Search Results (30)

With the deepening of degradation, the stability and reliability of the degrading system usually becomes poor, which may lead to random jumps occurring in the degradation path. A non-homogeneous jump diffusion process model is introduced to more accurately capture this type of degradation. In this paper, the proposed degradation model is translated into a state–space model, and then the Monte Carlo simulation of the state dynamic model based on particle filtering is employed for predicting the degradation evolution and estimating the remaining useful life (RUL). In addition, a general model identification approach is presented based on maximization likelihood estimation (MLE), and an iterative model identification approach is provided based on the expectation maximization (EM) algorithm. Finally, the practical value and effectiveness of the proposed method are validated using real-world degradation data from temperature sensors on a blast furnace wall. The results demonstrate that our approach provides a more accurate and robust RUL estimation compared to CNN and LSTM methods, offering a significant contribution to enhancing predictive maintenance strategies and operational safety for systems with complex, non-monotonic degradation patterns. Full article

Conventional applications of the Galvanostatic Intermittent Titration Technique (GITT) and EIS for estimating chemical diffusivity in battery electrodes face issues such as insufficient relaxation time to reach equilibrium, excessively long pulse durations that violate the short-time diffusion assumption, and the assumption of sequential electrode reaction and diffusion processes. In this work, a quasi-equilibrium criterion of 0.1 mV h⁻¹ was applied to NMC622 electrodes, yielding 8–9 h relaxations below 3.8 V, but above 3.8 V, voltage decayed linearly and indefinitely, even upon discharging titration, showing unusual nonmonotonic relaxation behavior. The initial 36-s transients of a 10-min galvanostatic pulse and diffusion impedance in series with the electrode reaction yielded consistent diffusivity values. However, solid-state diffusion in spherical active particles within porous electrodes, where ambipolar diffusion occurs in the pore electrolyte with $t_{+}=0.3$, requires a physics-based three-rail transmission line model (TLM). The corrected diffusivity may be three to four times higher. An analytic two-rail TLM approximating the three-rail numerical model was applied to temperature- and frequency-dependent EIS data. This approach mitigates parameter ambiguity and unphysical correlations in EIS. Physics-based EIS enables the identification of multistep energetics and the diagnosis of performance and degradation mechanisms. Full article

Ship weather routing is heavily dependent on weather forecasts. However, the predictive nature of meteorological models introduces an unavoidable level of uncertainty which, if not accounted for, can compromise navigational safety, operational efficiency, and environmental impact. This study examines the temporal degradation of forecast accuracy across certain oceanographic and atmospheric variables, using a six-month dataset for the area of North Atlantic provided by the National Oceanic and Atmospheric Administration (NOAA). The analysis reveals distinct variable-specific uncertainty trends with wind speed forecasts exhibiting significant temporal fluctuation (RMSE increasing from 0.5 to 4.0 m/s), while significant wave height forecasts degrade in a more stable and predictable pattern (from 0.2 to 0.9 m). Confidence intervals also exhibit non-monotonic evolution, narrowing by up to 15% between 96–120-h lead times. To address these dynamics, a Python-based framework combines distribution-based modeling with calibrated confidence intervals to generate uncertainty bounds that evolve with forecast lead time (R² = 0.87–0.93). This allows uncertainty to be quantified not as a static estimate, but as a function sensitive to both variable type and prediction horizon. When integrated into routing algorithms, such representations allow for route planning strategies that are not only more reflective of real-world meteorological limitations but also more robust to evolving weather conditions, demonstrated by a 3–7% increase in travel time in exchange for improved safety margins across eight test cases. Full article

To explore how the water–cement ratio affects the mechanical behavior of concrete subjected to freeze–thaw cycles, four sets of concrete samples with water–cement ratios of 0.41, 0.44, 0.47, and 0.50 were prepared for laboratory analysis. These samples underwent varying numbers of freeze–thaw cycles (0, 10, 20, and 30) before being tested using the split Hopkinson pressure bar (SHPB) system for dynamic compression. The experimental data show that the mass of the concrete specimens follows a non-monotonic trend during freeze–thaw cycling, initially rising and then gradually declining. Simultaneously, key dynamic mechanical properties, such as compressive strength and elastic modulus, markedly deteriorate, as evidenced by rightward shifts in the stress–strain curves. Importantly, the extent of degradation differs notably depending on the water–cement ratio. Additional analysis highlights a strong association between the fractal nature of the fracture patterns and the effects of freeze–thaw cycles: under consistent freeze–thaw conditions not only does the fractal dimension consistently increase with the number of cycles, but it also positively correlates with the water–cement ratio. Full article

The hydrolysis of proteins by proteases (proteolysis) plays a significant role in biology and food science. Despite the importance of proteolysis, a universal quantitative model of this phenomenon has not yet been created. This review considers approaches to modeling proteolysis in a batch reactor that take into account differences in the hydrolysis of the individual peptide bonds, as well as the limited accessibility (masking) for the enzymes of some hydrolysis sites in the protein substrate. Kinetic studies of the proteolysis of β-casein and β-lactoglobulin by various proteolytic enzymes throughout the whole degree of hydrolysis are reviewed. The two-step proteolysis model is regarded, which includes demasking of peptide bonds as a result of opening of the protein structure at the first stage, then hydrolysis of the demasked peptide bonds. To determine the kinetics of demasking, the shift in Trp fluorescence during opening of the protein substrate is analyzed. Two stages of demasking and secondary masking are also considered, explaining the appearance of unhydrolyzed peptide bonds at the end of proteolysis with decreasing enzyme concentrations. Proteolysis of a nanosized substrate is considered for the example of tryptic hydrolysis of β-CN micelles, leading to the formation and degradation of new nanoparticles and non-monotonic changes in the secondary protein structures during proteolysis. Full article

To investigate the mechanical properties and microstructure evolution of P92 steel during long-term service, the operated P92 main steam pipes from the first ultra-supercritical units in China were sectioned into samples representing various service durations and stresses (0# (as-received state, 1# (82,000 h, 67.3 MPa), 2# (85,000 h, 78.0 MPa), and 3# (100,000 h, 80.3 MPa)). Thereafter, a comprehensive assessment of their mechanical properties, including tensile strength, impact, hardness, and creep resistance, as well as a detailed microstructure analysis, was carried out. The effect of stress on the aging of material properties during operation is discussed. The results show that the circumferential stress caused by the increase in the internal steam pressure can significantly promote the creep life consumption of P92 steel, resulting in the degradation of mechanical properties and the expedited aging of the microstructure. The R_p0.2 and R_m of the P92 main steam pipe at room temperature and 605 °C decreased with the service time increase, reflecting the influence of stress in operation, which is expected to be used for the residual life evaluation of P92 steel. The relationship between the impact absorption energy (FATT50), Brinell hardness, and the operating time of P92 operating pipes is non-monotonic, indicating that these parameters are not sensitive indicators of material aging due to stress. The evaluation of performance degradation in P92 operating pipes due to stress-induced aging is not reliably discernible through optical metallography alone. To achieve a thorough assessment, the use of transmission electron microscopy (TEM) is essential. Full article

In steel production, defect detection is crucial for preventing safety risks, and improving the accuracy of steel defect detection in industrial environments remains challenging due to the variable types of defects, cluttered backgrounds, low contrast, and noise interference. Therefore, this paper introduces a steel surface defect detection model, DBCW-YOLO, based on YOLOv5. Firstly, a new feature fusion strategy is proposed to optimize the feature map fusion pair model using the BiFPN method to fuse information at multiple scales, and CARAFE up-sampling is introduced to expand the sensory field of the network and make more effective use of the surrounding information. Secondly, the WIoU uses a dynamic non-monotonic focusing mechanism introduced in the loss function part to optimize the loss function and solve the problem of accuracy degradation due to sample inhomogeneity. This approach improves the learning ability of small target steel defects and accelerates network convergence. Finally, we use the dynamic heads in the network prediction phase. This improves the scale-aware, spatial-aware, and task-aware performance of the algorithm. Experimental results on the NEU-DET dataset show that the average detection accuracy is 81.1, which is about (YOLOv5) 6% higher than the original model and satisfies real-time detection. Therefore, DBCW-YOLO has good overall performance in the steel surface defect detection task. Full article

This study investigates innovative approaches to improve the quality and aroma characteristics of Muscat Hamburg wine production by substituting the conventional Saccharomyces cerevisiae yeast with an efficient fermentation strain of Schizosaccharomyces pombe. The typical use of S. cerevisiae in Muscat Hamburg wine often leads to uniformity and prolonged processing times, requiring subsequent malolactic fermentation to degrade excessive malic acid. The study advocates for the replacement of S. cerevisiae with a specific S. pombe strain, Sp-410, isolated from the fermented grains of sauce-flavor Baijiu, a Chinese spirit. Muscat Hamburg wine fermented with the S. pombe strain demonstrates decreased malic acid levels, offering a potential alternative to malolactic fermentation. However, exclusive S. pombe fermentation may result in an overproduction of acetic acid metabolites, leading to a monotonous taste. In response, the study proposes a mixed fermentation approach, combining the S. pombe strain with a Saccharomyces uvarum strain and a non-Saccharomyces yeast, Torulaspora delbrueckii. The optimized mixed fermentation strategies (M:SP+TD and M60SP+TD) involve specific proportions and intervals of inoculation, aiming to enhance the quality and aroma complexity of Muscat Hamburg wine. In conclusion, this research contributes to advancing the production of high-quality Muscat Hamburg wines, utilizing S. pombe as the primary yeast strain and implementing mixed fermentation methodologies. Full article

(1) Background: A new probabilistic physico-chemical model of the drifting key parameter of measuring equipment is proposed. The model allows for the integrated consideration of degradation processes (electrolytic corrosion, oxidation, plastic accumulation of dislocations, etc.) in nodes and elements of measuring equipment. The novelty of this article lies in the analytical solutions that are a combination of the Fokker–Planck–Kolmogorov equation and the equation of chemical kinetics. The novelty also consists of the simultaneous simulation and analysis of probabilistic, physical and chemical processes in one model. (2) Research literature review: Research works related to the topic of the study were analyzed. The need for a probabilistic formulation of the problem is argued, since classical statistical methods are not applicable due to the lack of statistical data. (3) Statement of the research problem: A probabilistic formulation of the problem is given taking into account the physical and chemical laws of aging and degradation. (4) Methods: The author uses methods of probability theory and mathematical statistics, methods for solving the stochastic differential equations, the methods of mathematical modeling, the methods of chemical kinetics and the methods for solving a partial differential equations. (5) Results: A mathematical model of a drifting key parameter of measuring equipment is developed. The conditional transition density of the probability distribution of the key parameter of measuring equipment is constructed using a solution to the Fokker–Planck–Kolmogorov equation. The results of the study on the developed model and the results of solving the applied problem of constructing the function of the failure rate of measuring equipment are presented. (6) Discussion: The results of comparison between the model developed in this paper and the known two-parameter models of diffusion monotonic distribution and diffusion non-monotonic distribution are discussed. The results of comparison between the model and the three-parameter diffusion probabilistic physical model developed by the author earlier are also discussed. (7) Conclusions: The developed model facilitates the construction and analysis of a wide range of metrological characteristics such as measurement errors and measurement ranges and acquisition of their statistical estimates. The developed model is used to forecast and simulate the reliability of measuring equipment in general, as well as soldered joints of integrated circuits in special equipment and machinery, which is also operated in harsh conditions and corrosive environments. Full article

Ballast is coarse aggregate with particle size normally ranging from 10 mm to 65 mm. Upon repeated train loading, ballast deteriorates in the form of either continuous abrasion of sharp corners or size degradation, which have been reported as the fundamental cause for the instability of railway tracks. In this study, the splitting behavior of ballast grain with varying particle sizes under diametrical compression was examined to investigate the size effect and the Weibull characteristics of ballast tensile strength; a Weibull modulus of 2.35 was measured for the tested granite ballast. A series of large-scale monotonic triaxial tests on ballast aggregates having various size gradings was performed to study the effect of particle gradation on the mechanical behavior of ballast. The results show that compared to mono-sized uniformly distributed aggregates, non-uniformly distributed aggregates generally have greater shear strength, larger peak friction angle, 50% strength modulus, and greater volumetric dilation. The ballast aggregate conforming to the recommended PSD as per current standards exhibited the most superior mechanical performance, possessing the greatest shear strength, peak friction angle, and 50% strength modulus. Micromechanical analysis showed that aggregates with larger d₅₀ values have higher coordination numbers, inter-particle contact forces, and higher anisotropy level of contact normals, thus causing a greater possibility of particle breakage during shearing. Full article

For the synthesis of ionogels containing microcrystalline cellulose (MCC) and Na-bentonite (Na-Bent), ionic liquid (IL) 1-butyl-3-methylimidazolium acetate was used as an MCC solvent. Characterization and research of the physicochemical properties of the synthesized materials were carried out using methods such as SEM, WAXS, thermal analysis, FTIR, conductometry, and viscometry. WAXS analysis showed an increase in the interlayer distance of Na-bentonite in composites due to the intercalation of IL molecules. Based on the data on the characteristic temperatures of thermal degradation, enhanced thermal stability of triple IL/Na-Bent/MCC ionogels was revealed compared to that for cellulose-free systems. It was found that the electrical conductivity of both triple IL/Na-Bent/MCC and binary IL/MCC ionogels was non-monotonous. The data obtained can be used in the formation of multifunctional coatings with enhanced thermal stability. Full article

Drought is one of the major climate disasters leading to forest degradation in dryland mountains. Hence, revealing the response of forest resilience to drought is crucial to predict forest succession in dryland mountains under future global warming. Here, we chose the Qilian Mountains as the study area and calculated the recovery time and drought intensity along elevation from 1982 to 2020 using the Leaf Area Index (LAI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Then, the forest resilience to drought was calculated using the area of an exponentially fitted curve between drought intensity and corresponding recovery time. Finally, the dominant climate factors underlying altitude differentiation of forest resilience were analyzed using a random forest (RF) regression model, and correlations were determined based on a generalized additive model (GAM). The results indicate that forests in the elevation range of 2600–3900 m exhibited faster recovery rates and greater resilience compared to those in 1700–2600 m. The attributional analysis shows that altitudinal differentiation of forest resilience to drought was mainly constrained by precipitation with a non-monotonic correlation, and resilience was strongest when monthly precipitation reaches 30 mm. In terms of the occurrence of historical drought events, increased potential evapotranspiration improved resilience in the elevation range of 2600–3900 m and enhanced cloud cover initially enlarged the resilience and then decreased it in the elevation range of 3000–3400 m and 3400–3900 m, with resilience being strongest when cloud cover reached 24% and 33%, respectively. Under future climate change, global warming will further exacerbate the drought impact in arid regions, increasing the risk of primary forest collapse. The results of this study provide a scientific basis for predicting the potential changes in vegetation resilience and developing policies for ecological protection in dryland mountains, and we will take addressing the difficult study of the quantitative effects of tree species on resilience altitude differentiation based on ecosystem scales as our future direction. Full article

The Yellow River Delta wetlands in the Yellow River Delta National Nature Reserve are facing serious degradation due to water scarcity and soil salinization. This study aims to investigate the mechanism of wetland degradation by analyzing the small-scale distribution of soil nutrients and preferential flow transport patterns in the Robinia Pseudoacacia community, which is a typical vegetation community in degraded wetlands. Soil physical and chemical properties based on field staining experiments were analyzed, and indoor solute penetration experiments were conducted to investigate the distribution of soil nutrients and hydrological characteristics. The results showed that the contents of soil organic carbon, organic matter, total nitrogen, and available phosphorus decreased with increasing soil depth, with higher contents in the preferential flow area than in the matrix flow area. Soil organic carbon, organic matter, total nitrogen, total phosphorus, and available phosphorus showed positive correlations with each other, while soil pH and conductivity exhibited negative correlations with the above nutrients. The efflux rate of the Acacia community exhibited a gradual decline as soil depth increased, and the relative concentration of the solution exhibited a non-monotonic pattern of decrease, increase, and subsequent decrease with increasing soil depth. The findings could provide valuable guidance for the restoration and management of degraded wetlands in the Yellow River Delta. Full article

In our work, the model of self-consistent electron–deformation–diffusion effects in thin films grown on substrate with the mismatch of lattice parameters of the contacting materials is constructed. The proposed theory self-consistently takes into account the interaction of the elastic field (created by the mismatch of lattice parameters of the film and the substrate, and point defects) with the diffusion processes of point defects and the electron subsystem of semiconductor film. Within the framework of the developed model, the spatial distribution of deformation, concentration of defects, conduction electrons and electric field intensity is investigated, depending on the value of the mismatch, the type of defects, the average concentrations of point defects and conduction electrons. It is established that the coordinate dependence of deformation and the concentration profile of defects of the type of stretching (compression) centers, along the axis of growth of the strained film, have a non-monotonic character with minima (maxima), the positions of which are determined by the average concentration of point defects. It is shown that due to the electron–deformation interaction in film with a lattice parameter mismatch, the spatial redistribution of conduction electrons is observed and n-n+ transitions can occur. Information about the self-consistent spatial redistribution of point defects, electrons and deformation of the crystal lattice in semiconductor materials is necessary for understanding the problems of their stability and degradation of nano-optoelectronic devices operating under conditions of intense irradiation. Full article

Mitochondrial pyruvate dehydrogenase complex (PDHC) is essential for brain glucose and neurotransmitter metabolism, which is dysregulated in many pathologies. Using specific inhibitors of PDHC in vivo, we determine biochemical and physiological responses to PDHC dysfunction. Dose dependence of the responses to membrane-permeable dimethyl acetylphosphonate (AcPMe₂) is non-monotonous. Primary decreases in glutathione and its redox potential, methionine, and ethanolamine are alleviated with increasing PDHC inhibition, the alleviation accompanied by physiological changes. A comparison of 39 brain biochemical parameters after administration of four phosphinate and phosphonate analogs of pyruvate at a fixed dose of 0.1 mmol/kg reveals no primary, but secondary changes, such as activation of 2-oxoglutarate dehydrogenase complex (OGDHC) and decreased levels of glutamate, isoleucine and leucine. The accompanying decreases in freezing time are most pronounced after administration of methyl acetylphosphinate and dimethyl acetylphosphonate. The PDHC inhibitors do not significantly change the levels of PDHA1 expression and phosphorylation, sirtuin 3 and total protein acetylation, but increase total protein succinylation and glutarylation, affecting sirtuin 5 expression. Thus, decreased production of the tricarboxylic acid cycle substrate acetyl-CoA by inhibited PDHC is compensated by increased degradation of amino acids through the activated OGDHC, increasing total protein succinylation/glutarylation. Simultaneously, parasympathetic activity and anxiety indicators decrease. Full article