Search Results (255)

Developing and identifying the correct reactor model for a reaction system characterized by a high number of reaction pathways and flow regimes can be challenging. In this work, artificial neural networks (ANNs), used in deep learning, are used to develop a hybrid modelling framework for physics-based model discovery in reactions systems. The model discovery accuracy of the framework is investigated considering kinetic model parametric uncertainty, noise level, features in the data structure and experimental design optimization via a differential evolution algorithm (DEA). The hydrodynamic behaviours of both a continuously stirred tank reactor and a plug flow reactor and rival chemical kinetics models are combined to generate candidate physics-based models to describe a benzoic acid esterification synthesis in a rotating cylindrical reactor. ANNs are trained and validated from in silico data simulated by sampling the parameter space of the physics-based models. Results show that, when monitored using test data classification accuracy, ANN performance improved when the kinetic parameters uncertainty decreased. The performance improved further by increasing the number of features in the data set, optimizing the experimental design and decreasing the measurements error (low noise level). Full article

Grassland ecosystems are fundamentally shaped by the complex behaviours of livestock. While most previous studies have monitored grassland health using vegetation indices, such as NDVI and LAI, fewer have investigated livestock behaviours as direct drivers of grassland degradation. In particular, the spatial clustering and temporal concentration patterns of livestock behaviours are critical yet underexplored factors that significantly influence grassland ecosystems. This study investigated the spatiotemporal patterns of livestock behaviours under different grazing management systems and grazing-intensity gradients (GIGs) in Wenchang, China, using high-resolution GPS tracking data and machine learning classification. the K-Nearest Neighbours (KNN) model combined with SMOTE-ENN resampling achieved the highest accuracy, with F1-scores of 0.960 and 0.956 for continuous and rotational grazing datasets. The results showed that the continuous grazing system failed to mitigate grazing pressure when grazing intensity was reduced, as the spatial clustering of livestock behaviours did not decrease accordingly, and the frequency of temporal peaks in grazing behaviour even showed an increasing trend. Conversely, the rotational grazing system responded more effectively, as reduced GIGs led to more evenly distributed temporal activity patterns and lower spatial clustering. These findings highlight the importance of incorporating livestock behavioural patterns into grassland monitoring and offer data-driven insights for sustainable grazing management. Full article

To address the issue of surface glazing that occurs during prolonged polishing with gel tools, this study employs a triethanolamine (TEA)-based polishing fluid system to enhance the self-sharpening capability of the gel polishing disc. The inhibitory mechanism of TEA concentration on disc glazing is systematically analyzed, along with its impact on the gel disc’s frictional wear behaviour. Furthermore, the synergistic effects of process parameters on both surface quality and material removal rate (MRR) of SiC are examined. The results demonstrate that TEA concentration is a critical factor in regulating polishing performance. At an optimal concentration of 4 wt%, an ideal balance between chemical chelation and mechanical wear is achieved, effectively preventing glazing while avoiding excessive tool wear, thereby ensuring sustained self-sharpening capability and process stability. Through orthogonal experiment optimization, the best parameter combination for SiC polishing is determined: 4 wt% TEA concentration, 98 N polishing pressure, and 90 rpm rotational speed. This configuration delivers both superior surface quality and desirable MRR. Experimental data confirm that TEA significantly enhances the self-sharpening performance of gel discs through its unique complex reaction. During the rough polishing stage, the MRR increases by 34.9% to 0.85 μm/h, while the surface roughness S_a is reduced by 51.3% to 6.29 nm. After subsequent CMP fine polishing, an ultra-smooth surface with a final roughness of 2.33 nm is achieved. Full article

Duplex ball bearings are common components in space satellite mechanisms, and their behaviour impacts the overall performance and reliability of these systems. During rocket launches, these bearings suffer high vibrational loads, making their dynamic response essential for their survival. To predict the dynamic behaviour under vibration, simulations and experimental tests are performed. However, published models for space applications fail to capture the variations observed in test responses. This study presents a multi-degree-of-freedom nonlinear multibody model of a hard-preloaded duplex space ball bearing, particularized for this work to the case in which the outer ring is attached to a shaker and the inner ring to a test dummy mass. The model incorporates the Hunt and Crossley contact damping formulation and employs quaternions to accurately represent rotational dynamics. The simulated model response is validated against previously published axial test data, and its response under step, sine, and random excitations is analysed both in the case of radial and axial excitation. The results reveal key insights into frequency evolution, stress distribution, gapping phenomena, and response amplification, providing a deeper understanding of the dynamic performance of space-grade ball bearings. Full article

Many theories describing the flow of viscous fluids in thin lubrication layers during rotor motion inside a stator, including the influence of the convective term in the Navier–Stokes equation, are known and widely used. However, the results of individual studies show some inconsistencies in evaluating the influence of the convective term on the force occurring in the lubrication layer. Here, the effect of the convective term on the force acting on an arbitrarily moving rotor is explained based on a theoretical analysis of the Navier–Stokes equation. It is shown that for a constant fluid density in the case of an arbitrary trajectory of the centre of a non-rotating rotor, the convective term has zero effect on the force on the rotor. A non-zero effect of the convective term may only arise as a result of the spatial distribution of the momentum density at the inlet and outlet surfaces of the lubricating layer or as a result of variable fluid density due to cavitation or the compressibility of the fluid. Thus, the theoretical discussion presented here clarifies the numerical solutions obtained by researchers in the field of hydrodynamic lubrication and allows us to understand the reasons for the numerical behaviour of some simplified models. Full article

In this paper a new generalized fractal equation for studying the behaviour of self-similar beams using the Timoshenko beam theory is introduced. This equation is established in fractal dimensions by applying the concept of fractal continuum calculus $F^{\alpha }$-CC introduced recently by Balankin and Elizarraraz in order to study engineering phenomena in complex bodies. Ultimately, the achieved formulation is a fourth-order fractal single equation generated by superposing a shear deformation on an Euler–Bernoulli beam. A mapping of the Timoshenko principle onto self-similar beams in the integer space into a corresponding principle for fractal continuum space is formulated employing local fractional differential operators. Consequently, the single equation that describes the stress/strain of a fractal Timoshenko beam is solved, which is simple, exact, and algorithmic as an alternative description of the fractal bending of beams. Therefore, the elastic curve function and rotation function can be described. Illustrative examples of classical beams are presented and show both the benefits and the efficiency of the suggested model. Full article

The curing reaction of hydroxyl-terminated polybutadiene (HTPB) solid propellant slurry alters its internal molecular structure, leading to variations in rheological properties. This study investigates the evolution of the rheological behaviour of HTPB propellant slurry during the curing process. Rheological parameters of the slurry at different curing stages were measured using a rotational rheometer, and its time-dependent rheological characteristics were systematically analysed. Building upon the Herschel–Bulkley–Papanastasiou (HBP) viscosity model, a temporal variable was innovatively incorporated to extend the model into the time domain, resulting in the development of the Herschel–Bulkley–Papanastasiou–Wang (HBPW) constitutive viscosity model. Model parameters were determined through experimental data, and the accuracy of the HBPW model was rigorously validated by comparing numerical simulations with experimental results. The findings demonstrate that the HBPW model effectively captures the viscosity variation patterns of HTPB propellant slurry with respect to both shear rate and curing time, exhibiting a minimal discrepancy of 1.7525% between simulations and experimental data. This work establishes a novel theoretical framework for analysing the rheological properties of HTPB propellant slurry, providing a scientific foundation for optimised propellant formulation design and processing techniques. Full article

Visual behaviour in zebrafish, often measured by the optokinetic reflex (OKR), serves as a valuable model for studying aspects of human neurological and ocular diseases and for conducting therapeutic or toxicology assays. Traditional methods for OKR analysis often rely on binarization techniques (threshold-based conversion of images to black and white) or costly software, which limits their utility in low-contrast settings or hypopigmented disease models. Here, we present a novel deep learning pipeline for OKR analysis, using ResNet-50 within the DeepLabCut framework in a Python Version 3.10 environment. Our approach employs object tracking to enable robust eye movement quantification, regardless of variations in contrast or pigmentation. OKR responses were elicited in both wild-type and slc45a2 (albino) mutant zebrafish larvae at 5 days post-fertilisation, using a mini-LED arena with a rotating visual stimulus. Eye movements were recorded and analysed using both conventional software and our deep learning approach. We demonstrate that the deep learning model achieves comparable accuracy to traditional methods, with the added benefits of applicability in diverse lighting conditions and in hypopigmented larvae. Statistical analyses, including Bland–Altman tests, confirmed the reliability of the deep learning model. While this study focuses on 5-day-old zebrafish larvae under controlled conditions, the pipeline is adaptable across developmental stages, pigmentation types, and behavioural assays. With appropriate adjustments to experimental parameters, it could be applied to broader behavioural studies, including social interactions and predator–prey dynamics in ocular and neurological disease models. Full article

Outboard Dynamic-inlet Waterjets (ODW) are axisymmetric units, powered by a self-contained pump, that, by processing a uniform undisturbed streamtube, can operate more efficiently than conventional marine propulsors. This feature also provides methodological convenience, enabling accurate numerical investigations of the system alone using 2D axisymmetric models. Leveraging this property, the present study bridges the gap on the design principles required to tailor ODW geometries across multiple operating conditions. Reynolds-Averaged Navier Stokes (RANS) equations are solved, including turbulence and cavitation models, to draw the propulsor’s characteristic maps and identify two relevant operating points, set by the combination of a specified pump rotational regime with an advancing velocity. Simulations for these in- and off-design conditions are systematically performed over a database of 512 randomly sampled geometric variants. The corresponding results show that optimised shapes improving the inlet Pressure Recovery (PR) and nacelle drag at cruise conditions result in beneficial outcomes also at take-off operations, where lip cavitation may occur. Thus, analysing together the off-design PR and the cruise net force underscores their conflicting behaviour. In fact, while nacelles shortened by $12\%$ can reduce overall drag and enhance nominal net thrust by $2\%$, designs featuring a $34\%$ wider capture area improve off-design PR by over $1.5\%$, albeit at the cost of compromised propulsive efficiency under any operating range. Full article

Wind turbines align with the wind direction and adjust to wind speed by rotating their nacelle and blades using electromechanical or hydraulic actuators. Due to the fact that the rated capacity of wind turbines is increasing and that the actuators are reaching some size limits, the current solution is to install several actuators at each joint until the required torque is reached. The problem with this approach is that, despite the fact the actuators can be selected from the same type and series, they typically have distinct parameters, resulting in different behaviours. The synchronisation of actuators of wind turbines has still not been studied in the specialised literature. Therefore, a control approach for the synchronisation of the pitch actuators is proposed in this work. Two cases are considered: the synchronisation of torque outputs and the synchronisation of position angle. The simulation results indicate that the proposed solution is effective for synchronising actuators, either when they are placed together on the same blade or when they are on separate blades while simultaneously following the collective pitch control command. Full article

A novel over-constrained XYθ_z nano-positioning stage with a high load-bearing capacity is proposed. This serially connected displacement stage adopts an embedded structural design that integrates a translation stage with a rotation stage in series. The Z-axis amplification mechanism employs out-of-plane actuation, realising a compact solution for three-axis independent motion. The hybrid amplification mechanism designed in the translation stage ensures enhanced output displacement and structural stiffness. The hybrid-parallel amplification mechanism comprises a lever-type displacement amplifier and a Scott–Russell displacement amplifier connected in series, which is then connected in parallel with a bridge-type displacement amplifier. An over-constrained mechanism is introduced to impose redundant constraints along the Z-axis, effectively suppressing parasitic displacement in the Z-direction while enhancing resistance to out-of-plane deformation. A quasi-static model of the XYθ_z motion stage was established to comprehensively characterise the deformation behaviour of the stage, which was verified by finite element simulations and experiments on the prototype. The experimental results indicate that the XYθ_z stage achieves a large motion range (up to 152.22 μm × 151.3 μm × 2.885 mrad) while maintaining excellent anti-deformation capability 200 nm at 4 kg loading. Full article

The aim of this study was to investigate the encapsulation of natural food dyes incorporated into liposomes in terms of particle size, rheological and colour properties, zeta potential, and encapsulation efficiency. The liposomes contained dye substances of anthocyanins from freeze-dried raspberry powder (R), copper complexes of chlorophyllins (C), or commercial-grade β-carotene (B). The phospholipid envelope was composed of sunflower lecithin and carboxymethylcellulose sodium salt as a surface stabilizer treated by high-pressure homogenization. The median particle diameter of R and C systems fluctuated around 200 nm, while B systems showed a broader range of 165–405 nm. The rheological results demonstrated a specific flow behaviour pattern dependent on the rotational shear applied, indicating a flow-induced structural change in the dispersions. Samples were characterized by a translucent profile with relatively high lightness, accompanied by a hue angle (h*) typical of the dye encapsulated. The zeta potential was approx. −30 mV, showing electrokinetically stabilized dispersions. The encapsulation efficiency (EE) varied significantly, with the highest EE observed for anthocyanins, ranging from 36.17 to 84.61%. The chlorophyll encapsulation was the least effective, determined in the range between 1.82 and 16.03%. Based on the suitability index, optimal liposomal formulations were evaluated by means of the Central Composite Design (CCD). Full article

Ongoing research on the effectiveness of enrichment at the species, group, and individual levels is beneficial to our growing understanding of animal welfare and behaviour for animals housed in human care. Diversifying the enrichment opportunities offered to animals in facilities such as zoos and aquariums helps to encourage a wide repertoire of species-typical, naturalistic, and rewarding behaviours. The present study aimed to examine the behavioural impact of novel food (ice blocks, gelatine, eggs) and non-food (lavender, clean sheets, mirrors) enrichment strategies on two zoo-housed prides of African lions (Panthera leo) housed in a rotation-based enclosure system at Orana Wildlife Park, New Zealand. The results of the study indicate that, while both forms of enrichment had a behavioural impact, the effects on behaviour varied with the type of enrichment used, both between and within the two categories. Different enrichment strategies varied in their impacts on resting behaviour, locomotion, and exploration levels in the lions. An increased focus on the specific behavioural outcomes of various novel enrichment strategies is essential to expand the efficacy of enrichment programs for future efforts to improve the wellbeing of zoo-housed animals. Full article

This study investigates the effect of Eucomis autumnalis (EA) cellulose on the structural, thermal, and crystallization behaviour of polybutylene succinate (PBS) and polycaprolactone (PCL) composites. X-ray diffraction (XRD) results showed that in both matrices, EA cellulose promoted nucleation, as indicated by increased peak intensity, while differential scanning calorimetry (DSC) showed reduced melting enthalpy, suggesting the formation of smaller, less perfect crystals. In PBS composites, EA cellulose acted as a crystallization disruptor, reducing crystallinity and enthalpy. Moreover, it slightly lowered the melting temperature. This is because EA cellulose contains β-(1→4) glycosidic bonds, which introduce –O– (ether) linkages along its polymer backbone. These linkages allow for a degree of rotational flexibility. When the cellulose is incorporated into PBS, this structural characteristic may contribute to a reduction in T_m, likely by disrupting the crystallization of PBS chains. At 1 wt.% EA cellulose, broader, more intense melting peaks indicated imperfect crystal formation, while higher loadings (3 and 5 wt.%) resulted in narrower, less intense peaks, reflecting reduced crystallinity. These results are consistent with cooling-curve results and SEM images showing structural irregularities. In PCL composites, EA cellulose similarly reduced crystallinity and enthalpy without significantly affecting melting or crystallization temperatures. The decrease in the melting enthalpy from 55.6 J/g to 47.6 J/g suggested the formation of thinner lamellae and less organized crystals, a conclusion supported by stable crystallization temperatures and declining peak intensities in cooling curves. The combination of XRD and DSC data highlighted the dual role of EA cellulose: it enhances nucleation while hindering crystal growth, leading to the formation of more amorphous structures in both PBS and PCL matrices. These findings offer valuable insights into the potential use of EA cellulose as a functional modifier to tailor the properties of biopolymer composites for environmentally friendly, biodegradable applications. Full article

Background: A conceptual shift in healthcare emphasises multimorbidity and multibehaviours as interconnected phenomena, highlighting dose–response associations and sex-specific differences. Data-driven approaches have been suggested for overcoming methodological challenges, of multimorbidity research. By using exploratory factor analysis, this study aimed to identify sex specific lifestyle associative multimorbidity patterns, providing valuable evidence to primary care providers and informing future multimorbidity guidelines. Methods: A retrospective observational study examined the electronic health records of three general practices in the UK between 2015 and 2018. The participants were aged 18+ with lifestyle multimorbidity, having engaged with multiple health risk behaviours. Stratified exploratory factor analysis with oblique rotation was used to identify sex specific lifestyle associative multimorbidity patterns. Results: The study included N = 7560 patients, with females comprising 53.9%. Eight independent lifestyle associative multimorbidity patterns were identified and distributed as follows. For females, three patterns emerged: cardiometabolic–neurovascular spectrum disorders (42.97% variance), respiratory conditions (8.08%), and sensory impairment (5.63%), with 25.4% assigned to these patterns. For males, five patterns were revealed: cardiometabolic–vascular spectrum disorders (34.10%), genitourinary (9.19%), respiratory–vision (8.20%), ocular (5.70%), and neurovascular–gastro–renal syndrome (4.54%), with 43%. Conclusions: We revealed eight different sex-specific lifestyle-associated patterns, implying the need for tailored clinical approaches. The application of exploratory factor analysis yielded clinically valuable and scientifically rigorous multimorbidity patterns. Clinically, the findings advocate for a paradigm shift towards person-centred care, integrating multimorbidity and SNAP multibehaviours to enhance the complexity of inquiry and treatment of high-risk populations. Full article