Search Results (113)

Following hygiene standards in milk production is essential for making high-quality sour cream, especially when using traditional methods that rely on raw milk. The aim of this study was to determine the physicochemical, microbiological, and sensory quality of artisanal sour cream samples collected from major marketplaces in the wider Zagreb area. On average, the samples contained 27.99% milk fat, 3.30% protein, 34.29% dry matter, 6.51% fat-free dry matter and 3.00% lactose, with considerable variability observed across all components. Microbiological analysis revealed the presence of Staphylococcus aureus in 35.30% of the samples, Enterobacteriaceae in 76.47%, Escherichia coli in 94.11%, Bacillus spp. in 23.53%, and yeasts in 100% of the samples. Listeria monocytogenes and Salmonella spp. were not detected. The sensory analysis of the textural properties showed significant variability in firmness, adhesiveness, viscosity, creaminess, and fizziness. Samples with higher milk fat and dry matter content were rated better for creaminess, viscosity and mouth firmness. Flavour assessments, particularly for cream and diacetyl notes, also varied widely among samples. These findings highlight the complexity of sour cream’s sensory attributes and the significant influence of ingredient composition and processing techniques on appearance, aroma, texture, taste, and flavour. Principal component analysis (PCA) with Varimax rotation simplified the data structure and identified key dimensions of quality variation. Principal component analysis (PCA) revealed that the first principal component (PC1) effectively discriminated the cream samples based on sensory attractiveness and indicators of spoilage and highlighted the association between off-flavour and microbial contamination with inferior characteristics. The second principal component (PC2) captured the differences in physicochemical characteristics and showed a gradient from richer, creamier samples with higher fat content to those with lower acidity and higher freshness. Full article

Atmospheric climate science lacks the capacity to integrate thermodynamics with the gravitational potential of air in a classical quantum theory. To what extent can we identify Carnot’s ideal heat engine cycle in reversible isothermal and isentropic phases between dual temperatures partitioning heat flow with coupled work processes in the atmosphere? Using statistical action mechanics to describe Carnot’s cycle, the maximum rate of work possible can be integrated for the working gases as equal to variations in the absolute Gibbs energy, estimated as sustaining field quanta consistent with Carnot’s definition of heat as caloric. His treatise of 1824 even gave equations expressing work potential as a function of differences in temperature and the logarithm of the change in density and volume. Second, Carnot’s mechanical principle of cooling caused by gas dilation or warming by compression can be applied to tropospheric heat–work cycles in anticyclones and cyclones. Third, the virial theorem of Lagrange and Clausius based on least action predicts a more accurate temperature gradient with altitude near 6.5–6.9 °C per km, requiring that the Gibbs rotational quantum energies of gas molecules exchange reversibly with gravitational potential. This predicts a diminished role for the radiative transfer of energy from the atmosphere to the surface, in contrast to the Trenberth global radiative budget of ≈330 watts per square metre as downwelling radiation. The spectral absorptivity of greenhouse gas for surface radiation into the troposphere enables thermal recycling, sustaining air masses in Lagrangian action. This obviates the current paradigm of cooling with altitude by adiabatic expansion. The virial-action theorem must also control non-reversible heat–work Carnot cycles, with turbulent friction raising the surface temperature. Dissipative surface warming raises the surface pressure by heating, sustaining the weight of the atmosphere to varying altitudes according to latitude and seasonal angles of insolation. New predictions for experimental testing are now emerging from this virial-action hypothesis for climate, linking vortical energy potential with convective and turbulent exchanges of work and heat, proposed as the efficient cause setting the thermal temperature of surface materials. Full article

We develop a symmetry-based variational theory that shows the coarse-grained balance of work inflow to heat outflow in a driven, dissipative system relaxed to the golden ratio. Two order-2 Möbius transformations—a self-dual flip and a self-similar shift—generate a discrete non-abelian subgroup of $\mathrm{PGL}(2,\mathbb{Q}\left(\sqrt{5}\right))$. Requiring any smooth, strictly convex Lyapunov functional to be invariant under both maps enforces a single non-equilibrium fixed point: the golden mean. We confirm this result by (i) a gradient-flow partial-differential equation, (ii) a birth–death Markov chain whose continuum limit is Fokker–Planck, (iii) a Martin–Siggia–Rose field theory, and (iv) exact Ward identities that protect the fixed point against noise. Microscopic kinetics merely set the approach rate; three parameter-free invariants emerge: a $62\%:38\%$ split between entropy production and useful power, an RG-invariant diffusion coefficient linking relaxation time and correlation length ${\mathcal{D}}_{\alpha }={\xi }^z/\tau$, and a $\vartheta ={45}^{\circ }$ eigen-angle that maps to the golden logarithmic spiral. The same dual symmetry underlies scaling laws in rotating turbulence, plant phyllotaxis, cortical avalanches, quantum critical metals, and even de-Sitter cosmology, providing a falsifiable, unifying principle for pattern formation far from equilibrium. Full article

Fluids that exhibit self-rewetting properties, such as aqueous long-chain alcohol solutions, display a unique quadratic relationship between surface tension and temperature and are marked by a positive gradient. This characteristic leads to distinctive patterns of thermocapillary convection and associated interfacial dynamics, setting self-rewetting fluids apart from normal fluids (NFs). The potential to improve heat transfer using self-rewetting fluids (SRFs) is garnering interest for use in various technologies, including low-gravity conditions and microfluidic systems. Our research aims to shed light on the contrasting behaviors of SRFs in comparison to NFs regarding interfacial transport phenomena. This study focuses on the thermocapillary convection in SRF layers with a deformable interface enclosed inside a closed container modeled as a square cavity, which is subject to nonuniform heating, represented using a Gaussian profile for the heat flux variation on one of its sides, in the absence of gravity. To achieve this, we have enhanced a central-moment-based lattice Boltzmann method (LBM) utilizing three distribution functions for tracking interfaces, computing two-fluid motions with temperature-dependent surface tension and energy transport, respectively. Through numerical simulations, the impacts of several characteristic parameters, including the viscosity and thermal conductivity ratios, as well as the surface tension–temperature sensitivity parameters, on the distribution and magnitude of the thermocapillary-driven motion are examined. In contrast to that in NFs, the counter-rotating pair of vortices generated in the SRF layers, due to the surface tension gradient at the interface, is found to be directed toward the SRF layers’ hotter zones. Significant interfacial deformations are observed, especially when there are contrasts in the viscosities of the SRF layers. The thermocapillary convection is found to be enhanced if the bottom SRF layer has a higher thermal conductivity or viscosity than that of the top layer or when distributed, rather than localized, heating is applied. Furthermore, the higher the magnitude of the effect of the dimensionless quadratic surface tension sensitivity coefficient on the temperature, or of the effect of the imposed heat flux, the greater the peak interfacial velocity current generated due to the Marangoni stresses. In addition, an examination of the Nusselt number profiles reveals significant redistribution of the heat transfer rates in the SRF layers due to concomitant nonlinear thermocapillary effects. Full article

Laboratory data from in-cell tests at and near open circuit potentials (OCV) and ex-situ H₂O₂ vapor exposure tests are used to develop a fluoride emission rate (FER) model for a state-of-the-art 12-µm thin, low equivalent weight, long-chain perfluorosulfonic acid (PFSA) ionomer membrane that is mechanically reinforced with expanded PTFE and chemically stabilized with 2 mol% cerium as an anti-oxidant. The anode FER at OCV linearly correlates with O₂ crossover from the cathode and the high yield of H₂O₂ at anode potentials, as observed in rotating ring disk electrode (RRDE) studies. The cathode FER may be linked to the energetic formation of reactive hydroxyl radicals (·OH) from the decomposition of H₂O₂ produced as an intermediate in the two-electron ORR pathway at high cathode potentials. Both anode and cathode FERs are significantly enhanced at low relative humidity and high temperatures. The modeled FER is strongly influenced by the gradients in water activity and cerium concentration that develops in operating fuel cells. Membrane stability maps are constructed to illustrate the relationship between the cell voltage, temperature, and relative humidity for FER thresholds that define H₂ crossover failure by chemical degradation over a specified lifetime. Full article

This article presents a comprehensive study of the mechanical and tribological properties of detonation coatings in the NiCr-Al system. Using the detonation spraying technology, NiCr-Al homogeneous (HC) and gradient coatings (GCs) were produced, and their characteristics were determined. Modern analytical instruments were used in the course of the study. The results showed that the microhardness of the NiCr-Al GC was approximately 30% higher compared to the NiCr-Al HC. According to nanoindentation results, the elasticity modulus and nanohardness of the NiCr-Al GC were twice as high as those of the NiCr-Al homogeneous coating. Tribological tests conducted using the rotational ball-on-disk contact geometry showed that the wear rate of the NiCr-Al GC was significantly lower, while the friction coefficients of both coatings were approximately similar. According to the adhesion strength tests, the strength of the NiCr-Al GC was recorded at 38.7 ± 6.9 MPa, while that of the NiCr-Al HC was approximately 25.4 ± 3.1 MPa. High-temperature tribological tests revealed that the wear resistance of the NiCr-Al GC was 2.5 times higher than that of the NiCr-Al HC. The conducted studies demonstrated that the coating structure, particularly the distribution of elements, has a significant influence on its mechanical and tribological properties. Overall, the NiCr-Al GC exhibited superior mechanical and tribological performance. Full article

Geophysical flows are characterized by rapid rotation. Simulating these flows requires small timesteps to achieve stability and accuracy. Numerical stability can be greatly improved by the implicit integration of the terms that are most responsible for destabilizing the numerical scheme. We have implemented an implicit treatment of the Coriolis force in a rotating spherical shell driven by a radial thermal gradient. We modified the resulting timestepping code to carry out steady-state solving via Newton’s method, which has no timestepping error. The implicit terms have the effect of preconditioning the linear systems, which can then be rapidly solved by a matrix-free Krylov method. We computed the branches of rotating waves with azimuthal wavenumbers ranging from 4 to 12. As the Ekman number (the non-dimensionalized inverse rotation rate) decreases, the flows are increasingly axially independent and localized near the inner cylinder, in keeping with well-known theoretical predictions and previous experimental and numerical results. The advantage of the implicit over the explicit treatment also increases dramatically with decreasing $\mathrm{Ek}$, reducing the cost of computation by as much as a factor of 20 for Ekman numbers of order of ${10}^{-5}$. We carried out continuation for both the Rayleigh and Ekman numbers and obtained interesting branches in which the drift velocity remained unchanged between pairs of saddle–node bifurcations. Full article

In the context of coal mine operations, the assurance of work safety relies heavily on efficient autonomous navigation for rescue robots, yet traditional path planning algorithms such as A and RRT exhibit significant deficiencies in a coal mine environment. Traditional path planning algorithms (such as Dijkstra and PRM) have certain deficiencies in dynamic Spaces and narrow environments. For example, the Dijkstra algorithm has A relatively high computational complexity, the PRM algorithm has poor adaptability in real-time obstacle avoidance, and the A* algorithm is prone to generating redundant nodes in complex terrains. In recent years, research on underground mine scenarios has also pointed out that there are many difficulties in the integration of global planning and local planning. This paper proposes an enhanced A* algorithm in conjunction with the Dynamic Window Approach (DWA) to enhance the efficiency, search accuracy, and obstacle avoidance capability of path planning by optimizing the target function and eliminating redundant nodes. This approach enables path smoothing to be performed. In order to ensure that the requirement of multiple target point detection is realized, an RRT algorithm is proposed to reduce the element of randomness and uncertainty in the path planning process, leading to an increase in the convergence rate and overall performance of the algorithm. The solution to the problem of determining the global optimal path is proposed to be simplified by means of the optimal path planning algorithm based on the gradient coordinate rotation method. In this study, we not only focus on the efficiency of mobile robot path planning and real-time dynamic obstacle avoidance capabilities but also pay special attention to the symmetry of the final path. The findings of simulation experiments conducted within the MATLAB environment demonstrate that the proposed algorithm exhibits a substantial enhancement in terms of three key metrics: path planning time, path length, and obstacle avoidance efficiency, when compared with conventional methodologies. This study provides a theoretical foundation for the autonomous navigation of mobile robots in coal mines. Full article

Voltage withstand tests on stator bars can cause destructive phenomena such as thermal breakdown and flashover discharge on the surface of the anti-corona layer. This study optimizes the anti-corona structure at a stator bar’s end to prevent such failures using a 120 MW water-cooled turbogenerator with a rated voltage of 15.75 kV. For a well-designed anti-corona system, the maximum potential gradient of the stator bar should be lower than the discharge intensity of air corona. In our design, the electric field intensity is maintained below 3.1 kV/cm, and the maximum surface loss in the anti-corona layer is limited to less than 0.6 W/cm². Additionally, the terminal voltage is kept lower than that of flashover voltage at rated conditions. Furthermore, the length of the anti-corona layer should be minimized. The optimization process involves determining the rotation angle of the stator bar, calculating the total length of the anti-corona layer, and analyzing the electric field and loss in the layer at different lengths. The results demonstrate that the optimized anti-corona design effectively reduces the risk of flashover and thermal failure, ensuring stable operation under rated conditions. This manuscript belongs to purely computational experiments. At present, the electrical machinery with 120 MW rated power grade is put into operation steadily. There is a growing requirement for anti-corona. In this manuscript, computing method is used to assist the anti-corona structure design. The electrical machinery insulation is improved by better anti-corona materials. Therefore, the service life of electrical machinery can be prolonged, which is significant in engineering. Full article

Background/Objectives: This study aimed to identify the risk factors for retears after arthroscopic rotator cuff repair (ARCR) and to establish a hierarchy of their importance using machine learning. Methods: This study analyzed 788 primary ARCR cases performed by a single senior surgeon from January 2016 to December 2022. The condition of the repaired supraspinatus was assessed via magnetic resonance imaging (MRI) or sonography within 2 years after surgery. In total, 27 preoperative demographic, objective, and subjective clinical variables were analyzed using five well-established models: Extreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), Neural Network (NN), and logistic regression (LR). The models were trained on an 8:2 split training and test set, with three-fold validation. The primary metric for evaluating model performance was the area under the receiver operating characteristic curve (AUC). The top five influential features were extracted from the best-performing models. Univariate and multivariate LRs were performed independently as a reference. Results: The overall retear rate was 11.9%. The two best-performing prediction models were RF (validation AUC = 0.9790) and XGBoost (validation AUC = 0.9785). Both models consistently identified the tear size in the medial–lateral (ML) and anterior–posterior (AP) dimensions, full-thickness tears, and BMI among the top five risk factors. XGBoost uniquely included female sex, while RF highlighted the visual analogue scale (VAS) pain score. While conventional univariate regression indicated multiple significant factors associated with retears (age, full-thickness tear, AP and ML tear size, biceps conditions, fatty infiltration of three rotator cuff muscles, and atrophy of supraspinatus), multivariate analysis demonstrated that only age and the ML tear size are significant factors. Conclusions: Machine learning models demonstrated enhanced predictive accuracy compared to traditional LR in predicting retears, and the importance of risk factors was derived. Tear size, full-thickness tears, BMI, female sex, and VAS pain score emerged as the most influential risk factors. Full article

The sea surface displays dynamic characteristics, such as waves and various formations. As a result, images of the sea surface usually have few stable feature points, with a background that is often complex and variable. Moreover, the sea surface undergoes significant changes due to variations in wind speed, lighting conditions, weather, and other environmental factors, resulting in considerable discrepancies between images. These variations present challenges for identification using traditional methods. This paper introduces an algorithm based on the phase-consistency model. We utilize image data collected from a specific maritime area with a high-frame-rate surface array infrared camera. By accurately detecting images with identical names, we focus on the subtle texture information of the sea surface and its rotational invariance, enhancing the accuracy and robustness of the matching algorithm. We begin by constructing a nonlinear scale space using a nonlinear diffusion method. Maximum and minimum moments are generated using an odd symmetric Log–Gabor filter within the two-dimensional phase-consistency model. Next, we identify extremum points in the anisotropic weighted moment space. We use the phase-consistency feature values as image gradient features and develop feature descriptors based on the Log–Gabor filter that are insensitive to scale and rotation. Finally, we employ Euclidean distance as the similarity measure for initial matching, align the feature descriptors, and remove false matches using the fast sample consensus (FSC) algorithm. Our findings indicate that the proposed algorithm significantly improves upon traditional feature-matching methods in overall efficacy. Specifically, the average number of matching points for long-wave infrared images is 1147, while for mid-wave infrared images, it increases to 8241. Additionally, the root mean square error (RMSE) fluctuations for both image types remain stable, averaging 1.5. The proposed algorithm also enhances the rotation invariance of image matching, achieving satisfactory results even at significant rotation angles. Full article

Precipitation data from 104 meteorological stations in Inner Mongolia from 1960 to 2018 were analyzed to examine the regionalization and characteristics of precipitation variations. Using rotated empirical orthogonal function (REOF) analysis and K-means clustering, Inner Mongolia was divided into six precipitation subregions: the northeastern Hulunbuir area (subregion I); most of Hinggan League, northern Xilin Gol League, and northwestern Tongliao City (subregion II); most of Tongliao City and Chifeng City and east–central and southern Xilin Gol League (subregion III); southern Xilin Gol League, north–central Ulan Chab City, northern Hohhot City, most of Baotou City and north–central Bayannur City (subregion IV); Ordos City, southern Bayannur, and southeastern Alxa League (subregion V); and west–central Alxa League and parts of western Bayannur City (subregion VI). Precipitation showed a spatial gradient with higher annual averages in the east (400.85 mm in subregion I) and lower averages in the west (90.65 mm in subregion VI). From 1960 to 2018, precipitation exhibited an overall increasing trend consistent across the subregions. However, most regions showed decreasing trends from 1990 to 2010. The rate of precipitation change varied significantly across the subregions, reflecting distinct spatial dynamics. Full article

An approach to achieve nuclear fusion utilizing the formation of high densities of electrons and neutrals is described. The abundance of low energy free electrons produces intense electric fields that reduce the Coulomb barrier in nuclear fusion. Meanwhile, high-density rotating neutrals provide high centrifugal forces to achieve the extreme pressure gradients of electrons and consequent negative electric fields to reduce the ion repulsive Coulombic fields. These high-density neutrals also provide better stability and higher reaction rates. Ion–neutral coupling is responsible for the control of neutral dynamics. Since high-frequency excitations favor the generation of free electrons, pulsed operations are recommended to achieve fusion with higher gains. Full article

As the central component of a pumped storage power station, the pump-turbine frequently enters the hump region during operation, which impacts the safe functioning of the unit. This study investigates the flow patterns at various guide vane openings within the hump area, employing the Omega vortex identification method. The results reveal that transitioning into the hump region from design conditions results in an unsteady flow state in the vaneless space, seriously threatening the stability of the pump-turbine. Notably, at the lowest point in the hump zone, the vaneless space generates high-speed circulation characterized by large velocity gradients and severe flow separation. The region of high turbulent kinetic energy intensifies with increasing guide vane opening. Additionally, low-frequency pressure pulsations become the predominant frequency in the hump zone, and the relative amplitude of these pulsations reach higher values, which is caused by rotating stall. The Omega vortex identification technique illustrates that the vortex structure is minimized during optimal efficiency in the vaneless space. As the flow rate in the hump region decreases, persistent high-energy vortices accumulate in the vaneless space, resulting in a significant increase in vorticity intensity and causing unsteady flow in the pump turbine. Full article

This study investigated the microstructure, microhardness, and residual compressive stress of 14Cr12Ni3Mo2VN martensitic stainless steel treated with high-frequency induction quenching (HFIQ) and laser shock peening (LSP). Using rotating bending corrosion fatigue testing, the corrosion fatigue performance was analyzed. Results show that a microstructural gradient formed after HFIQ and LSP: the surface layer consisted of nanocrystals, the subsurface layer of short lath martensite, and the core of thick lath martensite. A hardness gradient was introduced, with surface hardness reaching 524 Hv_0.1, 163 Hv_0.1 higher than the core hardness. A residual compressive stress field was introduced near the surface, with a maximum residual compressive stress of approximately −575 MPa at a depth of 0.1 mm. Corrosion fatigue results indicate that cycle loading times of samples treated with HFIQ and LSP were 2.88, 2.04, and 1.45 times higher than untreated, HFIQ-only, and LSP-only samples, respectively. Transmission electron microscopy (TEM) characterization showed that HFIQ reduced the lath martensite size, while the ultra-high strain rate induced by LSP likely caused dynamic recrystallization, forming numerous sub-boundaries and refining grains, which increased surface hardness. The plastic strain induced by LSP introduced residual compressive stress, counteracting tensile stress and hindering the initiation and propagation of corrosion fatigue cracks. Full article