Search Results (553)

This study focuses on surface wind analysis at the small regional airport in Svidnik, used primarily for pilot training under daytime VFR conditions. Due to the complex local terrain and lack of prior meteorological data, an automatic weather station was installed, collecting over 208,000 wind measurements over a two-year period at ten-minute intervals. The dataset was processed using hierarchical filtering and statistical selection, and visualized via wind rose diagrams. The results confirmed a dominant southeastern wind component, supporting the current runway orientation (01/19). However, a less frequent easterly wind direction was identified as a safety concern, causing turbulence near the runway due to terrain and vegetation. This is particularly critical for trainee pilots during final approach and landing. Statistical analysis showed that easterly winds, though less common, appear year-round with a peak in summer. Pearson correlation and linear regression confirmed a significant relationship between the number of easterly wind days and their measurement frequency. Daytime winds were stronger than nighttime, justifying the focus on daylight data. The study provides practical recommendations for training flight safety and highlights the value of localized wind monitoring at small airports. The presented methodology offers a framework for improving operational awareness and reducing risk in complex environments. Full article

The specific features of the phase diagrams of aqueous Pluronic systems, and particularly those of reverse Pluronics, are critically important for their broad range of applications, notably as nanocarriers for anticancer molecules. This work aims to investigate the effect of increasing hydrophobicity, achieved by varying the PPO/PEO ratio and the molecular weight, on the phase behavior of three reverse Pluronics: 10R5 [(PPO)₈–(PEO)₂₂–(PPO)₈], 17R4 [(PPO)₁₄–(PEO)₂₄–(PPO)₁₄] and 31R1 [(PPO)₂₆–(PEO)₇–(PPO)₂₆]. A broad set of physical measurements, including density, sound velocity, viscosity, and surface tension, was used to characterize the physical properties of the solutions. These data were complemented by additional techniques such as direct observation, dynamic light scattering, and rheological measurements. Based on the primary measurements, molar volume, apparent adiabatic compressibility, and hydration profiles were subsequently derived. Phase diagrams were constructed for each system over concentration ranges of 0.1–90 wt.% and temperatures between 6 and 70 °C, identifying distinct regions corresponding to random networks, flower-like micelles, and micellar networks. Notably, the 31R1/water system does not form flower-like micelles, whereas both the 17R4/water and 10R5/water systems display such structures, albeit in a narrow interval, that shift toward higher concentrations and temperatures with increasing PPO/PEO ratio. Altogether, the present study provides new insights into the physicochemical behavior of reverse Pluronic systems, offering a foundation for their rational design as hydrophobic nanocarriers, either as standalone entities or in conjunction with other copolymers. Full article

Rizhao Reservoir, Shandong Province, China, as a key regional water supply hub, provides water for domestic, industrial, and agricultural uses in and around Rizhao City by intercepting runoff, which plays a central role in guaranteeing water supply security and supporting regional development. This study systematically collected 66 surface water samples to elucidate the hydrochemical characteristics within the reservoir area, identify the principal influencing factors, and clarify the sources of dissolved ions, aiming to enhance the understanding of the prevailing water quality conditions. A systematic analysis of hydrochemical facies, solute provenance, and governing processes in the study area’s surface water was conducted, employing an integrated mathematical and statistical approach, comprising Piper trilinear diagrams, correlation analysis, and ionic ratios. Meanwhile, the entropy weight-based water quality index (EWQI) and irrigation water quality evaluation methods were employed to assess the surface water quality in the study area quantitatively. Analytical results demonstrate that the surface water system within the study area is classified as freshwater with circumneutral to slightly alkaline properties, predominantly characterized by Ca-HCO₃ and Ca-Mg-SO₄-Cl hydrochemical facies. The evolution of solute composition is principally governed by rock–water interactions, whereas anthropogenic influences and cation exchange processes exert comparatively minor control. Dissolved ions mostly originate from silicate rock weathering, carbonate rock dissolution, and sulfate mineral dissolution processes. Potability assessment via the entropy-weighted water quality index (EWQI) classifies surface waters in the study area as Grade I (Excellent), indicating compliance with drinking water criteria under defined boundary conditions. Irrigation suitability analysis confirms minimal secondary soil salinization risk during controlled agricultural application, with all samples meeting standards for direct irrigation use. Full article

This study examined globalisation, de-globalisation, the combination, and the future of value chains to ascertain which would be best for the future of value chains. The study used a cross-sectional survey of 277 randomly selected employees of multinational manufacturing firms in Nigeria. The data were analysed using structural equation model path diagram techniques. The results indicate that de-globalisation and the combination of globalisation and de-globalisation have direct and indirect significant relationships with the future of value chains, but globalisation does not have any direct significant relationship with the future of value chains but has an indirect significant relationship with the future of value chains. In addition, supply chain management significantly mediates the relationships among globalisation, de-globalisation, the combination, and the future of value chains. By establishing a significant association between the combination and the future of value chains, the study departs from future studies whose results are largely situated on the bipolar ends of a continuum. The study makes significant contributions to the traditional theory of trade protectionism, endogenous growth theory, and institutional theory, as well as to practice. Full article

In this research paper, we study symmetry groups, soliton solutions, and the dynamical behavior of the Ivancevic Option Pricing Model (IOPM). First, we find the Lie symmetries of the considered model; next, we use them to determine the corresponding symmetry groups. Then, we attempt to solve IOPM by means of two methods. We provide some wave solutions and give further details of the solution using 2D and 3D graphs. These results are interpreted as important clarifications in financial mathematics and deepen our understanding of the dynamics involved during the pricing of options. Secondly, the quasi-periodic behavior of the two-dimensional dynamical system and its perturbed system are plotted using Python software (Python 3.13.5 version). Various frequencies and amplitudes are considered to confirm the quasi-periodic behavior via the Lyapunov exponent, bifurcation diagram, and multistability analysis. These findings are particularly in consonance with current research that investigates IOPM as a nonlinear wave alternate for normal models and the importance of graphical representations in the understanding of financial derivative dynamics. We, therefore, hope to fill in the gaps in the literature that currently exist about the use of multi-solution methods and their effects on financial modeling through the employment of sophisticated graphical techniques. This will be helpful in discussing matters in the field of financial mathematics and open up new directions of investigation. Full article

Remanufacturing plays a key role in the circular economy by reducing material consumption and extending product life cycles. However, a major challenge in remanufacturing is accurately forecasting the availability of cores, particularly regarding their quantity, timing, and condition. Although machine learning (ML) offers promising approaches for addressing this challenge, there is limited clarity on which influencing factors are most critical and which ML approaches are best suited to remanufacturing-specific forecasting tasks. This study addresses this gap through a mixed-method approach combining expert interviews with two systematic literature reviews. The interviews with professionals from remanufacturing companies identified key influencing factors affecting product returns, which were structured into an adapted Ishikawa diagram. In parallel, the literature reviews analyzed 125 peer-reviewed publications on ML-based forecasting in related domains—specifically, spare parts logistics and manufacturing quality prediction. The review categorized data sources into real-world, simulated, and benchmark datasets and examined commonly applied ML models, including traditional methods and deep learning architectures. The findings highlight transferable methodologies and critical gaps, particularly a lack of remanufacturing-specific datasets and integrated models. This study contributes a structured overview of ML forecasting in remanufacturing and outlines future research directions for enhancing predictive accuracy and practical applicability. Full article

The usual inputs for a causal identification task are a graph representing qualitative causal hypotheses and a joint probability distribution for some of the causal model’s variables when they are observed rather than intervened on. Alternatively, the available probabilities sometimes come from a combination of passive observations and controlled experiments. It also makes sense, however, to consider causal identification with data collected via schemes more generic than (perfect) passive observation or perfect controlled experiments. For example, observation procedures may be noisy, may disturb the variables, or may yield only coarse-grained specification of the variables’ values. In this work, we investigate identification of causal quantities when the probabilities available for inference are the probabilities of outcomes of these more generic schemes. Using process theories (aka symmetric monoidal categories), we formulate graphical causal models as second-order processes that respond to such data collection instruments. We pose the causal identification problem relative to arbitrary sets of available instruments. Perfect passive observation instruments—those that produce the usual observational probabilities used in causal inference—satisfy an abstract process-theoretic property called marginal informational completeness. This property also holds for other (sets of) instruments. The main finding is that in the case of Markovian models, as long as the available instruments satisfy this property, the probabilities they produce suffice for identification of interventional quantities, just as those produced by perfect passive observations do. This finding sharpens the distinction between the Markovianity of a causal model and that of a probability distribution, suggesting a more extensive line of investigation of causal inference within a process-theoretic framework. Full article

Background: The therapeutic potential of natural products in cognitive disabilities has drawn growing attention, yet a comprehensive analysis of trends and key contributors is lacking. This study provides a bibliometric overview highlighting growth patterns, themes, and future directions. Methods: A comprehensive Scopus search with multistep filtering was conducted by applying keywords related to natural products and cognitive disabilities to titles, abstracts, and keywords, initially retrieving 10,011 documents. Filters for original articles and English language reduced the results to 5688. Data extracted in October 2024 were analyzed using Excel and the R-package, yielding performance and citation indices. Differential proliferation was visualized using a Sankey diagram, while thematic maps highlighted key research themes, geographic trends, and subject clusters. Results: The field exhibited an annual growth rate of 12.36% from 1971 to 2024, with 2021 being the most productive year (497 articles). In recent decades, citation metrics have highlighted significant impacts. Thematic maps and Sankey diagrams revealed the research focus, geographic trends, and collaboration. Alzheimer’s disease dominates the field, alongside topics such as oxidative stress, neuroprotection, and molecular docking. Emerging trends include ferroptosis, UPLC-Q-TOF-MS, and network pharmacology, which have marked advancements in therapeutic and computational approaches. Conclusions: This analysis underscores the dynamic and interdisciplinary nature of this field, highlighting areas for future exploration, particularly underrepresented cognitive disorders and novel therapeutic approaches. Full article

This paper proposes a mathematical description of nitriding atmospheres obtained from a one-component ammonia ingoing atmosphere and a two-component ammonia inlet nitrogen-diluted atmosphere. The Fe-N phase equilibrium diagrams of the nitriding atmosphere in the hydrogen content-temperature (Q-T) system for selected NH₃/N₂ atmosphere compositions are presented. The nitriding atmosphere obtained with different degrees of nitrogen dilution of the ingoing atmosphere was characterized. It has been shown that in processes carried out in nitriding atmospheres obtained from a two-component atmosphere with nitrogen, there is no direct relationship between the value of the nitrogen potential and the degree of dilution of the ingoing atmosphere with nitrogen. It has been shown analytically and confirmed experimentally that with changes in the degree of dilution of ammonia with nitrogen, the hydrogen content of the nitriding atmosphere and, consequently, the nitrogen availability of the nitriding atmosphere change. Using the example of nitriding AISI 52100 steel, it has been experimentally demonstrated that the change in nitrogen availability, caused by a change in the degree of dilution of the ingoing atmosphere with nitrogen, is not accompanied by a change in the value of the nitrogen potential. It has also been shown that the change in the nitrogen availability of the nitriding atmosphere, induced by the change in the composition of the aNH₃/bN₂ ingoing atmosphere, affects the kinetics of nitrogen mass gain in the nitrided layer and the distribution of nitrogen mass between the iron nitride layer and the solution zone. It has also been shown that with the change in nitrogen availability, what changes in addition to the thickness of the iron nitride layer is also the phase composition of the layer. Using gravimetric tests, the mass of nitrogen in the iron nitride layer and the solution zone has been determined. To describe the equilibrium between the NH₃/H₂ atmosphere and nitrogen in the different iron phases, a modified Lehrer diagram in the coordinate system of temperature and hydrogen content in the nitriding atmospheres (T-Q) has been proposed. Full article

Fault diagnosis is one of the most important issues for a modular multilevel converter (MMC). However, conventional solutions are deficient in two aspects. Firstly, they lack the necessary feature information. Secondly, they are incapable of performing open-circuit fault diagnosis of the modular multilevel converter with the requisite degree of accuracy. To solve this problem, an intelligent diagnosis method is proposed to integrate the modal time–frequency diagram and FFT-CNN-BiGRU-Attention. By selecting the phase current and bridge arm voltage as the core fault parameters, the particle swarm algorithm is used to optimize the Variational Modal Decomposition parameters, and the fault signal is decomposed and reconstructed into sensitive feature components. The reconstructed signals are further transformed into modal time–frequency diagrams via continuous wavelet transform to fully retain the time–frequency domain features. In the model construction stage, the frequency–domain features are first extracted using the fast Fourier transform (FFT), and the local patterns are captured through a combination with a convolutional neural network; subsequently, the timing correlations are analyzed using bidirectional gated loop cells, and the Attention Mechanism is introduced to strengthen the key features. Simulations show that the proposed method achieves 98.63% accuracy in locating faulty insulated gate bipolar transistors (IGBTs) in the sub-module, with second-level real-time response capability. Compared with the recently published scheme, it maintains stable performance under complex working conditions such as noise interference and data imbalances, showing stronger robustness and practical value. This study provides a new idea for the intelligent operation and maintenance of power electronic devices, which can be extended to the fault diagnosis of other power equipment in the future. Full article

The present study aims to characterize complex geological structures and significant mineralization using remote sensing and aeromagnetic studies. Structural lineaments play a crucial role in the localization and concentration of mineral deposits. For the first time over the study district, a combination of aeromagnetic data, Landsat 9, ASTER, and PRISMA hyperspectral data was utilized to enhance the characterization of both lithological units and structural features. Advanced image processing techniques, including false color composites, principal component analysis (PCA), independent component analysis (ICA), and SMACC, were applied to the remote sensing datasets. These methods enabled effective discrimination between Phanerozoic rock formations and the complex basement units, which comprise the island arc assemblage, Dokhan volcanics, and late-orogenic granites. The local and deep magnetic sources were separated using Gaussian filters. The Neoproterozoic basement rocks were estimated using the radial average power spectrum technique and the Euler deconvolution technique (ED). According to the RAPS technique, the average depths to shallow and deep magnetic sources are approximately 0.4 km and 1.6 km, respectively. The obtained ED contacts range in depth from 0.081 to 1.5 km. The research area revealed massive structural lineaments, particularly in the northeast and northwest sides, where a dense concentration of these lineaments was identified. The locations with the highest densities are thought to signify more fracturization in the rocks that are thought to be connected to mineralization. According to the automatic lineament extraction methods and rose diagram, NW-SE, NNE-SSW, and N-S are the major structural directions. These trends were confirmed and visually represented through textural analysis and drainage pattern control. The lithological mapping results were validated through field observations and petrographic analysis. This integrated approach has proven highly effective, showcasing significant potential for both detailed structural analysis and accurate lithological discrimination, which may be related to further mineralization exploration. Full article

The roughness of the Earth’s surface dictates the nature of air flow across it. Detailed meteorological data that are necessary to access the aerodynamic roughness ($z_0$) are not widely collected and, as such, the geometry of a surface can be used to estimate $z_0$. Here, we present a novel formulation, and the corresponding computer code, to compute $z_0$ based on the Lettau (1969) geometric approach. The new code produces a mean $z_0$, as well as a histogram of all $z_0$ values for each individual roughness element (e.g., 10 s of thousand for the 1000 × 1000 grids) discretized using watersheds, as well as directional $z_0$ diagrams, which can be matches with the wind rose for the location. The formulation includes two parameters that may optionally be applied to smooth the surface before calculating $z_0$. By calculating $z_0$ as a function of these two parameters, we demonstrate the sensitivity of the $z_0$ value to these parameter choices. Since a large portion of the Earth’s surface is snow covered during some parts of the year, and the roughness of the snow surface varies over the snow season and over space, we apply the code to three snow surface datasets. Each surface is during a different phases of the snowpack. Each surface is evaluated at two resolutions). These surfaces are: fresh snow accumulation (1 m² at 1 and 10 mm), peak accumulation (1 km² at 1 and 10 m) and ablation sun cups (25 m² at 5 and 50 mm). Full article

Polyvinyl chloride (PVC) is one of the most widely used polymers due to its physical properties and versatility. Water consumption of the suspension method is a critical issue that hinders competitiveness. In that case, this study implements water integration through direct recycling, with the aim of minimizing both freshwater consumption and wastewater generation. The source–sink diagram was used to generate the recycled water network, and the integrated process was simulated using software. From simulation data, the water–energy–product (WEP) analysis method was used to assess the process performance, and sustainability indicators for water, energy, and product were evaluated. Fractional water consumption and wastewater production ratio indicators increased to 51.1% and 55.0%, compared to 41% and 54% in the non-integrated process, showing improved water efficiency and cost reduction. The unreacted material reuse index reached 100%, while the production yield was 99.8%, due to effective recycling of unreacted VCM. The use of natural gas and energy integration led to optimal performance in TCE, NGCI, and EECI indicators. However, the ESI indicator was high (3.59 MJ/t) due to energy demands from thermal control equipment for water recirculation. Full article

This study investigates the dynamic behavior and reliability of planar multi-link linkages with clearance in translational pairs. Using the Lagrange multiplier method, a dynamic model that accounts for clearance effects is developed. Furthermore, a reliability model is established by combining the first-order second-moment method with the stress-strength interference theory. Numerical simulations were performed to evaluate the impact of varying clearance sizes and driving speeds on motion errors and system reliability. This study also explores the nonlinear dynamics of the end-effector. The results indicate that increased clearance and higher driving speeds lead to certain changes in motion errors and operational reliability. Phase diagrams and Poincaré maps reveal directional differences in dynamic stability: chaotic motion along the X-direction and periodic oscillations along the Y-direction. These findings provide valuable insights for optimizing mechanism design and enhancing operational reliability. Full article

Li-ion battery recycling is growing with better tech and eco-awareness. Explosions are possible during battery recycling due to their residual voltage. Proper battery discharge is vital to successful recycling. The goal of this study was to investigate a new method for discharging cylindrical batteries, utilizing a saltwater solution and copper conductors and analyzing the impact of both direct and indirect contact between the copper and the battery. A key variable impacting the discharge process was inconsistent spacing between the battery and the copper conductor. In the gap, the saltwater, functioning as an electrolyte solution, created an electrical short circuit, thus causing faster discharge. Because the battery was not in contact with the copper conductor during the discharge process, corrosion of the battery cap and valve occurred, leading to the battery’s anode and cathode elements dissolving into the solution. However, a near-total voltage drop of 99% was observed in the battery, indicating that it was almost completely discharged. Upon making contact with the copper strip during its discharge cycle, the battery exhibited no signs of corrosion. This report details the battery discharge process, encompassing an analysis of the electrochemical reaction, schematic diagrams, and a chemical analysis of the discharge precipitate. Full article