Search Results (1,564)

The placement of hydraulic elements in existing pool-type fishways to make them more suitable for Cyprinid fish is an issue of increasing interest in fishway research. Hydrodynamic characteristics and fish behavior at the representative pool of the fishway with bottom orifices and notches were assessed at the Dagdelen hydropower plant in the Ceyhan River Basin, Türkiye. Three-dimensional velocity measurements were taken in the pool of the fishway using an Acoustic Doppler velocimeter. The measurements were taken with and without a brush block at two different vertical distances from the bottom, which were below and above the level of bristles tips. A computational fluid dynamics (CFD) analysis was conducted for the studied fishway. The numerical model utilized Large Eddy Simulation (LES) combined with the Darcy–Forchheimer law, wherein brush blocks were represented as homogenous porous media. Our results revealed that the relative submergence of bristles in the brush block plays a very important role in velocity and Reynolds shear stress (RSS) distributions. After the placement of the submerged brush block, flow velocity and the lateral RSS component were reduced, and a resting area was created behind the brush block below the bristles’ tips. Fish movements in the pool were recorded by underwater cameras under real-time operation conditions. The heatmap analysis, which is a 2-dimensional fish spatial presence visualization technique for a specific time period, showed that Capoeta damascina avoided the areas with high turbulent fluctuations during the tests, and 61.5% of the fish presence intensity was found to be in the low Reynolds shear regions in the pool. This provides a clear case for the real-world ecological benefits of retrofitting existing pool-weir fishways with such flexible hydraulic elements. Full article

Thermal wick-debinding, commonly used in low-pressure injection molding, remains challenging due to complex interactions between binder transport, capillary forces, and thermal effects. This study presents a numerical simulation of binder removal kinetics by coupling Darcy’s law with the Phase Transport in Porous Media interface in COMSOL Multiphysics. The model was validated and subsequently used to study the influence of key debinding parameters. Contrary to the Level Set method, which predicts isolated binder clusters, the Multiphase Flow in Porous Media method proposed in this work more accurately reflects the physical behavior of the process, capturing a continuous binder extraction throughout the green part and a uniform binder distribution within the wicking medium. The model successfully predicted the experimentally observed decrease in binder saturation with increasing debinding temperature or time, with deviation limited 3–10 vol. % (attributed to a mandatory brushing operation, which may underestimate the residual binder mass). The model was then used to optimize the debinding process: for a temperature of 100 °C and an inter-part gap distance of 5 mm, the debinding time was minimized to 7 h. These findings highlight the model’s practical utility for process design, offering a valuable tool for determining optimal debinding parameters and improving productivity. Full article

Titanium is widely recognized as an interesting material for electrodes due to its excellent corrosion resistance, mechanical strength, and biocompatibility. However, further functionalization is often necessary to impart advanced interfacial properties, such as selective ion transport or stimuli responsiveness. In this context, the integration of smart polymers, such as poly(2-(dimethylamino)ethyl methacrylate) (PDMAEMA)—noted for its dual pH- and thermo-responsive behavior—has emerged as a promising approach to tailor surface properties for next-generation devices. This work compares two covalent immobilization strategies for PDMAEMA on titanium: the “graft-to” method, involving the attachment of pre-synthesized polymer chains, and the “graft-from” method, based on surface-initiated polymerization. The resulting materials were characterized with size exclusion chromatography (SEC) for molecular weight, Fourier-transform infrared spectroscopy (FTIR) for chemical structure, scanning electron microscopy (SEM) for surface morphology, and contact angle measurements for wettability. Electrochemical impedance spectroscopy and polarization studies were used to assess electrochemical performance. Both strategies yielded uniform and stable coatings, with the mode of grafting influencing both surface morphology and functional stability. These findings provide valuable insights into the development of adaptive, stimuli-responsive titanium-based interfaces in advanced electrochemical systems. Full article

Engineering innovations play a critical role in achieving the United Nations’ Sustainable Development Goals, especially in human–robotic interaction and precise engineering. For the robot, writing Chinese calligraphy with hairy brush pen is a form of precision operation. Existing writing trajectory control models mainly focus on writing trajectory models, and the fine-grained trajectory control model based on brush strokes is not studied. The problem of how to establish writing trajectory control based on brush stroke model needs to be solved. On the basis of the proposed composite-curve-dilation brush stroke model (CCD-BSM), this study investigates the control methods of intelligent calligraphy robots and proposed fine-grained writing trajectory control models that conform to the rules of brush calligraphy to reflect the local writing characteristics. By decomposing and refining each writing process, control models in the process of brush movement are analyzed and modeled. According to the writing rules, fine-grained writing trajectory control models of strokes are established based on the CCD-BSM. The parametric representations of the control models are built for the three stages of initiation, execution, and completion of strokes writing. Experimental results demonstrate that the proposed fine-grained control models can exhibit excellent performances in basic strokes and Chinese characters with better writing capabilities. Compared with existing models, the writing results demonstrate the advantages of our proposed model in terms of high average similarity with two quantitative indicators Cosine similarity (CSIM) and Structural similarity index measure (SSIM), which are 99.54% and 97.57%, respectively. Full article

Camellia oleifera is one of the four largest woody oil species in the world, with more than 5 million hectares planted in China alone. Reducing bud damage and improving harvesting net rate and efficiency have become the key challenges to mechanized harvesting of Camellia oleifera fruits. This paper presents a novel comb-spiral impact harvesting device primarily composed of four parts, which are lifting mechanism, picking mechanism, rotating mechanism, and tracked chassis. The workspace of the four-degree-of-freedom lifting mechanism was simulated, and the harvesting reachable area was maximized using MATLAB R2021a software. The picking mechanism, which includes dozens of spirally arranged impact pillars, achieves high harvesting efficiency through impacting, brushing, and dragging, while maintaining a low bud shedding rate. The rotary mechanism provides effective harvesting actions, and the tracked chassis guarantees free movement of the equipment. Simulation experiments and field validation experiments indicate that optimal performance can be achieved when the brushing speed is set to 21.45 r/min, the picking finger speed is set to 341.27 r/min, and the picking device tilt angle is set to 1.0°. With these parameters, the harvesting quantity of Camellia oleifera fruits is 119.75 kg/h, fruit shedding rate 92.30%, and bud shedding rate as low as 9.16%. This new model for fruit shedding and the comb-spiral impact harvesting principle shows promise as a mechanized harvesting solution for nut-like fruits. Full article

The development of sustainable and functional nanocomposites has attracted considerable attention in recent years due to their broad spectrum of potential applications, including wood preservation. Also, a global goal is to reuse the large volumes of waste for environmental issues. In this context, the aim of the study was to obtain soda lignin particles, to graft ZnO nanoparticles onto their surface and to apply these hybrids, embedded into a biodegradable polymer matrix, as protection/preservation coating for oak wood. The organic–inorganic hybrids were characterized in terms of compositional, structural, thermal, and morphological properties that confirm the efficacy of soda lignin extraction and ZnO grafting by physical adsorption onto the decorating support and by weak interactions and coordination bonding between the components. The developed solution based on poly(3-hydroxybutyrate-co-3-hydroxyvalerate) and lignin-ZnO was applied to oak wood specimens by brushing, and the improvement in hydrophobicity (evaluated by water absorption that decreased by 48.8% more than wood, humidity tests where the treated sample had a humidity of 4.734% in comparison with 34.911% for control, and contact angle of 97.8° vs. 80.5° for untreated wood) and UV and fungal attack protection, while maintaining the color and aspect of specimens, was sustained. L.ZnO are well dispersed into the polymer matrix, ensuring a smooth and less porous wood surface. According to the results, the obtained wood coating using both a biodegradable polymeric matrix and a waste-based preservative can be applied for protection against weathering degradation factors, with limited water uptake and swelling of the wood, UV shielding, reduced wood discoloration and photo-degradation, effective protection against fungi, and esthetic quality. Full article

Background: As a well-known environmental hazard, ambient fine particulate matter (PM_2.5, aerodynamic diameter ≤ 2.5 µm) has been positively correlated with an increased risk of digestive system diseases, including appendicitis, inflammatory bowel disease, and gastrointestinal cancer. Additionally, PM_2.5 exposure has been shown to alter microbiota composition and diversity in human and animal models. However, its impact on goblet cells and gut mucus barrier integrity remains unclear. Methods: To address this, 8-week-old male and female interleukin-10 knockout (IL10^−/−) mice, serving as a spontaneous colitis model, were exposed to concentrated ambient PM_2.5 or filtered air (FA) in a whole-body exposure system for 17 weeks. Colon tissues from the PM_2.5-exposed mice and LS174T goblet cells were analyzed using H&E staining, transmission electron microscopy (TEM), and transcriptomic profiling. Results: The average PM_2.5 concentration in the exposure chamber was 100.20 ± 13.79 µg/m³. PM_2.5 exposure in the IL10^−/− mice led to pronounced colon shortening, increased inflammatory infiltration, ragged villi brush borders, dense goblet cells with sparse enterocytes, and lipid droplet accumulation in mitochondria. Similar ultrastructure changes were exhibited in the LS174T goblet cells after PM_2.5 exposure. Transcriptomic analysis revealed a predominantly upregulated gene expression spectrum, indicating an overall enhancement rather than suppression of metabolic activity after PM_2.5 exposure. Integrated enrichment analyses, including GO, KEGG, and GSEA, showed enrichment in pathways related to oxidative stress, xenobiotic (exogenous compound) metabolism, and energy metabolism. METAFlux, a metabolic activity analysis, further substantiated that PM_2.5 exposure induces a shift in cellular energy metabolism preference and disrupts redox homeostasis. Conclusions: The findings of exacerbated gut barrier impairment and goblet cell dysfunction following PM_2.5 exposure provide new evidence of environmental factors contributing to colitis, highlighting new perspectives on its role in the pathogenesis of colitis. Full article

Polysodiumoxy(methyl)siloxane is a highly functional polymer matrix that can be used for the preparation of both functional and non-functional polymers, including molecular brushes. To determine the molecular weight parameters of the matrix, as well as its chemical structure, it is necessary to develop an effective method of blocking functional (in our case, sodiumoxy) groups due to their high reactivity. At the same time, the blocking product should represent a complete non-functionalized replica of polysodiumoxy(methyl)siloxane. Since the obtained polysodiumoxy(methyl)siloxane can contain both sodium- and hydroxy groups in its composition, the presence of both types of functional groups should be considered in the blocking process. In this work, we investigated the blocking process of polysodiumoxy(methyl)siloxane and the influence of blocking conditions on the blocked product. We carried out several variants of blocking, which differed in the order and method of introduction of reagents, as well as in the temperature regime. The chemical structure and molecular weight characteristics of the obtained polymers were analyzed by ¹H NMR spectroscopy and gel permeation chromatography (GPC), respectively. According to the blocking results, only in one case, complete non-functionalized replicas of polysodiumoxy(methyl)siloxane were obtained, which allows this technique to be used as a tool for the analysis of complex, highly functionalized organosilicon systems. Full article

Intestinal alkaline phosphatase (IAP) is a brush border enzyme secreted by enterocytes, playing a crucial role in maintaining gut mucosal defense. This study investigated the expression dynamics of IAP in the small intestine of pigs challenged with Escherichia coli (E. coli) K88, compared to healthy controls. Five-week-old pigs (n = 8) were orally administered E. coli K88 at a concentration of 2 × 10⁸ CFU/mL, with a dose of 2 mL per pig at 0 and 24 h. Five days post-challenge, tissue samples from the duodenum, jejunum, and ileum were collected for mucosal morphometric analysis and evaluation of IAP expression via immunohistochemistry, Western blotting, and real-time PCR. The results revealed the presence of IAP on the apical surface of villi throughout the small intestine, along with significantly upregulated IAP expression in E. coli-challenged pigs compared to controls. These findings suggest that Gram-negative bacteria such as E. coli can induce IAP expression, likely through lipopolysaccharide (LPS) stimulation, thereby enhancing its enzymatic activity as part of the intestinal defense mechanism. This study provides insight into the protective role of IAP and highlights its potential as a biomarker for assessing gut health and diagnosing enteric infections in animals. Full article

Periodontal disease is a common and serious oral disease among older adults. As the global older population increases, preventing periodontal disease is vital for healthy ageing. Poor oral hygiene, uncontrolled diabetes, and smoking are key risk factors of periodontal disease. Improving oral hygiene, diabetes management, and quitting smoking are essential health behavioural change interventions to manage periodontal disease. The objective of this study is to review the prevention of periodontal disease among older adults through health behavioural change interventions. Effective strategies to improve oral hygiene include personalised education on proper brushing and interdental cleaning. Educating caregivers is equally important as they supervise care-dependent older adults to maintain oral health. For those with diabetes, physical activity improves glycated haemoglobin levels and clinical periodontal parameters by reducing reactive oxygen species and systemic inflammation. Smoking cessation could be achieved through a multi-faceted approach. Effective smoking cessation combines brief interventions with intensive behavioural/pharmacological support for long-term success, especially in highly dependent individuals. Tailored strategies for older adults, integrated care, and expanded research improve outcomes and health equity in ageing populations. In conclusion, health behavioural change interventions are non-invasive preventive measures that include oral hygiene reinforcement, diabetic management, and smoking cessation. Prioritising these interventions empowers older adults to maintain oral health, reducing disease burden and enhancing overall well-being for healthy ageing. Full article

Large turbine generators rely on shaft earthing brushes to safely divert harmful shaft currents to ground, protecting bearings from electrical damage. This paper presents a novel deep learning-based diagnostic framework to detect and classify faults in shaft earthing brushes of large turbine generators. A key innovation lies in the use of FFT-derived spectrograms from both voltage and current waveforms as dual-channel inputs to the CNN, enabling automatic feature extraction of time–frequency patterns associated with different SEB fault types. The proposed framework combines advanced signal processing and convolutional neural networks (CNNs) to automatically recognize fault-related patterns in shaft grounding current and voltage signals. In the approach, raw time-domain signals are converted into informative time–frequency representations, which serve as input to a CNN model trained to distinguish normal and faulty conditions. The framework was evaluated using data from a fleet of large-scale generators under various brush fault scenarios (e.g., increased brush contact resistance, loss of brush contact, worn out brushes, and brush contamination). Experimental results demonstrate high fault detection accuracy (exceeding 98%) and the reliable identification of different fault types, outperforming conventional threshold-based monitoring techniques. The proposed deep learning framework offers a novel intelligent monitoring solution for predictive maintenance of turbine generators. The contributions include the following: (1) the development of a specialized deep learning model for shaft earthing brush fault diagnosis, (2) a systematic methodology for feature extraction from shaft current signals, and (3) the validation of the framework on real-world fault data. This work enables the early detection of brush degradation, thereby reducing unplanned downtime and maintenance costs in power generation facilities. Full article

Bamboo, as a forest product material with good mechanical properties, is considered to be a future timber alternative due to its fast growth and accelerated reforestation potential. The use of OSB panels has significantly increased in the market and OSB has replaced traditional panels. Three different OSB panels coded Type 1, Type 2, and Type 3 were produced using bamboo and some mechanical properties were evaluated. Based on the results, Type 2 OSB panels yielded statistically higher bending strength values than Type 1 and Type 3 panels. There were no significant differences between the Type 1 and the Type 3 OSB panels. When the internal bonding (IB) values of the panels were examined, Type 3 yielded the highest values, followed by Type 2 and Type 1. However, it was observed that these resistance differences were not statistically significant. The only type of failure mode observed was brush-shaped separation from the center of the panels. The load–displacement graph of the OSB bamboo panels under bending load indicated a similar load-displacement curve of typical wood under bending load. Full article

The aim of this study was to evaluate and compare the surface roughness and gloss—both initially and after simulated toothbrushing—of three 3D-printed crown materials subjected to different surface treatments: varnishing, polishing with diamond-impregnated rubber polishers, and polishing with a bristle brush and paste. Disc-shaped specimens (n = 90) were 3D-printed using three commercially available crown resins (Rodin Sculpture, VarseoSmile TriniQ, and OnX Tough 2) and post-processed per manufacturers’ instructions. Specimens were divided into three surface treatment groups: application of a light-cured varnish, polishing with a two-step diamond-impregnated rubber polisher, or polishing with a bristle brush and abrasive paste. Surface roughness and gloss were measured after treatment and again following 20,000 cycles of simulated toothbrushing. Additional specimens were prepared for Vickers microhardness testing and determination of filler weight percentage (wt%). Statistical comparisons were performed using two-way ANOVA with significance set at p < 0.05. Results: The varnish provided the statistically lowest roughness of all surface treatments for all materials. The bristle brush and abrasive paste polishing protocol produced the greatest gloss for the softest material (VarseoSmile TriniQ) and lowest gloss for the hardest material (Rodin Sculpture), whereas the two-step diamond-impregnated rubber polisher produced an equivalent gloss on all materials. Following toothbrushing, roughness was minimally affected; however, gloss was considerably reduced. Conclusions: All tested polishing and varnishing methods achieved clinically acceptable surface roughness (Ra < 0.2 µm) that persisted after simulated toothbrushing. Notably, the two-step diamond-impregnated rubber polisher produced consistent gloss across all materials, while the bristle brush and abrasive paste polishing protocol performed better on softer materials, and varnish application resulted in equal or superior gloss and roughness retention compared to polishing. Full article

Outdoor cleaning robots must operate reliably across diverse and unstructured surfaces, yet many existing systems lack the adaptability to handle terrain variability. This paper proposes a terrain-aware cleaning framework that dynamically adjusts robot behavior based on real-time surface classification and slope estimation. A 128-channel LiDAR sensor captures signal intensity images, which are processed by a ResNet-18 convolutional neural network to classify floor types as wood, smooth, or rough. Simultaneously, pitch angles from an onboard IMU detect terrain inclination. These inputs are transformed into fuzzy sets and evaluated using a Mamdani-type fuzzy inference system. The controller adjusts brush height, brush speed, and robot velocity through 81 rules derived from 48 structured cleaning experiments across varying terrain and slopes. Validation was conducted in low-light (night-time) conditions, leveraging LiDAR’s lighting-invariant capabilities. Field trials confirm that the robot responds effectively to environmental conditions, such as reducing speed on slopes or increasing brush pressure on rough surfaces. The integration of deep learning and fuzzy control enables safe, energy-efficient, and adaptive cleaning in complex outdoor environments. This work demonstrates the feasibility and real-world applicability for combining perception and inference-based control in terrain-adaptive robotic systems. Full article

Large steam turbine generators are increasingly vulnerable to damage from shaft voltages and bearing currents due to the widespread adoption of modern power electronic excitation systems and more flexible operating regimes. Earthing brushes provide a critical path for discharging these shaft currents and voltages, but their effectiveness depends on the timely detection of brush degradation or faults. Conventional monitoring of shaft voltage and current is often rudimentary, typically limited to peak readings, making it challenging to identify specific fault conditions before mechanical damage occurs. This study addresses this gap by systematically analyzing shaft voltage and current signals under various controlled earthing brush fault conditions (floating brushes, worn brushes, and oil/dust contamination) in several large turbine generators. Experimental site tests identified distinct electrical signatures associated with each fault type, demonstrating that online shaft voltage and current measurements can reliably detect and classify earthing brush faults. These include unique RMS, DC, and harmonic patterns in both voltage and current signals, enabling accurate fault classification. These findings highlight the potential for more proactive maintenance and condition-based monitoring, which can reduce unplanned outages and improve the reliability and safety of power generation systems. Full article