Search Results (11,991)

Spatial pattern analysis is essential for understanding forest structure and successional dynamics. Focusing on natural secondary forests in the subalpine region of western Sichuan, China, we established two 1-hectare permanent plots to investigate the spatial distribution of dominant tree species and assess the soil’s water-holding properties, aiming to clarify the relationship between species spatial patterns and edaphic conditions. The pioneer species Betula albosinensis exhibited a unimodal diameter distribution with scarce seedling presence, indicating limited regeneration. In contrast, Abies fargesii var. faxoniana showed a typical inverse J-shaped diameter distribution, suggesting stable population recruitment. At fine spatial scales, dominant species generally exhibited aggregated distributions, with A. fargesii var. faxoniana seedlings showing the strongest clumping; however, as the spatial scale increased, distributions tended toward randomness, likely due to self-thinning and density-dependent interactions. Bivariate spatial association analysis revealed that B. albosinensis was positively associated with A. fargesii var. faxoniana and Picea asperata at small scales, suggesting a potential facilitative effect of B. albosinensis on Pinaceae species. Moreover, capillary water-holding capacity was significantly higher in areas with greater conifer dominance, underscoring the strong environmental filtering effect of microhabitat moisture on community spatial structure. Collectively, our results suggest an ongoing mid- to late-successional shift from pioneer broadleaved to shade-tolerant conifer dominance, with concurrent changes in species composition and soil conditions. This study provides empirical insight into spatial successional processes and highlights their ecological implications for hydrological regulation in subalpine secondary forests. Full article

Fault-tolerant strategies have received increasing attention recently, as reliability requirements have become more stringent. This has drawn significant attention to multiphase machines, due to their inherent fault-tolerance capabilities. Although multiphase machines have been extensively studied as motors since the late 1960s, their use as generators is still in its infancy. Moreover, research on their fault-tolerant capabilities and impact on the power grid remains very limited. With the global expansion of the wind energy sector, the continuous increase in turbine capacities, and the shift in wind energy markets toward offshore wind farms, there is a growing need for studies that investigate the integration of multiphase machines with fault-tolerant strategies and that evaluate their performance and impact on the grid. Therefore, this paper aims to investigate a wind energy conversion system (WECS) based on a five-phase permanent magnet synchronous generator (PMSG) and to evaluate its performance under two fault scenarios: a single-phase open-circuit fault and a double-phase open-circuit fault. A fault-tolerant control strategy is applied in both cases to evaluate its effectiveness under varying wind speeds. The study is carried out using simulation tools developed in MATLAB/Simulink. Full article

Background/Objectives: The aim of this study was to evaluate the prevalence of incidental findings in thoracic computed tomography (CT) performed because of COVID-19 and their potential impact on patient management. Methods: This retrospective analysis included 683 CT scans from 327 patients who underwent CT imaging of the thorax with or without the application of intravenous contrast-agents because of the primary indication of COVID-19. Radiological findings were categorized according to the COVID-19 Pneumonia Imaging Classification by four independent readers. Incidental findings were categorized according to a scale ranging from 0 (no patient impairment) to 3b (severe permanent impairment). Results: In the 683 CT-scans, typical COVID-19 findings were present in 273 scans (40.0%), atypical signs in 97 (14.2%), indeterminate findings in 40 (5.9%), and no signs of COVID-19 in 273 (40.0%). Incidental findings were reported in 93 out of 683 cases (13.6%), of which 63 (67.0%) were classified as category 0, 12 (12.8%) as category 1, 9 (9.6%) as category 2a, none (0.0%) as category 2b, 5 (5.3%) as category 3a, and 5 (5.3%) as category 3b. Conclusions: CT scans of the thorax for COVID-19 show a small but significant number of incidental findings that require further investigation. Full article

The recovery of rare earth elements (REEs) from the spent NdFeB magnets has great strategic significance for ensuring the security of critical mineral resources. This process requires scientifically designed separation technologies to ensure high output and purity of the obtained rare earths. Hydrometallurgy has been widely applied to extract REEs from spent permanent magnets. This paper summarizes and reviews hydrometallurgical technologies, mechanisms, and applications for the separation and recovery of REEs and iron (Fe) from the spent permanent magnets. Key methods include: The hydrochloric acid total solution method, where the spent NdFeB is completely dissolved in hydrochloric acid, iron is precipitated and removed, and then REEs are extracted. The hydrochloric acid preferential dissolution method, where spent NdFeB magnets are first fully oxidized by oxidative roasting, converting Fe²⁺ to Fe³⁺, which hydrolyzes to Fe(OH)₃, and is precipitated and removed, allowing for the subsequent extraction of REEs to obtain rare earth oxides. Acid baking and water leaching, where spent NdFeB is calcined with acidification reagents, and the calcined products are dissolved in water to leach out REEs. At the same time, Fe is retained in the leaching residue. Electrolysis in aqueous solution, where Fe is electrolyzed at the anode or deposited at the cathode to separate it from REES. Organic acids leaching, where organic acids dissolve metals through acidolysis and complexation. Bioleaching, which utilizes microorganisms to recover metal through biological oxidation and complexation. Ionic liquid systems, where Fe or REEs are extracted using ionic liquid or leached by deep eutectic solvents. This paper provides an in-depth discussion on the challenges, advantages, and disadvantages of these strategies for recycling spent NdFeB magnets, as well as the leaching and extraction behavior of REEs. It focuses on environmental impact assessment, improving recovery efficiency, and decreasing reagent consumption. The future development direction for recycling spent NdFeB magnets is proposed, and a research idea of proposing a combined process to avoid the drawbacks of a single recycling method is introduced. Full article

Objectives: Dental eruption is a complex process influenced by various factors, including endocrine factors as growth hormone (GH). The aim of this study was to assess differences in the advancement of tooth eruption between growth hormone-deficient (GHD) and idiopathic short-statured (ISS) children and a control group of children with normal growth patterns. Methods: A total of 156 children participated in this study: 78 patients with short stature (50 boys and 28 girls) and 78 healthy and age- and sex-matched control subjects. Each permanent tooth was classified according to its clinical eruption stage by one trained and calibrated dentist. Results: The mean age was 10.22 ± 2.42 years for the study and 10.15 ± 2.45 for the control group. In our study, we observed eruption delay during the early mixed dentition stage. A significant difference was found in the degree of eruption for all incisors and first permanent molars between the GHD before treatment group and the control group (p = 0.045). The difference was apparent at the initial stage of permanent tooth eruption, in the group of children who had not yet initiated growth hormone treatment. The eruption of remaining tooth groups did not differ significantly between the children with growth failure and the control group (p > 0.05). Conclusions: Our findings indicate that the delay in tooth eruption observed in short-statured children, particularly affecting the first permanent molars and incisors, may reflect the direct influence of growth hormone deficiency on early dental development. The clinical relevance of this finding underlines the importance of individualized dental care and careful timing of orthodontic assessments in short-statured patients, especially prior to the initiation of GH therapy. Full article

Thermoset composites are a fast-growing waste stream that resists conventional reusing routes. Water is the principal ageing agent for epoxy-based thermoset materials that bind high-pressure piping, wind-turbine blades and aircraft skins, yet its action is deceptively complex: a rapid, reversible plasticisation is often followed by a far slower, irreversible chemical hydrolysis. Here we bridge that gap to access a reliable diagnosis inspection. Gravimetric immersion tests (from 8 to 93 °C, up to more than a year) and in situ FTIR spectroscopy were performed on four industrial DGEBA networks (two amine-cured matrices and two anhydride-cured matrices that hydrolyse). This 2 + 2 design isolates reversible from irreversible changes and exposes the individual signatures of diffusion, specific sorption and bond scission. The data are rationalised with a compact three-contribution model that superposes Fickian diffusion through nano-voids, adsorption site saturation through hydrogen bonds and a power-law hydrolysis term sharing global Arrhenius parameters. Since the parameters retain clear physical meaning, the approach can be extrapolated to service temperatures, providing a fast, transparent tool for lifetime prediction and for separating recoverable plasticisation from permanent chemical degradation in critical epoxy infrastructure. Full article

This paper presents a cascaded control strategy for neutral-point-clamped three-level (NPC-3L) inverter-fed permanent magnet synchronous motors (PMSMs), integrating continuous-control-set model-predictive control (CCS-MPC) with mid-point voltage regulation and an online Lyapunov-stable neural-network (NN) disturbance observer. The outer CCS-MPC loop optimizes voltage vector application for accurate current tracking and harmonic suppression, while the inner loop balances mid-point voltage by adjusting the dwell times of P/N small-voltage vectors (VVs). The NN-based disturbance observer compensates parameter mismatches in real time, reducing steady-state dq-axis current errors. To validate the effectiveness of the proposed strategy, experiments are conducted using a three-phase PMSM fed by three-phase NPC-3L inverters. Experimental results demonstrate substantial improvements in mid-point voltage balance, current quality, and robustness against model uncertainties. Full article

In this study, we analyze a multi-species mutualistic Lotka–Volterra model with Lévy jumps and regime-switching. A defining feature of the work lies in modeling the random environment through state-dependent switching in an infinite countable state space. Our main objective is to establish the sufficient conditions of the extinction and stochastic permanence of the model. First, we analyze the existence and uniqueness of the model’s solution, followed by an examination of the solution’s stochastic ultimate boundedness. Moreover, the challenges arising from state-dependent switching are addressed using the stochastic comparison method. Due to the presence of the jump component, more complex conditions are required to achieve a finite partition of the countably infinite space. Furthermore, the M-matrix theory is also used to obtain the stochastic permanence property. Finally, two specific examples are provided to illustrate the conclusions in this paper. Full article

Museum collections around the world contain millions of objects related to religion that can be considered classic sources for religious studies. To date, however, there is no method in religious studies for systematically critiquing such objects from museum collections as sources. Religious studies must therefore expand their methods in order to be able to systematically use such objects as sources for their own research. Various examples show that museum objects can only be made accessible for religious studies research with the help of provenance research. The main focus of the selected examples is on dolls with a religious background—or, rather, on museum objects that have been classified as dolls in collections. Using such objects as examples, this article provides insight into the problems of provenance and the resulting consequences. The aim is to use the examples to show how objects find their way into museum collections, what intentions may lie behind the acquisition of such objects, and how and in what context such objects may be presented to the public. The background to such a scientific approach lies in the analysis of the changing perspective on such objects, since the meaning and attribution of an object are never static. Rather, these objects are subject to a permanent change in perspective due to changing social processes. Or they are presented as something they never really were. And all this can be revealed by systematic provenance research. The article is therefore intended as a plea for the expansion of religious studies methods to include provenance research. Full article

Background/Objectives: To report our single-centre experience with the first 100 patients who underwent transcatheter aortic valve replacement (TAVR) with the new balloon-expandable Myval system. We report 3-year outcomes in low- to high-risk TAVR patient populations. Methods: From November 2019 to July 2021, 100 consecutive patients underwent TAVR, and their outcomes were classified according to the Valve Academic Research Consortium 3 definitions. Device performance was assessed using transthoracic echocardiography. Data collection was approved by the local ethical committee. Results: Among the 100 patients, most were male (n = 63), the mean age was 74.7 years, the mean EuroSCORE II score was 4.8 ± 4.9, and the mean Society of Thoracic Surgeons score was 5.6 ± 3.9. All patients were followed up for three years or until death. The rates of all-cause mortality, cardiac mortality and stroke were 28%, 7% and 5%, respectively. After three years, residual moderate aortic regurgitation was detected in eight patients without severe grade, and bioprosthetic valve dysfunction was observed in 17: structural valve deterioration in 10 (only stage 2), non-structural valve deterioration in three (paravalvular leak in one, patient–prosthesis mismatch in two), and endocarditis in four. Definite transcatheter heart valve thrombosis (hypoattenuated leaflet thickening) was not observed. Bioprosthetic valve failure was detected in four patients (stage 1: 1, stage 2: 0, stage 3: 3). After three years of follow-up, survival analysis revealed no significant differences in all-cause mortality, cardiac mortality, or the composite endpoint (including cardiac mortality, stroke and valve-related dysfunction) between patients with bicuspid (BAV) and tricuspid (TAV) aortic valve morphology and across annulus sizes (small, intermediate and large). Conclusions: TAVR resulted in significant and sustained improvements in valve haemodynamics with low rates of valve dysfunction and adverse clinical outcomes over a three-year follow-up period. Valve morphology (BAV vs. TAV) and annulus size did not significantly impact survival, haemodynamic performance, or valve durability. These results support the expanded use of TAVR in diverse patient populations, although extended follow-up is essential to fully establish long-term durability. Full article

Monitoring bottom-hole pressure (BHP) is critical for reservoir management and flow assurance, especially in offshore fields where challenging conditions and production losses are more impactful. However, reliability issues and high installation costs of Permanent Downhole Gauges (PDGs) often limit access to this vital data. Soft sensors offer a cost-effective and reliable alternative, serving as backups or replacements for physical sensors. This study proposes a novel data-driven methodology for estimating flowing BHP using wellhead and topside measurements from plant monitoring systems. The framework employs ensemble methods combined with clustering techniques to partition datasets, enabling tailored supervised training for diverse production conditions. Aggregating results from sub-models enhances performance, even with simpler machine learning algorithms. We evaluated Linear Regression, Neural Networks, and Gradient Boosting (XGBoost and LightGBM) as base models. A case study of a Brazilian Pre-Salt offshore oilfield, using data from 60 wells across nine platforms, demonstrated the methodology’s effectiveness. Error metrics remained consistently below 2% across varying production conditions and reservoir lifecycle stages, confirming its reliability. This solution provides a practical, economical alternative for studies and monitoring in wells lacking PDG data, improving operational efficiency and supporting reservoir management decisions. Full article

Accurate modeling of Brushless DC (BLDC) motors is crucial for the multi-domain simulation of complex electromechanical systems like electric torque tools, especially when high fidelity is required for Model-Based Design (MBD) and controller validation. Standard BLDC models often employ simplifications that may not capture critical operational details. This paper presents a comparative analysis of four distinct BLDC motor simulation models: two based on ready-to-use MATLAB/Simulink/Simscape Electrical library blocks (Specialized Power Systems/Electrical Machines/Permanent Magnet Synchronous Machine and Electromechanical/Permanent Magnet/BLDC) and two custom models developed by the authors at AGH University. The models are evaluated based on their structure, underlying equations, and performance in simulating typical operational scenarios of an electric torque tool. Key assessment criteria include the ability to implement realistic (e.g., tabulated, non-ideal) back-EMF (electromotive force) profiles, incorporate cogging torque, model commutation effects, and flexibility for modification. Simulation results indicate that while all models can be suitable for basic control design, the custom-developed models offer greater flexibility and fidelity in representing detailed motor phenomena such as irregular back-EMF waveforms and cogging torque, making them better suited for advanced, high-precision applications. Conversely, standard library models, particularly the one underlying the PMSM block, exhibit limitations in custom back-EMF implementation. This study concludes by recommending models based on specific application requirements and outlines directions for future enhancements, including thermal modeling and iron loss representation. Full article

The scaling effect of machines from kW to MW greatly affects electromagnetic performance and needs to be investigated for different machines. Therefore, this paper presents a comprehensive comparative study on the intriguing electromagnetic performance of contra-rotating permanent-magnet vernier machines and dual-port, wound-field-excited, flux-switching machines at the MW power level for contra-rotating wind turbine applications. The analysis evaluates both machines across various slot/pole combinations while maintaining constant key design parameters. The electromagnetic performance analysis reveals that the permanent-magnet vernier machine (PMVM) exhibits superior torque and power, with minimal cogging torque compared to the wound-field flux-switching machine (WFFSM). Conversely, the WFFSM outperforms the PMVM in terms of power factor and efficiency. This study provides valuable perspectives on the strengths and weaknesses of each machine, highlighting their potential for contra-rotating turbine and wind power generation. Finally, to justify the findings of the finite element analysis and the proof of concept, an experimental prototype is tested to validate the study. Full article

Biomedical images, whether acquired by techniques such as magnetic resonance imaging (MRI), computed tomography (CT), ultrasound, X-ray, or other methods, are commonly obtained and permanently stored for diagnostic purposes. Therefore, leveraging this large number of images has become essential for the development of intelligent medical diagnostic systems. In this work, we propose a new biomedical image recognition in two stages: the first stage is to introduce a new image feature extraction technique using quaternion Legendre orthogonal moments (QLOMs) to extract features from biomedical images. The second stage is to use radial basis function (RBF) neural networks for image classification to know the type of disease. To evaluate our computer-aided medical diagnosis system, we present a series of experiments were conducted. Based on the results of a comparative study with recent approaches, we conclude that our method is very promising for the detection and recognition of dangerous diseases. Full article

This study presents a novel energy harvesting device that combines piezoelectric and electromagnetic transduction to extract energy from fluid flow within pipelines to supply power to wireless sensor nodes for the digital transformation of pipeline networks. The proposed harvester consisted of a permanent magnet, an unimorph circular piezoelectric plate, an adjustable housing, two wound coils, and a coil holder. In laboratory tests, the harvester demonstrated an ability to produce 831.7 µW of AC power and 680 µW of DC power at a flow pressure of 2.90 kPa and a flow rate of 11.083 L/s. The energy harvester charged a power backup from 1.01 V to 4.49 V in a time duration of 120 min. Additionally, a low-power wireless system for monitoring pipeline pressure was developed and integrated with this energy harvesting system. By incorporating this technology into the digitization of pipeline systems, continuous power generation is possible, ensuring the reliable and autonomous operation of sensors for real-time data collection and monitoring of the pipeline network. The hybrid flow energy harvester surpasses both earlier standalone electromagnetic and piezoelectric flow energy harvesters. Full article