Search Results (800)

Some Melanothamnus species have been documented growing epiphytically on other algae in seaweed aquaculture farms as fouling organisms. Such turf-forming Polysiphonia-looking algae were collected from a small (<1.0 km² area) Agarophyton tenuistipitata (Gracilariaceae, Gracilariales) farm on the east coast of the Bay of Bengal and examined for their taxonomy. DNA was extracted from silica gel-preserved specimens, and plastid-encoded rbcL, nuclear-encoded small subunit SSU, large subunit LSU, and universal plastid amplicon (UPA) were amplified and sequenced. Maximum likelihood (ML) and Bayesian inference were performed for the phylogenetic analysis. Four single-locus species delimitation methods (SDMs), namely, the generalized mixed Yule-coalescent (GMYC) method, a Poisson tree processes (PTP) model, the automatic barcode gap discovery (ABGD), and the assemble species by automatic partitioning (ASAP) method, were performed to segregate the putative species from other taxa in the Polysiphonia sensu lato clades. Our results revealed that rbcL had 1.4% interspecific genetic divergence, whereas LSU, UPA, and SSU had 1.6%, 2.5%, and 5.4% genetic divergence, respectively, from the nearest neighbors. Both comparative genetic and distinct morphological data revealed that the collected Bay of Bengal specimens comprise a species new to science. In addition, the above-mentioned SDMs supported the genetic data and segregated our specimens as Melanothamnus coxsbazarensis sp. nov. as a distinct species. Full article

Modeling ion transport through membrane channels is crucial for understanding cellular processes, and Poisson–Nernst–Planck (PNP) equations provide a fundamental continuum framework for such ionic fluxes. We investigate a quasi-one-dimensional steady-state PNP system for two oppositely charged ion species, focusing on how large permanent charges within the channel and realistic boundary conditions impact ion transport. In contrast to classical models that impose ideal electroneutrality at the channel ends (a simplification that eliminates boundary layers near the membrane interfaces), we adopt relaxed neutral boundary conditions that allow small charge imbalances at the boundaries. Using asymptotic analysis treating the large permanent charge as a singular perturbation, we derive explicit first-order expansions for each ionic flux, incorporating boundary layer parameters $(\sigma ,\rho )$ to quantify slight deviations from electroneutrality. This analysis enables a qualitative characterization of individual cation and anion flux behaviors. Notably, we identify two critical transmembrane potentials, $V_{1c}$ and $V_{2c}$, at which the cation and anion fluxes, respectively, vanish, signifying flux-reversal thresholds that delineate distinct monotonic regimes in the flux-voltage response; these critical values depend on the permanent charge magnitude and the boundary layer parameters. We further show that both ionic fluxes exhibit saturation: as the applied voltage becomes extreme, each flux approaches a finite limiting value, with the saturation level modulated by the degree of boundary charge imbalance. Moreover, allowing even small boundary charge deviations reveals non-intuitive discrepancies in flux behavior relative to the ideal electroneutral case. For example, in certain parameter regimes, a large permanent charge that enhances an ionic current under strict electroneutral conditions will instead suppress that current under relaxed-neutral conditions (and vice versa). This new analytical framework exposes subtle yet essential nonlinear dynamics that classical electroneutral assumptions would otherwise obscure. It provides deeper insight into the interplay between large fixed charges and boundary-layer effects, emphasizing the importance of incorporating such realistic boundary conditions to ensure accurate modeling of ion transport through membrane channels. Numerical simulations are performed to provide more intuitive illustrations of our analytical results. Full article

One of the key components of the software quality model is reliability. Its importance has grown with the increasing use and reuse of open-source components in software development. Software reliability growth models are commonly employed to address this aspect by predicting future failure rates and estimating the number of remaining defects throughout the development process. This paper investigates two software reliability growth models derived from the Verhulst model, with a particular focus on a structural property known as Hausdorff saturation. We provide analytical estimates for this characteristic and propose it as an additional criterion for model selection. The models are evaluated using four open-source datasets, where the Hausdorff saturation metric supports the conclusions drawn from standard goodness-of-fit measures. Furthermore, we introduce an interactive software reliability assessment tool that integrates with GitHub, enabling expert users to analyze real-time issue-tracking data from open-source repositories. The tool facilitates model comparison and enhances practical applicability. Overall, the proposed approach contributes to more robust reliability assessment by combining theoretical insights with actionable diagnostics. Full article

A method to characterize the mechanical properties of cellular materials manufactured using 3D printing, specifically employing the fused deposition modeling (FDM) technique, is developed. Numerical simulations, virtual testing, and optimization based on genetic algorithms are combined in this approach to determine the anisotropic properties of the material, which are essential for biomedical applications such as tissue engineering. Homogenization using representative unit cells enabled the calculation of orthotropic properties, including elastic moduli ($E_1$, $E_2$, $E_3$), Poisson’s ratios (${\nu }_{12}$, ${\nu }_{13}$ and ${\nu }_{23}$), and shear moduli ($G_{12}$, $G_{13}$, $G_{23}$). These results validated the virtual tests using an L-shaped beam model, based on a known state of displacements and stresses. In the virtual test of the FDM model, a significant correlation with experimental results was observed, confirming the material’s anisotropy and its influence on deformations and stresses. Meanwhile, the effective medium test demonstrated over 95% agreement between simulated and experimental values, validating the accuracy of the proposed constitutive model. The optimization process, based on multi-objective genetic algorithms, allowed the determination of the material’s mechanical properties through controlled iterations, achieving a strong correlation with the results obtained from the homogenization model. These findings present a new approach for characterizing and optimizing 3D-printed materials using FDM techniques, providing an efficient and reliable method for applications in tissue engineering. Full article

In recent times, copper oxide nanosheets (CONSs) have shown a broad spectrum of industrial uses due to their unique properties, including high electrical conductivity, surface-enhanced catalytic activity, etc. Therefore, industrial processes involved in their manufacture can give rise to airborne particulates. Several in vivo studies have reported toxicity of these nanoparticles due to their interactions with biological molecules. Generally, literature-based assessment of their toxicity has centered on experimental findings. In this paper, we report for the first time, trend in CONSs interactions in intracellular and extracellular fluids, using the Nonlinear Mean Field Poisson–Boltzmann theory. Our theoretical prediction for zeta potential in the extracellular fluid environment align with published values in the literature. Based on this theoretical approach, we also demonstrate that double layer disjoining pressure due to interacting double layers of CONSs is generally higher in intracellular fluids. The findings of our theoretical approach highlight the importance of predicting the extent of cellular uptake potential of CONSs in organs that are prone to such airborne environmental particulates. Full article

This article introduces a computational tool for Bayesian estimation of the expected time until the next event occurs in both homogeneous Poisson processes (HPPs) and non-homogeneous Poisson processes (NHPPs), following a truncated time. The estimation utilizes the linear exponential (LINEX) asymmetric loss function and incorporates both gamma and non-informative priors. Furthermore, it presents a minimax-type criterion to ascertain the optimal sample size required to achieve a specified percentage reduction in posterior risk. Simulation studies indicate that estimators employing gamma priors for both HPP and NHPP demonstrate greater accuracy compared to those based on non-informative priors and maximum likelihood estimates (MLE), provided that the proposed data-driven method for selecting hyperparameters is applied. Full article

Each charging/discharging cycle leads to a gradual decrease in the battery’s capacity. The degradation of capacity in lithium-ion batteries represents a non-monotonous process with random jumps. Earlier studies claimed that the instantaneous degradation value of a lithium-ion battery is influenced by the historical dataset with long-range dependence. The existing methods ignore large jumps and long-range dependences in degradation processes. In order to capture long-range-dependent behavior with random jumps, we refer to the fractional Poisson process. We also outline the relationship between the long-range correlation and the Hurst index. The connection between random jumps in capacitance and long-range dependence of the fractional Poisson process is proven. In order to construct the fractional Poisson predictive model, we included fractional Brownian motion as the diffusion term and the fractional Poisson process as the jump term. The proposed approach is implemented on NASA’s dataset for Li-ion battery degradation. We believe that the error analysis for the fractional Poisson process is advantageous compared with that of the fractional Brownian motion, the fractional Levy stable motion, the Wiener model, and the long short-term memory model. Full article

Lifetime reproductive output (LRO), also called lifetime reproductive success (LRS) is often described by its mean (total fertility rate or net reproductive rate), but it is in fact highly variable among individuals and often positively skewed. Several approaches exist to calculating the variance and skewness of LRO. These studies have noted that a major factor contributing to skewness is the fraction of the population that dies before reaching a reproductive age or stage. The existence of that fraction means that LRO has a zero-inflated distribution. This paper shows how to calculate that fraction and to fit a zero-inflated Poisson or zero-inflated negative binomial distribution to the LRO. We present a series of applications to populations before and after demographic transitions, to populations with particularly high probabilities of death before reproduction, and a couple of large mammal populations for good measure. The zero-inflated distribution also provides extinction probabilities from a Galton-Watson branching process. We compare the zero-inflated analysis with a recently developed analysis using convolution methods that provides exact distributions of LRO. The agreement is strikingly good. Full article

Background: Understanding how food processing impacts type 2 diabetes (T2DM) control is essential for disease management. This study aimed to assess the association between ultra-processed food (UPF) consumption, as defined by the NOVA classification, and metabolic parameters in T2DM patients. Methods: This was a cross-sectional analysis using baseline data from the NUGLIC study, a multicenter randomized clinical trial. Multiple linear and Poisson regressions were used to evaluate associations between quintiles of processed and ultra-processed food consumption and glycated hemoglobin (HbA1c) as the primary outcome. Secondary outcomes included fasting glucose, lipid profile, body mass index (BMI), and waist circumference. Results: This study included 326 participants. UPF consumption accounted for approximately 16.4% of total daily energy intake. No significant linear associations were observed between higher consumption of industrialized foods and anthropometric or glycemic markers. However, intermediate and high consumption levels were associated with an increased total cholesterol (Q3: β = 26.6; Q4: β = 26.7) and LDL-cholesterol (Q4: β = 19.8; Q5: β = 17.5). Conclusion: In T2DM patients, a higher intake of processed and ultra-processed foods was linked to elevated cholesterol and LDL levels. These findings highlight potential cardiovascular risks but do not support causality due to the study’s cross-sectional design. Full article

Understanding three-dimensional (3D) auxetic structural responses to impact loading remains challenging due to large deformations involving failure evolution and the interaction between geometric and material instabilities. In this study, the Generalized Interpolation Material Point Method (GIMP) is used to investigate representative auxetic structures, with the focus on the negative Poisson’s ratio effect on the responses to impact loading. Using a cubic lattice model for 3D re-entrant structures, simulations with different impact speeds are performed to evaluate corresponding energy absorption characteristics and deformation behaviors. Three constitutive models for lattice materials (linear elasticity, elastoplasticity, and damage) are employed to analyze the corresponding variations in auxetic structural performance. The computational results indicate that distinct deformation mechanisms are mainly associated with microstructural geometry, while the constitutive modeling effect is not significant. The findings demonstrate the importance of the process–structure–property relationship in the impact performance of protective structures. Verification against theoretical predictions of the Poisson’s ratio–strain relationship confirms the potential of GIMP in effectively engineering auxetic structures for general applications. Full article

Efficient autonomous exploration in unknown obstacle cluttered environments with interior obstacles remains a challenging task for mobile robots. In this work, we present a novel exploration process for a non-holonomic agent exploring 2D spaces using onboard LiDAR sensing. The proposed method generates velocity commands based on the calculation of the solution of an elliptic Partial Differential Equation with Dirichlet boundary conditions. While solving Laplace’s equation yields collision-free motion towards the free space boundary, the agent may become trapped in regions distant from free frontiers, where the potential field becomes almost flat, and consequently the agent’s velocity nullifies as the gradient vanishes. To address this, we solve a Poisson equation, introducing a source point on the free explored boundary which is located at the closest point from the agent and attracts it towards unexplored regions. The source values are determined by an exponential function based on the shortest path of a Hybrid Visibility Graph, a graph that models the explored space and connects obstacle regions via minimum-length edges. The computational process we apply is based on the Walking on Sphere algorithm, a method that employs Brownian motion and Monte Carlo Integration and ensures efficient calculation. We validate the approach using a real-world platform; an AmigoBot equipped with a LiDAR sensor, controlled via a ROS-MATLAB interface. Experimental results demonstrate that the proposed method provides smooth and deadlock-free navigation in complex, cluttered environments, highlighting its potential for robust autonomous exploration in unknown indoor spaces. Full article

Material Extrusion (MEX) process is increasingly used to fabricate components for structural applications, driven by the availability of advanced materials and greater industrial adoption. In these contexts, understanding the mechanical performance of printed parts is crucial. However, conventional methods for assessing anisotropic elastic behavior often rely on expensive equipment and time-consuming procedures. The aim of this study is to evaluate the applicability of the impulse excitation of vibration (IEV) in characterizing the dynamic mechanical properties of a 3D-printed composite material. Tensile tests were also performed to compare quasi-static properties with the dynamic ones obtained through IEV. The tested material, Nylon 12CF, contains 35% short carbon fibers by weight and is commercially available from Stratasys. It is used in the fused deposition modeling (FDM) process, a Material Extrusion technology, and exhibits anisotropic mechanical properties. This is further reinforced by the filament deposition process, which affects the mechanical response of printed parts. Young’s modulus obtained in the direction perpendicular to the deposition plane (E₃₃), obtained via IEV, was 14.77% higher than the value in the technical datasheet. Comparing methods, the Young’s modulus obtained in the deposition plane, in an inclined direction of 45 degrees in relation to the deposition direction (E₄₅), showed a 22.95% difference between IEV and tensile tests, while Poisson’s ratio in the deposition plane (v₁₂) differed by 6.78%. This data is critical for designing parts subject to demanding service conditions, and the results obtained (orthotropic elastic properties) can be used in finite element simulation software. Ultimately, this work reinforces the potential of the IEV method as an accessible and consistent alternative for characterizing the anisotropic properties of components produced through additive manufacturing (AM). Full article

Background: The consumption of ultra-processed foods (UPFs) represents an important public health challenge, especially among education workers, whose intense routine can negatively impact eating habits. This study aimed to analyze the factors associated with the regular consumption of UPF among employees of the Federal Network of Professional, Scientific and Technological Education (RFEPCT) in Brazil. Methods: This was a cross-sectional study, with a quantitative approach, carried out with 1563 education workers. Validated instruments on eating habits (PeNSE), mental health (DASS-21) and quality of life (WHOQOL-bref) were used. The regular consumption of UPF was defined as intake on ≥5 days in the last seven days. The association between the regular consumption of UPF and sociodemographic, occupational, behavioral, mental health and quality of life variables was assessed by Poisson regression with robust variance, generating adjusted prevalence ratios (PRadj) and respective 95% confidence intervals. Results: The regular consumption of UPF was associated mainly with female gender, a lower age group, Southeast and Midwest regions, dissatisfaction with sleep and the body, physical inactivity and poor sleep quality. In addition, the findings suggested a significant relationship between the worst stress scores and soft drinks (PRadj: 2.11; CI: 1.43–3.13), anxiety and soft drinks (PRadj: 1.83; CI: 1.24–2.70) and depression and industrialized/ultra-processed salty foods (PRadj: 2.43; CI: 1.82–3.26). The same was observed in the scores for the worst perception of quality of life, where there was a prevalence of up to 2.32 in the psychological domain and the consumption of industrialized/ultra-processed salty foods. Conclusions: The findings indicate that multiple interrelated factors—individual, psychosocial and occupational—are associated with the consumption of UPF among education workers. These results reinforce the importance of institutional policies that integrate actions to promote dietary health, mental health care and improved working conditions in the education sector. Full article

The accordion honeycomb has unique deformation characteristics in cellular materials. This study develops a three-dimensional equivalent Cauchy continuum model (3D-ECM) based on the variational asymptotic method (VAM) to efficiently predict the mechanical response of the accordion honeycomb. The accuracy of the 3D-ECM is validated via quasi-static compression experiments on 3D-printed specimens and detailed 3D finite element simulations (3D-FEM), showing a strong correlation between simulation and experimental data. Parametric analyses reveal that the re-entrant angle, ligament-to-strut length ratio, and thickness ratios significantly affect the equivalent elastic moduli, providing insights into geometric optimization strategies for targeted mechanical performance. Comparative experiments among honeycomb structures with positive, negative, and zero Poisson’s ratios show that the accordion honeycomb achieves superior dimensional stability and tunable stiffness but exhibits lower energy-absorption efficiency due to discontinuous buckling and recovery processes. Further comparison among different ZPR honeycombs confirms that the accordion design offers the highest equivalent modulus in the re-entrant direction. The findings underscore the accordion honeycomb’s promise in scenarios demanding structural reliability, tunable stiffness, and moderate energy absorption. Full article

This work investigates fractional stochastic Schrödinger evolution equations in a Hilbert space, incorporating complex potential symmetry and Poisson jumps. We establish the existence of mild solutions via stochastic analysis, semigroup theory, and the Mönch fixed-point theorem. Sufficient conditions for exponential stability are derived, ensuring asymptotic decay. We further explore trajectory controllability, identifying conditions for guiding the system along prescribed paths. A numerical example is provided to validate the theoretical results. Full article