Search Results (3,774)

Filled polymers yield differently under shear and uniaxial deformation, but filler and rate effects remain sparsely characterized. We study a glassy Kremer–Grest polymer with frozen filler beads at $N=100$, loading $\varphi \in [0,0.30]$, and strain rate $\dot{\epsilon }\in [{10}^{-4},{10}^{-2}]{\tau }_{\mathrm{LJ}}^{-1}$ by non-equilibrium molecular dynamics. All ten strain-rate-sensitivity confidence intervals exclude zero (uniaxial $m\in [0.17,0.30]$, shear $m\in [0.14,0.16]$). Uniaxial yield is more rate-sensitive than shear, but the mode gap is loading-dependent: $\Delta m\approx 0.08$–$0.16$ ($p\ge 0.98$) for $\varphi \le 0.10$, attenuating to $0.02$–$0.04$ for $\varphi \ge 0.20$ as filler loading increases. Frozen filler softens rather than reinforces (shear yield $-78\%$, plateau modulus $-43\%$); density-matched neat controls attribute most of the shear softening to density dilution (89–$97\%$). At $\varphi =0.30$, shear develops a low-rate crossover and the yield ratio ${\sigma }_y^{\mathrm{uniax}}/{\sigma }_y^{\mathrm{shear}}$ rises to $[1.30,1.40]$, below the von-Mises reference. Density dilution dominates, but both-mode controls isolate a mode-selective filler contribution at $\varphi =0.30$ (resolved at the higher rate): 35–$42\%$ of the uniaxial versus ∼10% of the shear yield. Full article

Reliable tools for assessing soil nutrient availability are essential for the accurate determination of fertilizer application rates. The aim of this study was to evaluate the reliability of commercially available electrochemical sensors for the real-time determination of water-soluble N, P, and K in soil as indicators of nutrient supply to crops. The experiment was conducted under both greenhouse and field conditions using seven probe models. Four probes (designated 1–4) were equipped with three sensors for the measurement of N, P, and K. Probes 5, 6, and 7 were equipped with sensors for N, P, K, electrical conductivity (EC), pH, soil temperature, and soil moisture, although probe 7 was manufactured by a different company. Each probe was inserted into 4 L pots filled first with a clay-loam soil and subsequently with a sandy soil. The soils were irrigated with nutrient solutions containing different concentrations of N, P, and K in order to modify nutrient concentrations in the soil solution and compare sensor readings with values obtained through standard chemical analyses. The results showed no significant correlation between probe readings and soil N, P, or K concentrations in either clay-loam or sandy soils. At the same time, all probes exhibited a constant relationship among N, P, and K readings regardless of soil texture or nutrient concentration. This finding suggests that the probe algorithms rely on a single measured variable that is subsequently converted into multiple output variables using fixed conversion coefficients. In conclusion, the NPK probes tested in this study were unable to provide reliable real-time measurements of soil N, P, and K concentrations. Full article

Background: The rising incidence of knee osteoarthritis in Oman has increased the demand for total knee replacement (TKR) surgeries, highlighting the critical role of evidence-based postoperative physiotherapy. However, no prior study has systematically assessed physiotherapy practices post-TKR in Oman. This study aimed to fill this gap by assessing current physiotherapy practices post-TKR in Oman, evaluating adherence to international guidelines, and identifying barriers to optimal care. Methods: A cross-sectional study was conducted between January and March 2025 using a self-administered, structured questionnaire distributed to 189 physiotherapists in governmental hospitals. Data were analyzed using descriptive statistics with SPSS version 26. Results: High adoption rates were found for preoperative education (94.2%) and strengthening exercises (95.3%). In acute-stage rehabilitation, functional training (96.35%) and early mobilization (94.27%) were prevalent. However, utilization of standardized outcome measures (e.g., WOMAC) was low (74.47%) and variability existed in discharge criteria. Major barriers included a shortage of physiotherapists (91.66% agreement), limited resources (92.18%), and patient-related challenges (94.79%). Conclusion: While foundational rehabilitation practices are implemented effectively in Oman, significant gaps remain in standardized assessments and adherence to specific international protocols. Addressing workforce shortages, resource limitations, and implementing unified national guidelines are essential for optimizing post-TKR rehabilitation outcomes. Full article

Wet cooling towers are widely used for low-energy thermal management and ventilation support; however, high-fidelity simulations are computationally expensive for large design studies. This work develops a physics-based static reduced-order model for a two-dimensional axisymmetric counterflow wet cooling tower derived from computational fluid dynamics (CFD) simulations coupled with a user-defined source-term formulation for heat and mass transfer in the fill region. A design of experiments based on advanced Latin hypercube sampling generated 210 configurations, of which 168 valid simulations were retained. The active inputs included tower diameter, fill height, inlet air mass flow rate, inlet air temperature, inlet humidity ratio, inlet water mass flow rate, and inlet water temperature, while the cooling range and evaporation rate were selected as target outputs. Five surrogate families were compared by cross-validation. Kriging was statistically most accurate, with $R_{CV}^2$ values of 0.9999 and 0.9998 for the cooling range and evaporation rate, respectively. Second-order quadratic polynomial models were selected as the engineering reduced order model (ROM) because they capture non-linear boundary curvatures with accuracy, achieving $R_{CV}^2\ge 0.9989$ and root mean square errors of 0.0426 K and 0.00042 kg/s while preserving an explicit, directly implementable algebraic form. Sensitivity analysis indicated that the inlet water temperature and air mass flow rate are dominant factors within the sampled domain. Full article

Lithium-ion batteries are widely used in digital, power and energy storage fields due to their high capacity and high cycle life advantages. This paper systematically screens the formulation system and designs a high-efficiency production line that can effectively improve production efficiency, reduce production costs, and lower energy consumption per unit product. The produced nano-silicon-enhanced graphite anode material has excellent performance. The selection of silicon raw materials, types of solvents, types of dispersants, and grinding processes is studied to investigate the influence of these four factors on the wet grinding process for preparing nano-silicon. Finally, metal silicon obtained by air flow pulverization is selected as the raw material, isopropanol is used as the solvent, FA01 (carboxylic acid type) is used as the dispersant, and a two-stage wet grinding process is adopted to prepare the nano-silicon dispersion solution. Zirconia beads of 0.5 mm and 0.2 mm size are used as the grinding media for the first and second stages, respectively, with filling rates of 80% and 90%, respectively. The final prepared nano-silicon dispersion is stable in dispersion and has a narrow particle size distribution. The nano-silicon dispersion solution and the multi-walled carbon nanotube dispersion solution are mechanically ground and mixed using a sand mill. At the same time, the multi-walled carbon nanotubes are coated with the nano-silicon. Then, artificial graphite is added for compounding. Finally, through spray drying, the Si@MWCNTs@graphite (SMG) nano-silicon-enhanced graphite negative electrode material is prepared. The SMG nano-silicon-enhanced graphite negative electrode material with a silicon content of 2% has a first Coulomb efficiency of up to 84.32%. Full article

Product codes (PCs) are widely used in high-speed communication systems due to their attractive trade-off between error-correction performance and complexity. To further meet the rapidly growing demand for higher data rates, soft-aided hard-decision decoders (SA-HDDs) have been developed. In this paper, we present a reduced-complexity iterative bounded distance decoder with random flipping (RC-iBDD-RF) for PCs, an SA-HDD that improves the decoding performance while preserving low decoding complexity. RC-iBDD-RF introduces an enhanced reliability metric that incorporates channel log-likelihood ratios (LLRs) and memory from previous iterations to guide random flipping. In addition, an error-and-erasure decoding (EaED) module employing fixed filling patterns, rather than randomly generated ones, is used for post-processing to further reduce the residual error rate. The comparisons for BCH-based PCs show that RC-iBDD-RF achieves both performance gain and complexity reduction with only a slight increase in memory requirement. Moreover, the proposed complexity-storage weighted SNR metric confirms its superior complexity-performance trade-off over iBDD-RF. Full article

Directing a stream of air across the tooth when light curing resin-based composites (RBCs) may affect their degree of conversion (DC), maximum rate of polymerization (RP_max), and in vitro intrapulpal temperature. Methods: Filtek One Bulk Fill and VisCalor bulk were preheated according to the manufacturer’s instructions and used to fill a Class I cavity in a molar at 32 °C. A stream of air at either 15 or 30 psi was directed across the tooth from an air-water syringe positioned 1 cm from the buccal surface. The RBCs were light-cured for 20 s using the Bluephase N, and the DC and RP_max were determined from real-time FT-IR data. A T-type thermocouple positioned inside the pulp chamber recorded the temperature. DC and RP_max data were analyzed using one-way ANOVA, whereas temperature was analyzed using two-way ANOVA, followed by Tukey post hoc tests. Results: Directing a stream of air at the tooth produced no significant differences in the DC and RP_max. The temperature change (ΔT) decreased compared to when no air was delivered. No significant difference in ΔT was found between the two air pressures. Conclusions: Directing a stream of air across the tooth when the preheated RBC was inserted did not affect the polymerization kinetics. The air stream reduced the temperature rise inside the pulp chamber as the RBC was light-cured. Clinical Significance: Directing a stream of air across the tooth at either 15 psi or 30 psi during light curing is an easy method to reduce the temperature increase inside the pulp chamber without affecting the polymerization kinetics of the evaluated preheated RBCs in this in vitro model. Full article

To investigate the influence of aggregate fractal gradation on the time-dependent deformation of cemented coal gangue backfill, four groups of specimens with different aggregate fractal dimensions were prepared based on mass fractal theory. Multi-stage loading creep tests were conducted to examine the effects of aggregate fractal dimension on creep strain, steady-state creep rate, and long-term strength. An improved fractional-order Burgers creep model incorporating a fractional Abel dashpot was then established to describe the creep response and to further interpret the relationship between aggregate gradation and model parameters. The results show that the creep deformation of cemented coal gangue backfill increased with increasing stress level and exhibited instantaneous deformation, decelerating creep, steady-state creep, and accelerating creep stages. With increasing aggregate fractal dimension, the creep deformation, steady-state creep rate, and damage accumulation first decreased and then increased. Among the tested aggregate fractal gradations, the specimen with D = 2.41 exhibited the best creep resistance, with a long-term strength of 8.83 MPa, approximately 33.40% higher than that of the specimen with D = 2.20. This behavior may be attributed to a more favorable coarse–fine particle proportion, which improves particle filling and skeleton continuity under the present material system. The comparison between experimental and fitted results indicates that the improved fractional-order Burgers model can effectively reproduce the creep process of cemented coal gangue backfill, with coefficients of determination greater than 0.97 for all tested specimens. These findings provide a useful reference for aggregate gradation optimization and creep-resistance evaluation of cemented coal gangue backfill under laboratory multi-stage loading conditions. Full article

Ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) are physically complementary non-destructive evaluation methods for reinforced concrete, yet their integrated diagnostic use has been limited by the absence of controlled, ground-truth-validated calibration of the joint-signature space. This paper presents a laboratory calibration programme in which a single C30/37 reinforced concrete beam (3000 mm × 300 mm × 200 mm, three T12 bars at 35 mm cover, CEM I 42.5N, w/c = 0.50) was sequentially conditioned through four controlled deterioration states—intact reference (Model A), water-filled saw-cut crack (Model B), full saturation by seven-day top-surface ponding (Model C), and chloride-induced active corrosion (Model D). Seven RES2DINV inverted ERT sections at three electrode spacings (a = 7, 15, and 30 mm) and three 800 MHz GPR profiles were acquired across the four known ground-truth conditions. The intact-reference resistivity ρ₀ = 558 Ω·m (full-section median of the mlab dataset at a = 7 mm) and GPR-calibrated velocity v = 0.095 ± 0.008 m/ns (from hyperbola fitting at 35 mm rebar cover) establish the absolute baselines. The four conditions produce systematically distinct joint signatures: Model A exhibits uniform high resistivity with clean rebar hyperbolae and no anomalous reflections; Model B produces a localised ERT low-ρ anomaly (ρ_min = 1.46 Ω·m) co-located with a negative-polarity (R = −0.68) GPR crack-mouth reflection confirming water-fill; Model C produces pervasive low-ρ with a smooth depth gradient and 50–65% GPR amplitude attenuation (−6.0 to −9.1 dB); Model D produces the same bulk GPR signatures as Model C but with a critically different ERT spatial texture—a heterogeneous near-surface layer above a sharp boundary at z ≈ 40 mm with depth-preferential low-ρ concentrated at rebar level. This depth-preferential signature, quantified here by a reproducible Depth-Preferential Index (DPI), is the primary ERT-only diagnostic criterion distinguishing active corrosion from pervasive saturation. For the Model C versus Model D distinction, the GPR response is non-discriminating; this high-risk distinction is resolved exclusively by the ERT depth-preferential criterion. The calibration demonstrates that GPR and ERT are physically non-redundant in the strict sense: neither method alone can unambiguously discriminate all four states, but their combination yields correct classification within the controlled laboratory conditions and subject to the stated qualification conditions. The corrosion state was confirmed at the regime level (chloride above the depassivation threshold, under accelerated polarisation) but was not quantified electrochemically, so the depth-preferential signature is interpreted as an indirect spatial proxy for active corrosion rather than a measurement of corrosion rate. Seven failure modes are quantitatively characterised and embedded in the framework as a priori qualification conditions. The calibrated reference values (ρ₀, A₀, Stage 2 thresholds, depth-preferential criterion) are specific to the laboratory mix and curing history and require local Stage 1 recalibration for field application. Full article

Global demographic shifts and rising population mobility have created a profound decoupling between dynamic population distributions and static public service facility configurations. This socio-spatial mismatch is particularly acute in less-developed counties, where the widespread “multi-local living” practices among rural residents have rendered traditional planning models based on static administrative quotas ineffective. This study uses Pucheng County, China, as a case study; we integrate mobile phone signaling data with complex network analysis to construct population flow networks that capture actual service demand and usage preferences. A demand-driven improvement of the traditional Optimal Supply–Demand Accessibility (OSD) model is proposed through flow-based supply adjustment coefficients and determines the coverage and accessibility of public service facilities at the county level to achieve optimization of their layout. The findings reveal: (1) Villages are classified into five types (high-inflow, inflow, balanced, outflow, high-outflow). (2) Within a 30 min walking radius, the service coverage rates of the three facility types improved by an average of 25 percentage points, with medical and elderly care facilities showing significantly greater improvements. (3) Accordingly, a “precise gap-filling + medical-care integration + mobile services” allocation model is proposed. The study provides a transferable framework for improving public service accessibility in regions characterized by high population mobility and service underprovision. Full article

This study aimed to analyze the differences in serum metabolomes at different stages of estrus synchronization in Kazakh horses, to characterize dynamic changes in serum metabolites during estrus synchronization, and to screen potential metabolic markers and key regulatory pathways. Four sampling stages (M1: intravaginal device insertion; M3: device removal, labeled consistently with the pre-experiment timeline; P: 24 h post-PG injection; L: tertiary follicle emergence) were selected. The research results showed that 37 significantly different metabolites (DAMs) were identified in the M1-vs.-M3 positive ion mode, with 16 metabolites significantly upregulated and 21 significantly downregulated. In the M1-vs.-M3 negative ion mode, 47 significantly different metabolites were identified, including 17 upregulated and 30 downregulated. In the M3-vs.-P positive ion mode, 69 significantly different metabolites were identified, with 53 upregulated and 16 downregulated. In the M3-vs.-P negative ion mode, 63 significantly different metabolites were identified, including 39 upregulated and 24 downregulated. In the Pvs-L positive ion mode, 65 significantly different metabolites were identified, with 16 upregulated and 49 downregulated. In the P-vs.-L negative ion mode, 61 significantly different metabolites were identified, including 13 upregulated and 48 downregulated. The significantly different metabolites mainly included lipids and lipid-like molecules, organic heterocyclic compounds, and organic acids and their derivatives. KEGG enrichment analysis showed that the significantly different metabolites in Kazakh horses at different stages were mainly enriched in nicotinic acid and nicotinamide metabolism, amino acid synthesis, and related pathways. This study revealed significant differences in the serum metabolome, and nicotinic acid and nicotinamide metabolism, by generating NAD⁺ and NADPH, simultaneously supporting energy supply, steroid hormone synthesis, and antioxidant protection, which are the basic metabolic guarantees for the development of follicles from quiescence to growth; amino acid synthesis not only provides protein raw materials for follicular cell proliferation but also participates in the regulation of the follicular microenvironment by synthesizing signaling molecules and antioxidant substances. This study enriched the research on the metabolic regulation of estrus synchronization in equine species, filled the gap in the metabolomics research of estrus synchronization in Kazakh horses, and provided an important theoretical basis and practical reference for optimizing the estrus synchronization treatment plan for Kazakh horses, adjusting the focus of feeding and management at each stage and improving the conception rate. Full article

In the scallop shucking industry, labor-intensive manual operations and inconsistent product quality remain persistent challenges. To address these issues, this study develops a scallop shucking system based on visual feedback temperature control. To support this system, systematic experiments are conducted to determine the baseline shucking method and its initial parameters. On this basis, the scallop doneness detection model SDD-RT-DETR, serving as the system’s core, integrates an enhanced backbone centered on the self-developed module HierarchicalRepBlock, a frequency-domain self-attention module AIFI-EDFFN, a neck featuring the self-developed EfficientBalanceFusion module as the feature fusion unit and the Converse2DC3 module as the feature extraction unit, and the Wise-DIoU loss function. A scallop doneness image dataset specifically constructed for this task was used to train and validate this model. Experimental results demonstrate that the model achieves 95.5% accuracy, 93.6% recall, and 96.1% mAP50, improving by 4.7%, 3.2%, and 4.2%, respectively, over the baseline model RT-DETR. Additionally, the model’s computational cost was reduced by 18.9%, and its parameters were reduced by 14.1% compared to the baseline model. This model provides real-time, accurate doneness assessment, thereby filling a gap in computer vision for scallop doneness detection. Furthermore, this study integrated this model into a water bath scallop shucking system with feedback temperature control, ensuring that the doneness of scallops after shucking is maintained within an optimal range. Batch tests show that this system achieves a 96.6% shucking rate and an 88.5% properly cooked rate, outperforming the conventional method. This improves the quality of automatically shucked scallops while offering a practical solution for the intelligent upgrading of the seafood processing industry. Full article

To address the problems of high moisture content, fine particle size, and limited conventional reutilization of stainless steel slag mud (SSSM), controlled low-strength material (CLSM) was prepared using SSSM as the primary solid component and cement together with ground granulated blast furnace slag (GGBS) as cementitious materials. The effects of GGBS replacing cement and SSSM, respectively, on the properties of CLSM and their variation patterns were investigated. Its solidification mechanism was analyzed through simulated control tests, X-ray diffraction (XRD), thermogravimetric–differential thermogravimetric analysis (TG-DTG), and scanning electron microscopy (SEM). The results show that, when GGBS replaces cement, the water-to-solid ratio and bleeding rate increase, while the compressive strength at all curing ages decreases overall; however, the 28 d strength still meets the requirement for CLSM. When GGBS replaces SSSM, the water-to-solid ratio and bleeding rate increase with GGBS fraction, and the compressive strength at all curing ages increases overall. At a GGBS fraction of 18%, the water-to-solid ratio reaches 0.363, the bleeding rate reaches 5%, and the 28 d and 60 d compressive strengths reach 7.3 and 11.2 MPa, respectively, representing increases of 23.3 and 21.4 times compared with the system without GGBS (0.3 and 0.5 MPa). The simulated SSSM substitution tests show that a synergistic solidification effect exists between SSSM and GGBS and contributes to strength development. Microstructural analysis shows that GGBS undergoes hydration under the alkali–sulfate environment provided by SSSM, generating ettringite (AFt) and calcium silicate hydrate (C-S-H gel), which fill pores and thereby enhance strength, while calcium hydroxide (Ca(OH)₂) provides an alkaline environment and promotes the participation of potentially active components in SSSM in the synergistic solidification process. Full article

Abrasive flow machining (AFM) is an effective finishing process for complex internal surfaces, particularly cavities, intersecting holes, and micro-channels that are difficult to access using conventional tools. However, when low-viscosity abrasive media is used (here defined, relative to conventional putty-like viscoelastic AFM carriers (with apparent viscosities of 10³–10⁵ mPa·s), as a water-based slurry with an apparent viscosity below 300 mPa·s over the operating shear-rate range), unfavorable flow conditions during the initial polishing stage can induce local over-polishing, erosion depressions, stepped patterns, and cavitation pits, resulting in non-uniform surface quality. The relationship between these flow behaviors and polishing defects remains insufficiently understood. To address this issue, this study investigates the AFM process applied to turbine blade film cooling holes through combined experimental and numerical approaches. The observed defects include erosion depressions, stepped surface patterns, and cavitation pits. The effects of abrasive injection pressure, flow velocity, hole geometry, abrasive viscosity, and particle size on defect formation are systematically examined. The results show that the initial abrasive filling level strongly affects defect distribution by altering the evolution of shear fields and void regions within the hole. Experimentally, at high Reynolds numbers (Re > 2 × 10⁴), intensified local shear and cavitation promote defect formation, while a moderate inclination angle (45–60°) and a higher aspect ratio (>8) are favorable for polishing uniformity. Complementary numerical simulations further indicate that smaller abrasive particles (<5 μm) and a moderate abrasive viscosity (~60 mPa·s) are predicted to improve polishing uniformity. This study clarifies the fluid-dynamic origin of polishing defects in film cooling holes and provides process guidance for suppressing local over-polishing, cavitation, and uneven material removal. Full article

Active area protection against unauthorized UAV swarms requires coordinated target assignment strategies that account for both low-level physical capabilities and the stochastic, consumptive nature of physical interceptions. This paper presents a decentralized target assignment framework based on probabilistic flow optimization. By utilizing an aerodynamics-aware flight model, we derive a probabilistic prior to capture the geometric dependency of terminal interception success under high-velocity maneuvers. Modeling the defense process as a probabilistic consumption flow couples initial tactical assignments with conditional transition flows, allowing surviving defensive assets to be proactively redistributed to secondary unauthorized intrusions. To resolve this problem under practical communication and sensing constraints, we develop the Distributed Flow-regularized Market-based Consensus (DFMC) algorithm. The proposed algorithm decomposes the global optimization into localized subproblems and employs a water-filling projection to plan secondary paths. Simulation results demonstrate that the proposed framework yields improved interception rates and better spatial resource dispersion compared to conventional auction-based baselines, while maintaining stable scalability in dense interception scenarios. Full article