Search Results (144)

The Soft Yoke Mooring (SYM) system is a critical single-point mooring method for Floating Production Storage and Offloading systems (FPSOs) in shallow waters. Its articulated thrust roller bearing operates long-term in harsh marine environments, making it prone to failure and difficult to diagnose. To address the issues of non-stationary signals and fault features submerged in strong noise caused by the bearing’s non-rotational oscillatory motion, this paper proposes an adaptive improved diagnosis scheme based on Minimum Entropy Deconvolution (MED). By optimizing Finite Impulse Response (FIR) filter parameters to adapt to the oscillatory operating conditions and combining joint analysis of time-domain indicators and envelope spectra, precise identification of bearing faults is achieved. Research shows that this method effectively enhances fault impact components. After MED processing, the kurtosis value of the fault signal can be significantly increased from approximately 2.6 to over 8.6. Its effectiveness in noisy environments was verified through simulation. Experiments conducted on a 1:10 scale soft yoke model demonstrated that the MED denoising and filtering signal analysis method can effectively identify damage in the thrust roller bearing of the SYM system under marine conditions characterized by high noise and complex frequencies. This study provides an efficient and reliable method for fault diagnosis of non-rotational oscillatory bearings in complex marine environments, holding significant engineering application value. Full article

Conjugate heat transfer in non-Newtonian fluids is a fundamental phenomenon in thermal management systems. This study investigates the combined effects of magnetic field topology, heat absorption/generation, the thermal conductivity ratio, enclosure inclination, and power-law rheology using the lattice Boltzmann method. The parametric analysis shows that increasing the heat generation coefficient from −5 to +5 reduces the average Nusselt number by up to 97% for the pseudo-plastic fluids and up to 29% for the Newtonian fluids, while entropy generation increases by 44–86% depending on the thermal conductivity ratio. Increasing the inclination angle from 0° to 90° weakens convection and reduces heat transfer by nearly 77%. Magnetic field strengthening (Ha = 0–45) decreases the Nusselt number by 20–55% depending on the barrier temperature. Among all tested conditions, the highest thermal performance (maximum heat transfer and minimum entropy generation) occurs when using a pseudo-plastic fluid (n = 0.75), exhibiting high wall conductivity (TCR = 50) and heat absorption (HAPC = −5), a cold obstacle (${\mathsf{\theta }}_{\mathrm{b}}=0$), and zero inclination (λ = 0°), as well as in the absence of the magnetic field effects. These quantitative insights highlight the controllability of the conjugate heat transfer and irreversibility in the power-law fluids under coupled magnetothermal conditions. Full article

Roof water inrush is a major hazard threatening coal mine safety. This paper addresses the risk of roof water inrush during mining in the shallow-buried Jurassic coalfield of Northern Shaanxi, taking the Guojiawan Coal Mine as a case study. A systematic framework of “identification of main controlling factors–coupling of subjective and objective weighting–GIS-based spatial evaluation” is proposed. An integrated weighting system combining the Fuzzy Analytic Hierarchy Process (FAHP) and the Coefficient of Variation (CV) method is innovatively adopted. Four weight optimization models, including Linear Weighted Method, Multiplicative Synthesis Normalization Method, Minimum Information Entropy Method, and Game Theory Method, are introduced to evaluate 10 main controlling factors, including the fault strength index and sand–mud ratio. The results indicate that the GIS-based vulnerability evaluation model using the Multiplicative Synthesis Normalization Method achieves the highest accuracy, with a Spearman correlation coefficient of 0.9961. This model effectively enables five-level risk zoning and accurately identifies high-risk areas. The evaluation system and zoning results developed in this paper can provide a direct scientific basis for the design of water prevention engineering and precise countermeasures in the Guojiawan Coal Mine and other mining areas with similar geological conditions. Full article

Hydrophilic interaction liquid chromatography (HILIC) is widely used for the analysis of glycans and oligosaccharides, yet the molecular basis of retention remains incompletely understood. In this study, we investigated dextran ladders labelled with 2-aminobenzamide (2-AB) and Rapifluor-MS™ (Waters, Milford, MA, USA) across a wide range of degrees of polymerization (DP 2–15), temperature conditions (10 °C to 70 °C), and gradient programs using a Acquity™ Premier Glycan BEH Amide column (Bridged Ethylene Hybrid, Waters, Milford, MA, USA). Van’t Hoff analysis revealed distinct enthalpic and entropic contributions to retention, allowing identification of a mechanistic transition from enthalpy-dominated docking interactions at low DP to entropy-driven dynamic adsorption at higher DP. This transition occurred reproducibly between DP 4–6, depending on the fluorescent label, while gradient steepness primarily influenced the location of the minimum enthalpy. Molecular dynamics simulations provided additional evidence, showing increased conformational flexibility and end-to-end distance variability for longer oligomers. This finding is consistent with entropy-dominated adsorption accompanied by displacement of structured interfacial water. Together, these results establish a molecular-level framework linking retention thermodynamics, conformational behavior, and solvation effects, thereby advancing our mechanistic understanding of glycan separation in HILIC. Full article

Coal-free zones, particularly scouring zones, reduce recoverable reserves and increase water inrush risk in coal mining. Existing sedimentological, geophysical, and geostatistical methods are often constrained by coring conditions, lithological interpretation accuracy, and geological complexity. Given that well log signals provide the most continuous carriers of geological information, this study integrates Singular Spectrum Analysis (SSA), Maximum Entropy Spectral Analysis (MESA), and Integrated Prediction Error Filter Analysis (INPEFA) to establish a multi-curve framework for analyzing the genesis and logging responses of coal-free zones. A two-stage SSA workflow was applied for noise reduction, and a Trend–Fluctuation Composite (TFC) curve was constructed to enhance depositional rhythm detection. The minimum singular value order (N), naturally derived from SSA-decomposed INPEFA curves, emerged as a quantitative indicator of mine water inrush risk. The results indicate that coal-free zones resulted from inhibited peat-swamp development followed by fluvial scouring and are characterized by dense inflection points and frequent cyclic fluctuations in TFC curves, together with the absence of low anomalies in natural gamma-ray logs. By integrating multi-curve logs, core data, and in-mine three-dimensional direct-current resistivity surveys, the genetic mechanisms and boundaries of coal-free zones were effectively delineated. The proposed framework enhances logging-based stratigraphic interpretation and provides practical support for working face layout and mine water hazard prevention. Full article

This study investigated the production and characterization of avocado oil emulsions generated with a three-fluid nozzle (3FN) and the physicochemical and thermodynamic properties of the resulting microcapsules obtained by spray drying. The emulsions showed a bimodal size distribution with a main peak at 0.893 µm and PDI values below 0.70 indicate a mid-range polydispersity. Despite their shear-thinning behavior, emulsions exhibited limited stability, as indicated by ζ-potential (−23.9 mV) and increasing TSI values. Spray drying with 3FN achieved a yield of 71.7% and an encapsulation efficiency of 57.8%, with moisture content below 4%, meeting commercial requirements. The microcapsules displayed unimodal particle distributions (D[3,2] = 8.38 µm; D[4,3] = 11.14 µm) and irregular spherical morphologies with surface folds and roughness. Adsorption isotherms followed a type II pattern, well described by the GAB model, with monolayer moisture content (0.043–0.060 g H₂O/g solids) defining critical stability conditions. Thermodynamic analyses identified a “minimum entropy zone” corresponding to enhanced structural stability, while glass transition data confirmed that encapsulated oil did not act as a plasticizer. Overall, the use of a three-fluid nozzle enabled the development of avocado oil microcapsules with favorable physical and thermal attributes, supporting their potential for long-term stability in functional food applications. Full article

Understanding the climate change impacts on the geographical distribution of plant species is vital for biodiversity conservation. Lycium ruthenicum, a second-grade protected plant in China, holds considerable medicinal and ecological value; however, its potential habitat distribution under climate change remains uncertain. By utilizing occurrence records and geographical and environmental data, we optimized a maximum entropy model and evaluated the current and future potential habitat suitability of L. ruthenicum in China. The main results were as follows: (1) The distribution of L. ruthenicum was primarily influenced by the precipitation of the warmest quarter, topsoil base saturation, precipitation seasonality, precipitation of the coldest quarter, and minimum temperature of the coldest month. (2) Under the current conditions, the potential suitable area of L. ruthenicum was approximately 2.25 × 10⁶ km² in China, predominantly distributed in Xinjiang, Qinghai, Gansu, Ningxia, and Inner Mongolia. (3) An obvious reduction in the predicted suitable area of L. ruthenicum was found under future climate scenarios, with the centroid primarily shifting northeastward. These findings highlight the potential vulnerability of this medicinally and ecologically important species and underscore the urgent need for targeted conservation strategies to ensure its long-term survival. Full article

Multistage pumps serve as the core power source for fluid transportation, and runaway conditions of multistage pumps as turbines (PATs) may lead to severe consequences. This study investigated the pressure pulsation, flow structure, and impeller transient characteristics of an 11-stage petrochemical pump under runaway conditions. Full-flow numerical simulations at varying speeds analyzed head, efficiency, and entropy production via the entropy diagnostic method. The results showed that total entropy production generally increases with rotational speed, while efficiency first rises then declines, peaking at 78.48% at 4000 r/min. Maximum/minimum pressure pulsation peaks consistently occur at identical stages, with dominant peak amplitudes overall increasing with speed. Pressure coefficient amplitudes decrease with frequency growth, with larger pulsation magnitudes observed at monitoring points closer to impeller outlets. Dominant pressure pulsation peaks exhibit upward trends with increasing rotational speed. Both the blade-passing frequency and its harmonics were detected at 5100 r/min, including the impeller inlet/outlet side and the region near the cutwater within the guide vanes. This study identified the critical threshold of 4800 r/min and pinpointed fatigue risk zones, providing a theoretical foundation for designing and manufacturing high-performing multistage PAT systems under runaway conditions. Full article

In order to solve the problem of random noise in rolling bearing vibration signals under complex working conditions, this paper use a symmetry VMD theory to set up a rolling bearing vibration signal noise reduction processing algorithm using the fusion HPO-VMD and improved wavelet threshold. Based on the theory of variational mode decomposition (VMD), we introduce the hunter–prey optimization (HPO) algorithm to optimize the core parameters of VMD with the minimum envelope entropy as the objective function and obtain the optimal decomposition modes that contain the rolling bearing vibration signal. And then, we propose to use an improved wavelet threshold processing method to denoise the decomposed rolling bearing vibration signal to improve the recognition effect. Through the acquisition and test of the rolling bearing vibration signal, the proposed algorithm is verified; the results show that the method can reduce random noise and avoid the information loss caused by excessive noise reduction and improve the signal-to-noise ratio. Full article

With the rapid development of internet technologies, enhancing security protection for patient information during its transmission has become increasingly important. Compared with traditional image encryption methods, chaotic image encryption schemes leveraging sensitivity to initial conditions and pseudo-randomness demonstrate superior suitability for high-security-demand scenarios like medical image encryption. In this paper, a novel 3D fractional-order memristive Hopfield neural network (FMHNN) chaotic model with a minimum number of neurons is proposed and applied in medical image encryption. The chaotic characteristics of the proposed FMHNN model are systematically verified through various dynamical analysis methods. The parameter-dependent dynamical behaviors of the proposed FMHNN model are further investigated using Lyapunov exponent spectra, bifurcation diagrams, and spectral entropy analysis. Furthermore, the chaotic behaviors of the proposed FMHNN model are successfully implemented on FPGA hardware, with oscilloscope observations showing excellent agreement with numerical simulations. Finally, a medical image encryption scheme based on the proposed FMHNN model is designed, and comprehensive security analyses are conducted to validate its security for medical image encryption. The analytical results demonstrate that the designed encryption scheme based on the FMHNN model achieves high-level security performance, making it particularly suitable for protecting sensitive medical image transmission. Full article

The division of the flood season is of great significance for the precise operation of water conservancy projects, flood control and disaster reduction, and the rational allocation of water resources, alleviating the contradiction of the uneven spatial and temporal distribution of water resources. The single weighting method can only determine the weight of the flood season division indicators from a certain perspective and cannot comprehensively reflect the time-series attributes of the indicators. This study proposes a Flood Season Division Model based on the Goose Optimization Algorithm and Minimum Deviation Combined Weighting (FSDGOAMDCW). The model uses the Goose Optimization Algorithm (GOA) to solve the Minimum Deviation Combination model, integrating weights from two subjective methods (Expert Scoring and G1) and three objective methods (Entropy Weight, CV, and CRITIC). Combined with the Set Pair Analysis Method (SPAM), it realizes comprehensive flood season division. Based on daily precipitation data of the Nandujiang River (1961–2022), the study determines its flood season from 1 May to 30 October. Comparisons show that: ① GOA converges faster than the Genetic Algorithm, stabilizing at T = 5 and achieving full convergence at T = 24; and ② The model’s division results have the smallest Intra-Class Differences, avoiding indistinguishability between flood and non-flood seasons under special conditions. This research aims to support flood season division studies in tropical islands. Full article

This study explores the machinability of Incoloy 800HT (high temperature) under a sustainable lubrication approach, employing a twin-nozzle minimum quantity lubrication (MQL) system with groundnut oil as a green cutting fluid. The evaluation focuses on key performance indicators, including surface roughness, tool flank wear, power consumption, carbon emissions, and chip morphology. Groundnut oil, a biodegradable and nontoxic lubricant, was chosen to enhance environmental compatibility while maintaining effective cutting performance. The Taguchi L₁₆ orthogonal array (three factors and four levels) was utilized to conduct experimental trials to analyze machining characteristics. The best surface quality (surface roughness, Ra = 0.514 µm) was obtained at the lowest depth of cut (0.2 mm), modest feed (0.1 mm/rev), and moderate cutting speed (160 m/min). The higher ranges of flank wear are found under higher cutting speed conditions (320 and 240 m/min), while lower wear values (<0.09 mm) were observed under lower speed conditions (80 and 160 m/min). An entropy-integrated multi-response optimization using the MOORA (multi-objective optimization based on ratio analysis) method was employed to identify optimal machining parameters, considering the trade-offs among multiple conflicting objectives. The entropy method was used to assign weights to each response. The obtained optimal conditions are as follows: cutting speed = 160 m/min, feed = 0.1 mm/rev, and depth of cut = 0.2 mm. Optimized outcomes suggest that this green machining strategy offers a viable alternative for sustainable manufacturing of difficult-to-machine alloys like Incoloy 800 HT. Full article

Friston proposed the Minimum Free Energy Principle (FEP) based on the Variational Bayesian (VB) method. This principle emphasizes that the brain and behavior coordinate with the environment, promoting self-organization. However, it has a theoretical flaw, a possibility of being misunderstood, and a limitation (only likelihood functions are used as constraints). This paper first introduces the semantic information G theory and the R(G) function (where R is the minimum mutual information for the given semantic mutual information G). The G theory is based on the P-T probability framework and, therefore, allows for the use of truth, membership, similarity, and distortion functions (related to semantics) as constraints. Based on the study of the R(G) function and logical Bayesian Inference, this paper proposes the Semantic Variational Bayesian (SVB) and the Maximum Information Efficiency (MIE) principle. Theoretic analysis and computing experiments prove that R − G = F − H(X|Y) (where F denotes VFE, and H(X|Y) is Shannon conditional entropy) instead of F continues to decrease when optimizing latent variables; SVB is a reliable and straightforward approach for latent variables and active inference. This paper also explains the relationship between information, entropy, free energy, and VFE in local non-equilibrium and equilibrium systems, concluding that Shannon information, semantic information, and VFE are analogous to the increment of free energy, the increment of exergy, and physical conditional entropy. The MIE principle builds upon the fundamental ideas of the FEP, making them easier to understand and apply. It needs to combine deep learning methods for wider applications. Full article

Fault location technology is crucial for enhancing the efficiency of fault maintenance and ensuring the safety of the power supply in small current grounding systems. To address the challenge that traditional single-end positioning methods experience when identifying the reflected wave head and that the adaptability of wave head calibration methods is typically limited, a single-end location method of modulus wave velocity differences based on marine predator algorithm optimized multivariate variational mode decomposition (MVMD) and morphological gradient is proposed. Firstly, the minimum comprehensive entropy kurtosis ratio is used as the fitness function, and the marine predator algorithm is used to realize the automatic optimization of the mode number and penalty factor of the multivariate variational mode decomposition. Therefore, with the goal of decomposing the traveling wave characteristic signals with the most significant traveling wave characteristic information and the lowest noise component, the line-mode traveling wave and the zero-mode traveling wave are accurately decomposed. Secondly, the intrinsic mode function component with the smallest entropy kurtosis ratio is selected as the line-mode traveling wave characteristic signal and the zero-mode traveling wave characteristic signal, respectively, and the arrival time of the wave head is accurately calibrated by combining the morphological gradient value. Finally, the fault distance is calculated by the modulus wave velocity difference location formula and compared with the variational mode decomposition-Teager energy operator (VMD-TEO) method and the empirical mode decomposition _first-order difference method. The results show that the proposed method has the highest accuracy of positioning results, and the algorithm time is significantly reduced compared with the VMD-TEO method, and it has strong adaptability to different line types of faults, different fault initial conditions, and noise interference. Full article

As climate change continues to alter species distributions, Pinus bungeana, an endangered conifer of significant ecological and ornamental value, faces heightened vulnerability, underscoring the critical need to understand and predict its future habitat shifts. Here, we used 83 effective geographic distribution records, along with climate, topography, soil, and drought indices, to simulate the potential distribution of suitable ecological niches for P. bungeana under current conditions and across three future time periods (2040–2060, 2060–2080, and 2080–2100) under two shared socioeconomic pathways: SSP126 (low emissions) and SSP585 (high emissions), using the maximum entropy (MaxEnt) model. The results show that the area under the receiver operating characteristic curve (AUC) for all simulations exceeded 0.973, indicating high predictive accuracy. Soil moisture, the minimum temperature of the coldest month, temperature seasonality, isothermality, the precipitation of the wettest quarter, and altitude were identified as key environmental factors limiting the distribution of P. bungeana, with soil moisture and the minimum temperature of the coldest month being the most important factors. Under the current climatic conditions, the potentially suitable ecological niches for P. bungeana were primarily located in Shaanxi Province, southern Shanxi Province, southeastern Gansu Province, northeastern Sichuan Province, Henan Province, and northwestern Hubei Province, covering approximately 75.59 × 10⁴ km². However, under the future climate scenarios, highly suitable areas were projected to contract, with the rate of decline varying significantly between scenarios. Despite this, the total area of potentially suitable ecological niches was predicted to expand in the future periods. Additionally, a pronounced eastward shift in P. bungeana’s distribution was projected, especially under the high-emission SSP585 scenario. These findings provide insights into the potential impacts of climate change on the distribution of P. bungeana, and they offer valuable guidance for its conservation strategies and habitat management in the context of climate change. Full article