Search Results (3,936)

This paper delves into the free vibration analysis of a rotating non-uniform functionally graded carbon nanotube-reinforced composite (FG-CNTRC) beam with symmetric material distribution, taking into account boundary relaxation. Three common carbon nanotube (CNT) distributions, namely FG-X, UD, and FG-O, are considered. The governing equations of a rotating FG-CNTRC beam with variable cross-section and boundary relaxation are formulated via Hamilton’s principle. Some factors, including the centrifugal force induced by rotation, boundary relaxation, cross-section gradient, and others, substantially complicate the boundary conditions, making it challenging to directly obtain an analytical solution with variable coefficients. To address this, a novel power series solution based on the differential transformation method (DTM) is introduced to discretize the vibration equation and obtain the natural frequency of the rotating FG-CNTRC beam, which forms the core novelty of this study. Comprehensive numerical calculations are carried out, and the reliability of the DTM results is fully verified via comparisons with finite element (FEM) outputs and published reference data. Full article

Liquefied natural gas (LNG) submersible centrifugal pumps are critical components in marine energy transportation systems, and fault-induced degradation may threaten operational safety, transfer reliability, and maintenance efficiency. However, condition monitoring and fault diagnosis often rely on heterogeneous multi-source data, where redundant information, unequal channel sensitivity, and inter-signal coupling may obscure discriminative fault features. To address this challenge, this paper proposes a hierarchical multi-source condition monitoring and fault diagnosis framework for LNG submersible centrifugal pumps by integrating an Entropy-Weighted Sensor Selection Method (EWSSM) with a hybrid convolutional neural network (CNN)–Transformer model. Functional information is used for front-end abnormality screening, while selected response signals are used for fault category recognition. EWSSM evaluates channel contribution and suppresses redundant inputs to construct a compact fault-sensitive input space. The CNN–Transformer model combines local feature extraction with global dependency modeling to identify complex fault patterns. A laboratory-scale fault simulation platform was established, and vibration, acoustic, internal pressure-pulsation-related response information, and operating parameter data were collected under ten operating states. Experimental results show that the proposed framework achieves effective abnormality screening and accurate fault diagnosis, with an average classification accuracy of 98.73% over repeated experiments. Covariance-difference analysis further provides interpretable evidence for condition assessment by revealing fault-related multi-source response redistribution. The proposed framework provides an effective, intelligent monitoring and diagnosis solution for LNG submersible centrifugal pumps and supports reliability-oriented operation and maintenance of marine energy transportation equipment. Full article

Magnetic fluid seals use magnetic field gradients generated by permanent magnets, pole pieces, and rotating shafts to confine ferrofluid in the sealing gap and form multiple liquid sealing rings. Compared with mechanical and labyrinth seals, they exhibit low wear, high cleanliness, low friction loss, and near-zero leakage, making them suitable for high-vacuum equipment, semiconductor devices, clean robotic joints, and rotary feedthrough systems. This review summarizes the development, theoretical basis, experimental methods, structural design, performance characteristics, failure mechanisms, numerical modeling approaches, and engineering applications of magnetic fluid sealing technology. Quantitative comparisons show that ferrofluid seals generally provide a single-stage pressure-bearing capacity of approximately 10–20 kPa with near-zero leakage and good self-replenishment, whereas magnetic powder seals can reach approximately 50–100 kPa per stage but suffer from higher leakage and poor self-recovery. Under high-speed conditions, centrifugal depletion, viscous heating, carrier-liquid volatilization, and interfacial instability become the dominant causes of performance degradation. The reviewed literature indicates that pole-tooth geometry, magnetic-circuit topology, saturation magnetization, thermal transport, and medium compatibility jointly determine sealing reliability. Future research should focus on high-saturation and low-vapor-pressure ferrofluids, optimized pole-tooth and magnetic-circuit structures, magnetic–flow–thermal coupling, integrated cooling, online monitoring, life prediction, and standardized reliability evaluation. Full article

Background/Objectives: eccDNA is a promising cancer biomarker in liquid biopsy. However, the reliability and reproducibility of eccDNA studies rely on the standardization of pre-analytical handling and processing of eccDNA, as well as transparent methodological reporting. Although evidence-based guidelines for cell-free DNA handling provide clear recommendations for plasma/serum processing, the extent to which eccDNA studies report and adhere to these key procedures remains uncertain. Methods: We systematically reviewed 14 studies (2017–2025) assessing eccDNA in plasma or serum from cancer patients. Each study was evaluated against 22 checklist items summarized from the NCI Biospecimen Collection and Processing Guideline, categorized into biospecimen collection, blood processing, and eccDNA processing. Items were classified as “reported,” “not reported,” or “deviated from NCI guideline,” and missing/deviation rates were calculated. Results: Publication was largely post-guideline (13/14 after 2020). Reporting gaps were widespread. Items with 100% missing were venipuncture site (14/14), freeze–thaw cycles (14/14), and fitness for downstream analysis/pre-assay QC (14/14). Other frequently missing elements included blood volume (10/14; 71%), collection tube type (7/14; 50%), date/time from draw to processing (11/14; 79%), second centrifugation parameters (8/14; 57%), storage temperature before freezing (6/14; 43%), frozen storage duration (13/14; 93%), and post-thaw handling (13/14; 93%). By contrast, the extraction method was consistently reported (0% missing), and most reported quantification (21% missing). Deviations from the NCI guideline were uncommon when items were reported, such as a blood processing delay (2/14; 14%) and the use of circulating nucleic acid kits for eccDNA extraction (1/14; 7%). Conclusions: Inconsistent reporting of pre-analytical procedures limits the reproducibility, transparency, and clinical translation of eccDNA research. We propose a concise reporting checklist informed by the NCI guideline. By focusing on the most frequently underreported aspects of key pre-analytical eccDNA procedures, the checklist provides researchers with an efficient and succinct methodological reporting framework that will enhance transparency and promote standardization in future eccDNA studies. Full article

FeNi50 powder production for metallic magnetic cores faces challenges including low fine-powder yield and defects like hollow particles. This study employed cyclone atomization to prepare FeNi50 powder and systematically examined the effects of atomization pressure (1–6 MPa) through combined simulation, experiment, and theoretical analysis. Results show that increasing pressure reduces the average particle size (D50) from 80.7 μm to 27.9 μm and raises the fine powder yield (−500 mesh) from 19.4% to 50.0%, far exceeding that of close-coupled nozzle atomization (<10%). The powder particles are spherical/near-spherical with dense, non-hollow interiors. Higher pressure also increases the cooling rate, which blurs surface grain boundaries, refines grain structure, and induces single-crystal or amorphous characteristics in particles < 15 μm while suppressing N and O absorption. X-ray diffraction confirms the phase composition remains unchanged. These evolutions originate from three synergistic mechanisms: competition between solidification and spheroidization times, centrifugal and Magnus forces from swirling flow, and plastic-state droplet deformation imparting specific surface roughness. Cyclone atomization therefore proves a promising method for producing high-quality FeNi50 powder, suitable for large-scale manufacturing of high-performance magnetic powder cores. Full article

The preparation of platelet-rich plasma (PRP) requires precise density-based centrifugation of anticoagulated whole blood to achieve an optimal hematologic bioformulation while enhancing platelet recovery efficiency. Commercial PRP systems exhibit substantial heterogeneity in processing architecture, with variable platelet yields and inconsistent cellular composition profiles. In this clinical PRP device evaluation, 70 sequential samples sourced from two independent clinical facilities were used to evaluate the performance characteristics of the XCELL 60 mL single-spin centrifugation platform. Two different PRP preparations were consistently prepared as per physician preferences: PRP-1 and PRP-2. The main differences between these two preparations were the concentration of leukocytes and reduction in red blood cells. The system was evaluated based on critical PRP performance metrics. The results demonstrated the following: (1) A consistent 8-fold increase in platelet concentration relative to baseline whole blood was achieved. (2) The average platelet capture rate (PCR) was 83%. (3) The total available platelets (TAPs) in the PRP specimen produced from both groups combined were 10.8 ± 2595 billion platelets within a final product volume of 6 mL. (4) Hematocrit values were reduced to <2–6% across sites (reduction of 94% and 84% in RBCs, respectively). Finally, (5) a customizable leukocyte content (20.9–25.4 × 10⁹/L) was achieved without comprising platelet yield. This single-spin centrifugation architecture achieved performance parity with historically preferred double-spin systems while reducing the processing time and number of preparation steps. Engineering analysis established that high-precision platelet recovery and bioformulation control are achievable through optimized single-spin centrifugal design, enabling standardized therapeutic dosing for autologous regenerative medicine applications. Full article

Spirulina-derived protein hydrolysates (SPPHs) have attracted considerable attention as bioactive agents due to their potential metabolic and physiological benefits. This study evaluated the therapeutic efficacy of different enzyme-specific SPPHs—Pepsin (SPPH-P), Trypsin (SPPH-T), Chymotrypsin (SPPH-C), and a combined hydrolysate (SPPH-PTC)—in high-fat diet (HFD)-induced male Wister rats, compared with Spirulina platensis protein extract (SPPE, formulated using freeze–thaw cycles and ultrasonication followed by centrifugation) and atorvastatin as a Positive Control. The animals were randomly allocated into seven groups (n = 6 per group) and received their respective treatments orally for 4 weeks. Across treatment groups, significant improvements in obesity-related anthropometric indices were observed, including reductions in BMI, Lee Index, and abdominal circumference to thoracic circumference ratio (AC:TC), with the strongest effects noted in the atorvastatin and SPPH-PTC groups. Protein metabolism markers showed enhanced hepatic and serum protein status, reflected by increased albumin and total protein concentrations. Lipid profile analysis revealed marked decreases in total cholesterol, triglycerides, and LDL in both serum and liver homogenates, while HDL exhibited non-significant but favorable elevations. Liver function markers (bilirubin, ALT, AST) and renal parameters (uric acid, BUN) demonstrated notable improvements, particularly in enzyme-derived hydrolysate groups and Positive Control. Antioxidant assessments indicated substantial reductions in MDA levels and significant increases in SOD, CAT, and GSH activities in serum and liver tissues, confirming enhanced oxidative stress resistance. Among all treatments, SPPH-PTC consistently produced the most robust therapeutic outcomes. Overall, Spirulina protein hydrolysates, especially the combined PTC formulation, exert comprehensive beneficial effects on metabolic regulation, hepatic and renal function, and oxidative balance. These findings support their potential application as functional bioactive agents for managing obesity-associated metabolic disturbances. Full article

Spirometra mansoni causes sparganosis in humans and spirometrosis in domestic dogs. It is transmitted through the consumption of raw or undercooked meat from fish, frogs or paratenic animals, producing subcutaneous and tissue infections in humans, whereas dogs or cats develop gastrointestinal infections. Sparganosis is a zoonotic parasitosis associated with freshwater aquatic environments, prevalent in tropical and subtropical regions of the world. The purpose of this investigation was to identify S. mansoni in domestic dogs from riverine sectors of the Daule River in Ecuador, using coproparasitological methods: direct examination, flotation and sedimentation with centrifugation using saline solution (as screening); and for confirmation, morphometric methods and PCR were used. Through a descriptive, prospective and cross-sectional study, 402 domestic dogs were analyzed, and Spirometra mansoni were determined in 67 (16.66%) of the collected samples. The clinical and epidemiological characteristics of spirometrosis in dogs and the potential risk of sparganosis occurring in humans were determined. However, cases may appear in pets from other locations. Full article

Real-hardware deployment of adaptive manipulator controllers remains difficult because assumptions made in paper-level formulations are weakened by friction, encoder quantisation, current limits, communication latency, and low-speed actuation nonlinearities. This paper investigates that deployment gap for a recent Nussbaum-function PID controller by translating it from a simulation-level formulation into direct current-command control on a Niryo NED3 Pro actuator. To isolate deployment-layer behaviour from the whole-arm Coriolis, centrifugal, and gravity dynamics, the study is centred on a single decoupled actuator (Dynamixel ID 6, distal wrist) under long-horizon sinusoidal tracking around a fixed operating region. A direct transfer of the baseline law is first reproduced and shown to degrade through cumulative adaptation-state growth, weakening of the Nussbaum modulation, and high internal command saturation. A hardware-oriented implementation is then evaluated that preserves the Nussbaum core while adding adaptation-state regularisation, low-speed velocity-reference feedforward, and tail-region damping; its parameters are selected through a hardware-aware Optuna archive of 79 real-hardware trials with hard rejection of unsafe runs and a score that jointly reflects tracking quality, internal command saturation, actuation activity, and bounded adaptation growth. Over 300 s of continuous operation, the enhanced implementation reduces the mean absolute error from ${10.476}^{\circ }$ to ${1.054}^{\circ }$ and the internal command saturation ratio from $0.450$ to $0.012$ relative to the direct baseline, within the reported actuator, trajectory, and safety envelope. The main contribution is therefore not only a tuned controller but a reproducible real-hardware methodology showing how Nussbaum-based PID control can be deployed and improved on a low-cost manipulator when adaptation management, actuation mapping, and hardware-aware optimisation are treated as core elements of the research design. Full article

Accurate healthy-state performance modeling under multiple operating conditions is essential for the condition assessment of industrial centrifugal compressors. However, conventional healthy-state baselines often struggle to meet the requirements of real-time condition assessment for centrifugal compressors operating under complex real-gas and multi-condition environments. To address this issue, this study proposes a two-layer framework combining a CFD-based physical baseline with data-driven residual correction using limited factory data. A three-dimensional full-machine CFD model was reconstructed and validated under real-gas conditions, then used to generate 1440 healthy-state operating points. XGBoost, LightGBM, Random Forest, and multilayer perceptron were evaluated as baseline surrogate models. A residual-correction model was subsequently trained to compensate for systematic discrepancies between CFD predictions and actual machine performance. Ablation tests compared the CFD baseline, a factory-data-only model, and the proposed hybrid model. Online computation requires only surrogate inference and residual correction, achieving an inference latency of 0.6585 ms per operating point on Intel64 Family, compatible with the 60 s SCADA sampling interval. After correction, the maximum errors in power, polytropic head, and polytropic efficiency were 0.611%, 0.481%, and 0.899%, respectively. Post-overhaul field validation yielded maximum errors of 1.650%, 3.048%, and 1.708% for outlet pressure, power, and polytropic efficiency. The framework provides a physically grounded and computationally efficient healthy-state reference, although its transferability requires validation using additional station-specific data. Full article

Jellyfish collagen, a sustainable and biocompatible marine biomaterial, holds great potential in food and biomedical applications. This study explores the emulsification properties and therapeutic potential of pepsin-soluble collagen derived from salt-preserved Rhopilema esculentum (RPSC). Structural analysis confirmed that RPSC retained an intact triple-helix structure with a denaturation temperature of approximately 36.0 °C and formed elastic gels at concentrations ≥1.5% (w/w). As an emulsion stabilizer, RPSC (2%, w/w) effectively stabilized oil-in-water emulsions with oil fractions up to 50%, forming viscoelastic networks that exhibited excellent centrifugal stability but limited freeze–thaw tolerance. The gel–sol transition occurred near 38.0 °C, consistent with the thermal denaturation of RPSC. As a wound healing promoter, RPSC showed no cytotoxicity and dose-dependently enhanced 3T3 fibroblast viability, migration, and SOD activity. Notably, RPSC downregulated TGF-β1 expression and suppressed endogenous type I collagen synthesis, indicating a scar-mitigating profile distinct from conventional pro-fibrotic collagen dressings. These findings establish RPSC as a bifunctional marine biomaterial for both emulsified food systems and regenerative wound dressings in the biomedical field. Full article

It is essential for quinoa’s rapid expansion in the global market to comply with the circular economy to become a green agro-food industry. For this purpose, in this work, bioactive added-value compounds, specifically saponins and phenolic antioxidants, were extracted and purified from quinoa by-products (QbP), namely hulls, using green solvent extraction (60 wt% ethanol-water) and nanofiltration (NF). So far, research published on the implementation of NF in the treatment of QbP, or modelization and optimization of the membrane performance focusing on fouling minimization and control, is scarce. Centrifugation and microfiltration were conducted as separation-purification pretreatments before NF. A three-level factorial design was successfully applied to optimize NF membrane operation in terms of saponins and phenolic compound recovery, as well as permeate flux, comprising operating pressure and tangential velocity as key input factors. Membrane fouling, critical for stable process operation scale-up, required intensive multifactorial analysis. Optimization at 4 bar and 15 m/s permitted the recovery of up to 84.5% saponins and 84.3% phenolic compounds in the permeate stream. Moreover, NF dynamic performance modeling and optimization ensured fouling build-up minimization and maximization of membrane productivity almost ten-fold, up to a stable value as high as 175.4 L/hm², ensuring full recovery of the membrane performance after each operating cycle, key for the technical–economic viability of the proposed process to obtain standardized purified extract products. Full article

Intelligent fault diagnosis of rotating machinery typically assumes that training and test data share the same operating speed, an assumption that rarely holds in industrial end-of-line testing, where a rotor must be certified across a range of shaft speeds. In this paper, we expose this assumption through a systematic benchmark of four deep learning architectures (TCN, 1D-CNN, BiLSTM, and CNN-BiLSTM) on a laboratory rotor testbench with three operating speeds (1000, 2000, and 3000 rpm) and four unbalance fault classes. Under within-speed 5-fold cross-validation, all four models achieve a perfect macro-F1 of 1.000, offering no basis for architecture selection. Under Leave-One-Speed-Out (LOSO) evaluation (train on two speeds, test on the held-out speed), performance drops substantially and diverges across models: BiLSTM 0.180, TCN 0.270, 1D-CNN 0.271, and CNN-BiLSTM 0.401. We trace the LOSO gap to the unbalance centrifugal force law F = meω², which makes speed-confounded features unreliable under cross-speed testing. CNN-BiLSTM improves the mean LOSO macro-F1 by 48% relative to the stronger single-module baseline, 1D-CNN. Although CNN-BiLSTM achieves the highest LOSO performance among the evaluated architectures, it still does not surpass the physics-informed LightGBM baseline of 0.487. Therefore, the primary contribution of this work is not to solve cross-speed diagnosis, but to demonstrate that conventional same-speed evaluation substantially overestimates model capability and that LOSO provides a more deployment-relevant benchmark for future algorithm development. Full article

Oat milk (OM) has gained popularity as a plant-based dairy alternative; however, conventional filtration-based production removes oat pulp, leading to β-glucan loss and processing waste. This study investigated the effects of particle size reduction by different grinding techniques on the powder properties and in vitro digestion characteristics of oat powder (OP), and it evaluated the applicability of superfine OP to filtration-free OM production. OP was prepared at three particle sizes: coarse, fine, and superfine, using a blender, ultra-centrifugal mill, and ball mill, respectively. Decreasing particle size improved hydration properties, including water absorption capacity, swelling capacity, and water solubility. During in vitro digestion, OP-superfine showed higher dialyzable protein fraction, β-glucan extractability, and digestion extract viscosity than OP-coarse, indicating an enhanced release of proteins and viscosity-contributing soluble components. When applied to OM, OP-superfine increased viscosity, Brix, turbidity, and suspension stability, while particle size had only a minor influence on pH. Sensory evaluation showed that OM prepared with OP-superfine had reduced grittiness and throat-feel intensity while maintaining relatively high sweetness. These findings suggest that superfine grinding is a promising strategy for producing filtration-free OM with improved digestion-related properties, physical stability, and sensory quality. Full article

Bovine milk represents a highly complex colloidal system whose physicochemical stability depends on the organization of milk fat globules, casein micelles, membrane-associated phospholipids, and somatic cellular components. Mechanical separation procedures such as centrifugation induce redistribution of dispersed colloidal fractions and structural perturbations within the milk matrix, potentially enabling fraudulent reduction of somatic cell count while preserving bulk compositional parameters. In the present study, we investigated whether advanced deep learning architectures could identify centrifugation-associated structural alterations in bovine milk using microscopy image representations. A total of 16,472 microscopy images obtained from centrifuged and non-centrifuged milk samples were analyzed using Swin Transformer V2 and ConvNeXt-Base architectures. Both models successfully detected centrifugation-associated structural perturbations and substantially outperformed the previously analyzed InceptionC baseline. ConvNeXt-Base achieved 87.30% classification accuracy together with 86.85% balanced accuracy and 86.59% harmonic average of recalls following totalogit aggregation. Importantly, Swin Transformer V2 demonstrated strong monotonic relationships between logit metrics and centrifugation ratio (r = 0.640–0.651, p < 0.01), indicating sensitivity to progressive image-level changes associated with increasing centrifugation ratio. Collectively, the obtained findings demonstrate that microscopy-derived deep learning representations capture structural information associated with centrifugation-induced changes in bovine milk, supporting the applicability of AI-assisted microscopy for detecting processing-related alterations in complex dairy systems. Full article