Search Results (7,855)

This study utilizes the Standard k-ε turbulence model and ANSYS CFX software to tackle silt erosion in the top cover clearances of guide vane of the Francis turbine at Genda Power Station (Minjiang River Basin section, 103°17′ E and 31°06′ N) under sediment-laden flow conditions. A numerical simulation of a solid–liquid two-phase flow along the whole flow route was performed under rated operating circumstances to examine the impact of varying guide vane end clearance heights (0.3 mm, 0.5 mm, and 1.0 mm) on internal flow patterns and sediment erosion characteristics. The simulation parameters employed an average sediment concentration of 2.9 kg/m³ and a median particle size of 0.058 mm, indicative of the flood season. The findings demonstrate that augmenting the clearance height intensifies leaky flow and secondary flow, resulting in a 0.49% reduction in efficiency. As the gap expanded from 0.3 mm to 1.0 mm, the leakage flow velocity notably increased to 40 m/s, exacerbating flow separation, enlarging the vortex structures in the vaneless space, and augmenting the sediment velocity gradient and concentration, consequently heightening the risk of erosion. An experimental setup was devised based on the numerical results, and the dynamic resemblance between the constructed test section and the prototype turbine was confirmed for flow velocity, concentration, and Reynolds number. Tests on sediment erosion revealed that the erosion resistance of the anti-sediment erosion material 04Cr13Ni5Mo markedly exceeded that of the base cast steel, especially in high-velocity areas. This study delivers a systematic, quantitative analysis of clearance effects on flow and erosion, along with an experimental wear model specifically for the Gengda Power Station, thereby providing direct theoretical support and engineering guidance for its wear protection strategy and maintenance planning. Full article

Investigating the properties of red clay under the action of dry–wet cycles is crucial for mitigating geological disasters and promoting the sustainable development of geotechnical engineering infrastructure. In this paper, red clay from the Yuanmou dry-hot valley in Yunnan Province was selected as the research subject. The investigation focused on examining the effects of dry–wet cycles on its permeability and shear strength. Samples were prepared by controlling the initial moisture content (8%, 11%, 14%, 17%, and 20% for permeability tests; 11%, 14%, and 17% for strength tests) and initial dry density (1.65 g/cm³, 1.70 g/cm³, 1.75 g/cm³, and 1.80 g/cm³). We conducted variable-head permeability tests and direct shear tests on samples undergoing 1–5 dry–wet cycles. The results demonstrated that (1) the saturated moisture content decreased with the increasing number of dry–wet cycles, with the first cycle showing the most significant decrease (decreasing by approximately 15–25% depending on initial conditions). (2) The permeability coefficient decreased continuously with the number of cycles, exhibiting a transition behavior around the optimum moisture content (14%). Samples with lower initial moisture content (8–14%) showed higher permeability reduction (up to 40% decrease) compared to those with higher initial moisture content (14–20%). (3) The dry–wet cycles lead to a significant attenuation of the shear strength, and the first cycle has the largest reduction. The shear strength parameters of red clay exhibit distinct attenuation patterns. The cohesion decreased exponentially with the number of cycles (total attenuation ≈55–60%), and the internal friction angle decreased linearly (total attenuation ≈20–25%). The total attenuation of cohesion was much larger than the internal friction angle. (4) The degradation mechanism is essentially a multi-scale coupling process of cementation dissolution, pore collapse, and fracture expansion of red clay internal structure. These findings provide critical insights for sustainable engineering design and disaster prevention in regions with similar soil conditions, contributing to the resilience and longevity of infrastructure under changing climatic conditions. Full article

Metformin, an oral antihyperglycemic drug, represents the cornerstone of pharmacological treatment for type 2 diabetes mellitus (T2DM). Its primary glucose-lowering effects are well established, predominantly mediated through the activation of AMP-activated protein kinase (AMPK). This activation leads to a reduction in hepatic glucose production (primarily by inhibiting gluconeogenesis and glycogenolysis) and an increase in peripheral glucose uptake and utilization. Beyond its direct impact on glucose metabolism, metformin also improves insulin sensitivity and has beneficial effects on lipid profiles. Increasingly, research shows that metformin has pleiotropic effects. In addition to its recognized antihyperglycemic action, metformin is emerging as a regulator of cellular processes implicated in aging. Indeed, emerging evidence suggests a potential role of metformin in modulating pathways associated with longevity and ameliorating the symptoms of age-related diseases, including neurodegenerative disorders (such as Alzheimer’s and Parkinson’s diseases), cardiovascular diseases, age-related macular degeneration, and osteoporosis. The proposed mechanisms for these broader effects involve AMPK activation, modulation of the mTOR pathway, reduction of oxidative stress, and promotion of autophagy. After exploring the established role of metformin in T2D, this review provides a comprehensive investigation of its promising applications in the context of age-related diseases, offering valuable insights into its multifaceted therapeutic potential beyond glycemic control. Full article

As automated equipment in PCB manufacturing becomes increasingly reliant on precision hot-air ovens, ensuring operational stability and reducing downtime have become critical challenges. Existing anomaly detection methods, such as Support Vector Machines (SVMs), Deep Neural Networks (DNNs), and Long Short-Term Memory (LSTM) Networks, struggle with high-dimensional dynamic data, leading to inefficiencies and overfitting. To address these issues, this study proposes an innovative anomaly detection system specifically designed for fault diagnosis in PCB hot-air ovens. The motivation is to improve accuracy and efficiency while adapting to dynamic changes in the manufacturing environment. The core innovation lies in the introduction of the Adaptive Temporal Feature Map (ATFM), which dynamically extracts and adjusts key temporal features in real time. By combining ATFM with Bi-Directional Dimensionality Reduction (BDDR) and eXtreme Gradient Boosting (XGBoost), the system effectively handles high-dimensional data and adapts its parameters based on evolving data patterns, significantly enhancing fault detection accuracy and efficiency. The experimental results show a fault prediction accuracy of 99.33%, greatly reducing machine downtime and product defects compared to traditional methods. Full article

A key direction of the development of modern power systems is the application of a continuously increasing number of grid-forming power converters to provide various system services. One of the possible strategies for the implementation of grid-forming control is a control algorithm based on a virtual synchronous generator (VSG). However, at present, the problem of VSG operation under abnormal conditions associated with an increase in output current remains unsolved. Existing current saturation algorithms (CSAs) lead to the degradation of grid-forming properties during overcurrent limiting or reduce the possible range of current output. In this regard, this paper proposes to use the structure of modified current-controlled VSG (CC-VSG) instead of traditional voltage-controlled VSG. A current vector amplitude limiter is used to limit the output current in the CC-VSG structure. At the same time, the angle of the current reference vector continues to be regulated based on the emerging operating conditions due to the voltage feedback in the used VSG equations. The presented simulation results have shown that it was possible to achieve a wide operating range for the current phase from 0° to 180° in comparison with a traditional VSG algorithm. At the same time, the properties of the grid-forming inverter, such as power synchronization without phase-locked loop controller, voltage, and frequency control, are preserved. In addition, in order to avoid saturation of the voltage controller, it is proposed to use a simple algorithm of blocking and switching the reference signal from the setpoint to the current voltage level. Due to this structure, it was possible to prevent saturation of integrators in the control loops and to provide a guaranteed exit from the limiting mode. The results of adding this structure showed a five-second reduction in the overvoltage that occurs when it is absent. A comparison with conditional integration also showed that it prevented lock-up in the limiting mode. The results of experimental verification of the developed prototype of the inverter with CC-VSG control and CSA are also given, including a comparison with the serial model of the hybrid inverter. The results obtained showed that the developed algorithm excludes both the dead time and the load current loss when the external grid is disconnected. In addition, there is no tripping during overload, unlike a hybrid inverter. Full article

This study developed the RATS (Range-Aware Two-Stage) modeling approach to establish mechanistic foundations for feed ratio optimization in fluoroelastomers. Using ¹⁹F NMR spectroscopic analysis, the approach decomposes complex composition–property relationships into sequential processes: monomer feed ratios to NMR-derived structural features, and structural features to properties, enabling mechanistic pathway analysis through quantifiable structural intermediates. Using 52 industrial datasets, RATS achieved an average R² of 0.90 across four property predictions, representing a 0.14 improvement over direct modeling and a 28% reduction in prediction error. The approach identified 72 systematic transmission pathways, including promoting effects of PMVE-series structures (+0.220 influence strength) and inhibitory effects of VDF monomers (−0.219 influence strength), through quantified model parameter analysis. This methodology provides a practical analytical tool for mechanism-driven feed ratio optimization, facilitating the transition from empirical trial-and-error to systematic, data-guided fluoroelastomer formulation. Full article

To address the computational efficiency challenges in two-dimensional (2D) direction-of-arrival (DOA) estimation, a two-stage framework integrating the Nyström approximation with subspace decomposition techniques is proposed in this paper. The methodology strategically integrates the Nyström approximation with subspace decomposition techniques to bridge the critical performance–complexity trade-off inherent in high-resolution parameter estimation scenarios. In the first stage, the Nyström method is applied to approximate the signal subspace while simultaneously enabling construction of a reduced rank covariance matrix, which effectively reduces the computational complexity compared with eigenvalue decomposition (EVD) or singular value decomposition (SVD). This innovative approach efficiently derives two distinct signal subspaces that closely approximate those obtained from the full-dimensional covariance matrix but at substantially reduced computational cost. The second stage employs a sophisticated subspace-based estimation technique that leverages the principal singular vectors associated with these approximated subspaces. This process incorporates an iterative refinement mechanism to accurately resolve the paired azimuth and elevation angles comprising the 2D DOA solution. With the use of the Nyström approximation and reduced rank framework, the entire DOA estimation process completely circumvents traditional EVD/SVD operations. This elimination constitutes the core mechanism enabling substantial computational savings without compromising estimation accuracy. Comprehensive numerical simulations rigorously demonstrate that the proposed framework maintains performance competitive with conventional high-complexity estimators while achieving significant complexity reduction. The evaluation benchmarks the method against multiple state-of-the-art DOA estimation techniques across diverse operational scenarios, confirming both its efficacy and robustness under varying signal conditions. Full article

Organic fertilizer granulation represents a promising strategy for modifying nitrogen (N) release from compost in soil. Nevertheless, there is a lack of large-scale field trials exploring its impact on tobacco production and soil N supply. This research conducted a preliminary study by employing ¹⁵N tracing technology to investigate the effects of granular compost on soil N transformation and supply; on the yield and quality of tobacco leaves; and on the distribution of granular compost-derived N among the different soil N pools and tobacco plant organs. The results revealed that the 2 cm diameter granule organic fertilizer treatment (G2) significantly increased tobacco leaf yield by 15% compared to conventional fertilization (CK). However, the 4 cm diameter granule organic fertilizer (G4) treatment resulted in a reduction in leaf yield. Notably, the quality of tobacco leaves remained unaffected compared to conventional fertilization treatment; the N content ranged from 15 to 25 g kg⁻¹, which was within the high-quality range. The results also indicated that direct N supply to the tobacco from granular compost was limited. The G2 and G4 treatments provided 2.8% and 2.2% of the N in the fertilizer to the tobacco plants, respectively, with more than 93% of the N in the tobacco plants derived from the soil. Therefore, both of these particle sizes of granular compost facilitated the absorption of soil N by tobacco plants. At the end of the growth period, the N content derived from the G4 granular fertilizer in the soil was significantly higher than that from the G2 fertilizer. This may be due to the slower nutrient release mechanism and longer release period of the G4 fertilizer compared to G2. Our results suggested that granulated compost fertilizer (both G2 and G4) has the potential to enhance soil N supply. Despite the elevated nitrogen levels observed in leaves treated with 4 cm diameter granular fertilizer, an integrated assessment of yield performance demonstrates that the 2 cm diameter granular organic fertilizer delivers superior economic benefits. However, G2 may also have a higher potential for N loss. Further investigations under field conditions are necessary to validate the applicability of granular fertilizer of different particle sizes and its specific mechanisms of impact. Full article

Research into floating photovoltaics (FPV) has seen a significant increase in recent years. Still, the observed outputs are poorly quantified, isolated, and occasionally contradictory, with reported cooling-induced efficiency increases varying widely across sources. To address the need for consensus in the field, a systematic literature review (SLR) and meta-analysis were conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to provide a comprehensive overview of the current state-of-the-art in FPV systems. 3751 articles were identified through Boolean queries on three databases (Scopus, Web of Science, and Google Scholar). Using Python programming to ensure objectivity and replicability, the dataset was screened to 109 publications (subject to a manual, full-text review) relating strictly to modelling, simulation, and performance analysis of FPV systems with regard to the observed effect of reduced operating temperature. Focusing on these areas, this study provides a fundamental understanding of the temperature-based performance, as well as insights into the operation and simulation of FPV systems. Consistent temperature reductions were observed between ground-mounted and floating systems. Experimental data on FPV temperature were subject to a regression analysis, and the resulting equation was found to correspond well to a reported relation in the literature. The article concludes with a set of informed research directions to underpin the further development and implementation of FPV technology. Full article

Spinal cord injury (SCI) often results in long-term locomotor impairments, and strategies to enhance functional recovery remain limited. While epidural electrical stimulation (EES) has shown clinical promise, our understanding of the mechanisms by which it improves function remains incomplete. Here, we use genetic tools in an animal model to perform neuromodulation and treadmill rehabilitation in a manner similar to EES, but with the benefit of the genetic tools and animal model allowing for targeted manipulation, precise quantification of the cells and circuits that were manipulated, and the gathering of extensive kinematic data. We used a viral construct that selectively transduces large diameter afferent fibers (LDAFs) with a designer receptor exclusively activated by a designer drug (hM3Dq DREADD; a chemogenetic construct) to increase the excitability of large fibers specifically, in the rat contusion SCI model. As changes in locomotion with afferent stimulation can be subtle, we carried out a detailed characterization of the kinematics of locomotor recovery over time. Adult Long-Evans rats received contusion injuries and direct intraganglionic injections containing AAV2-hSyn-hM3Dq-mCherry, a viral vector that has been shown to preferentially transduce LDAFs, or a control with tracer only (AAV2-hSyn-mCherry). These neurons then had their activity increased by application of the designer drug Clozapine-N-oxide (CNO), inducing tonic excitation during treadmill training in the recovery phase. Kinematic data were collected during treadmill locomotion across a range of speeds over nine weeks post-injury. Data were analyzed using a mixed effects model chosen from amongst several models using information criteria. That model included fixed effects for treatment (DREADDs vs. control injection), time (weeks post injury), and speed, with random intercepts for rat and time point nested within rat. Significant effects of treatment and treatment interactions were found in many parameters, with a sometimes complicated dependence on speed. Generally, DREADDs activation resulted in shorter stance duration, but less reduction in swing duration with speed, yielding lower duty factors. Interestingly, our finding of shorter stance durations with DREADDs activation mimics a past study in the hemi-section injury model, but other changes, including the variability of anterior superior iliac spine (ASIS) height, showed an opposite trend. These may reflect differences in injury severity and laterality (i.e., in the hemi-section injury the contralateral limb is expected to be largely functional). Furthermore, as with that study, withdrawal of DREADDs activation in week seven did not cause significant changes in kinematics, suggesting that activation may have dwindling effects at this later stage. This study highlights the utility of high-resolution kinematics for detecting subtle changes during recovery, and will enable the refinement of neuromechanical models that predict how locomotion changes with afferent neuromodulation, injury, and recovery, suggesting new directions for treatment of SCI. Full article

This study presents a method for deriving closed-form solutions for Lagrange multipliers in worst-case performance optimization (WCPO) beamforming. By approximating the array-received signal autocorrelation matrix as a rank-1 Hermitian matrix using the low-rank approximation theory, analytical expressions for the Lagrange multipliers are derived. The method was first developed for a single plane wave scenario and then generalized to multiplane wave cases with an autocorrelation matrix rank of N. Simulations demonstrate that the proposed Lagrange multiplier formula exhibits a performance comparable to that of the second-order cone programming (SOCP) method in terms of signal-to-interference-plus-noise ratio (SINR) and direction-of-arrival (DOA) estimation accuracy, while offering a significant reduction in computational complexity. The proposed method requires three orders of magnitude less computation time than the SOCP and has a computational efficiency similar to that of the diagonal loading (DL) technique, outperforming DL in SINR and DOA estimations. Fourier amplitude spectrum analysis revealed that the beamforming filters obtained using the proposed method and the SOCP shared frequency distribution structures similar to the ideal optimal beamformer (MVDR), whereas the DL method exhibited distinct characteristics. The proposed analytical expressions for the Lagrange multipliers provide a valuable tool for implementing robust and real-time adaptive beamforming for practical applications. Full article

Climate change continues to threaten global biodiversity, making it essential to assess how keystone species may shift their distributions and to use these findings to inform conservation planning. This study evaluated the current and future habitat suitability of D. macropodum, an important tree species within subtropical evergreen broad-leaved forests in China, using 354 occurrence records and a suite of environmental variables. A parameter-optimized MaxEnt model (calibrated with ENMeval; RM = 4, FC = QHPT) was applied to simulate the species’ present distribution and projected changes under three climate scenarios (SSP126, SSP245, SSP585). The main factors influencing distribution were determined to be moisture and temperature seasonality, with the precipitation of the coldest quarter (Bio19, 36.3%), the mean diurnal range (Bio2, 37.5%), and the precipitation of the warmest quarter (Bio18, 14.2%) jointly contributing 88.0% of the total influence. The model projections indicated a 40.1% reduction in the total number of suitable habitats under high-emission scenarios (SSP585) by the 2090s, including a loss of over 80% of highly suitable areas. Centroid movements also diverged across the scenarios: a southwestern shift under SSP126 and SSP245 contrasted with a southeastern shift under SSP585, with each accompanied by significant habitat fragmentation. Key climate refugia were identified primarily in central Taiwan Province and the mountainous zones of Zhejiang and Fujian Provinces, which should be prioritized for conservation activities. These insights offer a foundational understanding for the conservation of D. macropodum and other ecologically similar subtropical evergreen species. However, direct extrapolation to other taxa should be made cautiously, as specific responses may vary based on differing ecological tolerances and dispersal capacities. Further research is needed to test the generalizability of these patterns across diverse plant functional types. Full article

In this study, Cu(II) complexes containing the bidentate ligand N,N-dimethylethylendiamine (dmen), i.e., [Cu^II(dmen)₂(CH₃COO)₂], [Cu^II(dmen)₂(NO₃)₂], and [Cu^II(dmen)₂Cl₂], were developed to explore molecular catalysis for the oxygen reduction reaction (ORR). Cyclic voltammetry and UV–vis spectroelectrochemical and electrochemical impedance spectroscopy experiments were performed in the absence and presence of oxygen. The UV–vis spectroscopy results suggested that the aforementioned Cu(II) complexes present an octahedral geometry in the solid state; meanwhile, they show a square pyramidal geometry in an aqueous solution. It is proposed that the chemical species [Cu^I(dmen)₂H₂O]⁺ reacts with O₂, exhibiting an outer-sphere electron transfer mechanism. The same UV–vis spectroelectrochemical response obtained with and without O₂ indicated a direct electron transfer from Cu(II) to Cu(I), with the regeneration of catalyst and the absence of other intermediate species. Among the reported compounds, [Cu(dmen)₂(NO₃)₂] exhibited the highest catalytic rate (TOF = 1.3 × 10⁴ s⁻¹). The impedance spectroscopy results showed that the resistance charge transfer (R_ct) of the redox pair Cu^II|Cu^I decreased in the presence of O₂ from 36.391 kΩ to 5.54 kΩ. For a better understanding of the effect of aliphatic amines on the ORR, a comparison with the complex [Cu(1,10-phen)₂NO₃]NO₃ is also presented. Full article

Research Problem and Gap: Live streaming sales rely heavily on streamers, with both genuine and AI-generated virtual streamers gaining popularity. However, these streamer types possess contrasting capabilities. Genuine streamers are superior at building trust and reducing product valuation uncertainty but have limited reach, while virtual streamers excel at broad audience engagement but are less effective at mitigating uncertainty, often leading to higher product return rates. This trade-off creates a critical strategic gap; that is, brand firms lack clear guidance on whether to invest in genuine or virtual streamers or adopt a hybrid approach for their live channels. Objective and Methods: This study addresses this gap by developing a theoretical analytical model to determine a monopolistic brand firm’s optimal streamer strategy among three options: using only a genuine streamer, only a virtual streamer, or a combination of the two (hybrid approach). The researchers model consumer utility, factoring in uncertainty and the streamers’ differential impact on reach, to derive optimal decisions on pricing and streamer selection. Results and Findings: The analysis yields several key findings with direct managerial implications. First, while a hybrid strategy leverages the complementary strengths of both streamer types, its success depends on employing high-quality streamers; in other words, this strategy does not justify settling for inferior talent of either type. Second, employing a virtual streamer requires a moderate price reduction to compensate for higher consumer uncertainty and prevent high profit-eroding return rates. Third, a pure strategy (only genuine or only virtual) is optimal only when that streamer type has a significant cost advantage. Otherwise, the hybrid strategy tends to be the most profitable. Moreover, higher product return costs directly diminish the viability of virtual streamers, making a genuine or hybrid strategy more attractive for products with expensive return processes. Conclusions: The results provide a clear framework for brand firms—that is, the choice of streamer is a strategic decision intertwined with pricing and product return costs. Firms should pursue a hybrid strategy not as a compromise but as a premium approach, use targeted pricing to mitigate the risk of virtual streamers, and avoid virtual options altogether for products with high return costs. Full article

Heart failure (HF) remains a leading cause of morbidity and mortality globally, with increasing prevalence driven by aging populations and comorbidities such as diabetes mellitus. Recent advances have highlighted sodium-glucose cotransporter-2 (SGLT2) inhibitors, particularly empagliflozin and dapagliflozin, as effective agents in HF management across a broad spectrum of ejection fractions. Initially developed for glycemic control in type 2 diabetes, both drugs have demonstrated significant cardiovascular benefits, including reductions in HF hospitalizations and improvements in symptoms and quality of life. Their mechanisms extend beyond glucose lowering, involving natriuresis, osmotic diuresis, improved myocardial energetics, reduced sympathetic activation, and anti-inflammatory effects. While empagliflozin and dapagliflozin share a core renal mechanism via selective SGLT2 inhibition, subtle differences in pharmacokinetics, potency, and tissue selectivity may influence their clinical profiles. Emerging evidence suggests empagliflozin may confer stronger benefits in heart failure with reduced ejection fraction (HFrEF), while dapagliflozin could offer enhanced efficacy in heart failure with preserved ejection franction (HFpEF), although head-to-head comparisons are lacking. This review synthesizes current evidence comparing the mechanisms of action and clinical performance of empagliflozin and dapagliflozin in HF, providing insight into agent selection and future directions in therapy personalization. Full article