-level LST reconstruction via random forest (RF) modeling with multi-source predictors (e.g., NDVI, NDWI, surface reflectance, DEM, land cover), coupled with HANTS-based temporal smoothing to enhance temporal consistency and seasonal fidelity; and (3) Poisson-based image fusion, which ensures spatial continuity and smooth transitions without compromising temperature gradients. Experiments conducted over two representative regions—Huainan and Jining—demonstrate the superior performance of the proposed method under both daytime and nighttime scenarios. The integrated approach (Step 3) achieves high accuracy, with correlation coefficients (CCs) exceeding 0.95 and root mean square errors (RMSEs) below 2K, outperforming conventional HANTS and standalone interpolation methods. Cross-validation with high-resolution Landsat LST further confirms the method’s ability to retain spatial detail and cross-scale consistency. Overall, this study offers a robust and generalizable solution for reconstructing MODIS LST with high spatial and temporal fidelity. The framework holds strong potential for broad applications in land surface process modeling, regional climate studies, and urban thermal environment analysis. Full article

In this paper we present an exact numerical model for the evaluation of a three-echelon supply chain with multiple retailers. Poisson demand, exponentially distributed transportation times and lost sales at the retailers are assumed. The system is modeled as a continuous time Markov chain, and the analysis is based on matrix analytic methods. We analyze the infinitesimal generator matrix of the process and develop an algorithm for its construction. Performance measures for the system are calculated algorithmically from the stationary probabilities vector. The algorithm is used for an extensive numerical investigation of the system so that conclusions of managerial importance may be drawn. Full article

In this article, the mechanism of relaxation polarization currents occurring at a constant temperature (isothermal process) in crystals with ionic-molecular chemical bonds (CIMBs) in an alternating electric field was investigated. Methods of the quasi-classical kinetic theory of dielectric relaxation, based on solutions of the nonlinear system of Fokker–Planck and Poisson equations (for the blocking electrode model) and perturbation theory (by expanding into an infinite series in powers of a dimensionless small parameter) were used. Generalized nonlinear mathematical expressions for calculating the complex amplitudes of relaxation modes of the volume-charge distribution of the main charge carriers (ions, protons, water molecules, etc.) were obtained. On this basis, formulas for the current density of relaxation polarization (for transient processes in a dielectric) in the k-th approximation of perturbation theory were constructed. The isothermal polarization currents are investigated in detail in the first four approximations (k = 1, 2, 3, 4) of perturbation theory. These expressions will be applied in the future to compare the results of theory and experiment, in analytical studies of the kinetics of isothermal ion-relaxation (in crystals with hydrogen bonds (HBC), proton-relaxation) polarization and in calculating the parameters of relaxers (molecular characteristics of charge carriers and crystal lattice parameters) in a wide range of field parameters (0.1–1000 MV/m) and temperatures (1–1550 K). Asymptotic (far from transient processes) recurrent formulas are constructed for complex amplitudes of relaxation modes and for the polarization current density in an arbitrary approximation k of perturbation theory with a multiplicity r by the polarizing field (a multiple of the fundamental frequency of the field). The high degree of reliability of the theoretical results obtained is justified by the complete agreement of the equations of the mathematical model for transient and stationary processes in the system with a harmonic external disturbance. This work is of a theoretical nature and is focused on the construction and analysis of nonlinear properties of a physical and mathematical model of isothermal ion-relaxation polarization in CIMB crystals under various parameters of electrical and temperature effects. The theoretical foundations for research (construction of equations and working formulas, algorithms, and computer programs for numerical calculations) of nonlinear kinetic phenomena during thermally stimulated relaxation polarization have been laid. This allows, with a higher degree of resolution of measuring instruments, to reveal the physical mechanisms of dielectric relaxation and conductivity and to calculate the parameters of a wide class of relaxators in dielectrics in a wide experimental temperature range (25–550 K). Full article

In traditional scallion cultivation, the bare-root transplanting method—which involves direct seeding, seedling raising in the field, and lifting—is commonly adopted to minimize seedling production costs. However, during the mechanized transplanting of bare-root scallion seedlings, practical problems such as severe seedling damage and poor planting uprightness exist. In this paper, the Hertz–Mindlin with Bonding contact model was used to establish the scallion seedling model. Combined with the Plackett–Burman experiment, steepest ascent experiment, and Box–Behnken experiment, the bonding parameters of scallion seedlings were calibrated. Furthermore, the accuracy of the scallion seedling model parameters was verified through the stress–strain characteristics observed during the actual loading and compression process of the scallion seedlings. The results indicate that the scallion seedling normal/tangential contact stiffness, scallion seedling normal/tangential ultimate stress, and scallion Poisson’s ratio significantly influence the mechanical properties of scallion seedlings. Through optimization experiments, the optimal combination of the above parameters was determined to be 4.84 × 10⁹ N/m, 5.64 × 10⁷ Pa, and 0.38. In this paper, the flexible planting components of scallion seedlings were taken as the research object. Flexible protrusions were added to the planting disc to reduce the damage rate of scallion seedlings, and an EDEM-ADAMS coupling interaction model between the planting components and scallion seedlings was established. Based on this model, optimization and verification were carried out on the key components of the planting components. Orthogonal experiments were conducted with the contact area between scallion seedlings and the disc, rotational speed of the flexible disc, furrow depth, and clamping force on scallion seedlings as experimental factors, and with the uprightness and damage status of scallion seedlings as evaluation criteria. The experimental results showed that when the contact area between scallion seedlings and the disc was 255 mm², the angular velocity was 0.278 rad/s, and the furrow depth was 102.15 mm, the performance of the scallion planting mechanism was optimal. At this point, the uprightness of the scallion seedlings was 94.80% and the damage rate was 3%. Field experiments were carried out based on the above parameters. The results indicated that the average uprightness of transplanted scallion seedlings was 93.86% and the damage rate was 2.76%, with an error of less than 2% compared with the simulation prediction values. Therefore, the parameter model constructed in this paper is reliable and effective, and the designed and improved transplanting mechanism can realize the upright and low-damage planting of scallion seedlings, providing a reference for the low-damage and high-uprightness transplanting operation of scallions. Full article

This paper explores the mechanisms of energy transfer and failure zones in rock mass blasting. By combining theoretical derivation with numerical simulation, we examine the deformation, failure features, and source parameters of rock subjected to spherical charge blasting. Using the Mohr–Coulomb yield criterion, we classify the rock failure process into four zones: the cavity zone, fracture zone, radial fracture zone, and vibration zone. Additionally, we establish a dynamic partitioned model that considers explosion cavity expansion, compression wave propagation, and energy dissipation. Applying elastic failure conditions, we develop a calculation model for vibration parameters in each zone and use MATLAB programming to find numerical solutions for the radius of the failure zone, elastic potential energy, and the interface pressure over time. Verification with a granite underground blasting project in Qingdao shows the ratio of the spherical cavity radius to the charge radius is 1.49, and the crushing zone radius to the charge radius is 2.85. Theoretical results are consistent with the approximate method in magnitude and value, confirming the model’s reliability. The interface pressure sharply peaks and then decays exponentially. The growth of the fracture zone depends heavily on initial pressure, rock strength, and Poisson’s ratio. These findings support blasting engineering design and seismic effect assessment. Full article

Background/Objectives: Cancer progression is characterized by the suppression of apoptosis, activation of metastatic processes, and dysregulation of cell proliferation. The proper functioning of these mechanisms relies on critical signaling pathways, including Phosphoinositide 3-kinase/Protein kinase B/mammalian Target of Rapamycin (PI3K/Akt/mTOR), Mitogen-Activated Protein Kinase (MAPK), and Signal Transducer and Activator of Transcription 3 (STAT3). Although curcumin and resveratrol exhibit anticancer properties and affect these pathways, their pharmacokinetic limitations, including poor bioavailability and low solubility, restrict their clinical application. The aim of our study was to evaluate the synergistic anticancer potential of curcumin and resveratrol through hybrid molecules rationally designed from these compounds to mitigate their pharmacokinetic limitations. Furthermore, we analyzed the multi-target anticancer effects of these hybrids on the AKT serine/threonine kinase 1 (AKT1), MAPK, and STAT3 pathways using in silico molecular modeling approaches. Methods: Three hybrid molecules, including a long-chain (ELRC-LC) and a short-chain (ELRC-SC) hybrid, an ester-linked hybrid, and an ether-linked hybrid (EtLRC), were designed using the Avogadro software (v1.2.0), and their geometry optimization was carried out using Density Functional Theory (DFT). The electronic properties of the structures were characterized through Frontier Molecular Orbital (FMO), Molecular Electrostatic Potential (MEP), and Fourier Transform Infrared (FTIR) analyses. The binding energies of the hybrid molecules, curcumin, resveratrol, their analogs, and the reference inhibitor were calculated against the AKT1, MAPK, and STAT3 receptors using molecular docking. The stabilities of the best-fitting complexes were evaluated through 100 ns molecular dynamics (MD) simulations, and their binding free energies were estimated using the Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA) method. Results: DFT analyses demonstrated stable electronic characteristics for the hybrids. Molecular docking analyses revealed that the hybrids exhibited stronger binding compared to curcumin and resveratrol. The binding energy of −11.4 kcal/mol obtained for the ELRC-LC hybrid against AKT1 was particularly remarkable. Analysis of 100 ns MD simulations confirmed the conformational stability of the hybrids. Conclusions: Hybrid molecules have been shown to exert multi-target mechanisms of action on the AKT1, MAPK, and STAT3 pathways, and to represent potential anticancer candidates capable of overcoming pharmacokinetic limitations. Our in silico-based study provides data that will guide future in vitro and in vivo studies. These rationally designed hybrid molecules, owing to their receptor affinity, may serve as de novo hybrid inhibitors. Full article

Implementing follow-up policies under healthcare warranties for chronic disease patients plays a crucial role in reducing the risk of adverse outcomes (AOs) and controlling long-term medical costs. However, the additional cost associated with these services often discourages hospitals from providing them. Background/Objectives: To incentivize participation from both hospitals and patients in follow-up programs, this paper introduces a patient copayment mechanism. We propose a theoretical mathematical modeling framework to investigate the optimal pricing of follow-up policies from both patients’ and hospitals’ perspectives to achieve win–win outcomes. Methods: Using the Cox frailty model, we stratify patients by risk level and model hazard rate functions for three follow-up policies featuring periodic checkups, incorporating the virtual age method. Building on this framework, we employ the Non-Homogeneous Poisson Process to analyze the total expected costs incurred by hospitals and patients across different policies and risk strata. This analysis derives the minimum price acceptable to hospitals for providing follow-up services and the maximum additional cost patients are willing to bear for them. The feasibility and applicability of the proposed model are demonstrated through a case study of pediatric type 1 diabetes mellitus (T1DM). Results: Win–win price intervals for T1DM patients are more achievable for higher-risk individuals. These intervals narrow or widen with the age reduction factor, checkup cost, and AO treatment cost. Hospitals should prioritize higher-risk patients, improve checkup effectiveness, and balance costs of checkups and treatments when optimizing pricing decisions. Conclusions: These insights provide valuable guidance for hospitals in strategically designing follow-up policies tailored to diverse risk cohorts and determining optimal price intervals. Full article

The spatial distribution of plant species is a crucial indicator of the mechanisms driving competition or coexistence both within and between populations and communities. Analyzing these patterns provides essential insights into fundamental ecological processes and aids in evaluating ecological hypotheses. To study the spatial distribution of dominant tree species and their associations both within and among species, we established a 25-hectare forest plot in Lushan Mountain. We employed the g(r) function alongside three null models—complete spatial randomness (CSR), heterogeneous Poisson (HP), and antecedent condition (AC)—to analyze spatial patterns and assess species interactions at various life stages. Additionally, we examined the relationships between spatial distributions and environmental factors such as soil properties and topography using Berman’s test. Our results showed that all 12 dominant tree species exhibited significant aggregation under the CSR model; however, the scales of aggregation were reduced under the HP model. We also found evidence of aggregation among multiple species across different life stages and tree layers under CSR. Notably, this pattern persisted under the AC model but was limited to specific spatial scales. Furthermore, elevation, topographical convexity, and the total content of soil nitrogen (N) and carbon (C) were identified as statistically significant predictors of species distributions. Overall, these findings highlight that both biological and environmental factors play a vital role in shaping plant spatial patterns across different scales. Full article