Search Results (914)

Accurate modeling of smart composite dampers is crucial for simulation and model-based control. This study focuses on the constitutive modeling of a novel damper that synergistically combines an Entangled Metallic Wire Mesh (EMWM) with a magnetorheological (MR) fluid. Unlike traditional MR dampers, the interaction between the field-responsive MR fluid and the rate-sensitive, deformable EMWM matrix introduces strong coupled current–frequency dependence. To capture this essential characteristic, a control-oriented, bivariate (current–frequency) hysteresis model is formulated, wherein all parameters are explicit, continuous functions of both the control current (I) and excitation frequency (f). A systematic two-step identification method is employed to derive these functions from dynamic tests. A key finding is that the identified damping exponent (α) consistently exceeds unity across the tested operational range. This quantitatively indicates a transition from viscous-dominated to inertial-flow-dominated dissipation within the EMWM matrix, a distinctive mechanism attributed to non-Darcian flow in its porous structure. The fully parameterized model demonstrates high fidelity (R² > 0.99) within the characterized low-frequency, small-amplitude regime and shows reliable predictive capability for interpolated conditions. The presented model serves as a ready-to-use constitutive tool for the simulation and design of low-frequency vibration isolation systems utilizing EMWM-MR composites, and the revealed inertial flow mechanism provides fundamental insight for the development of next-generation adaptive dampers. Full article

With the increasing use of reinforced concrete segments in large-scale tunnels, engineering projects have placed higher mechanical demands on concrete, and the choice of concrete materials significantly influences these mechanical properties. This study is based on the preliminary mix design for the concrete used in the Second Undersea Tunnel Project, with the mass content of nano-SiO₂ (NS) (1–3%), the volume content of steel fibers (SF) (0.5–1.5%) and the volume content of polypropylene fibers (PPF) (0.05–0.25%) as independent variables and using compressive strength (Y₁), splitting tensile strength (Y₂), and toughness index (Y₃) as response variables. Using the Box–Behnken response surface design method, response surface models for each parameter were established and analyzed. The effects of NS, SF, and PPF on the mechanical properties of the concrete were investigated. Combining the MOPSO algorithm and the entropy-weighted TOPSIS method, a multi-objective cooperative optimization study was conducted. Finally, a microstructural analysis of the optimal NSDHFRC was performed. The results indicate that Y₁, Y₂, and Y₃ all initially increase and then decrease with increasing NS content; Y₁ and Y₃ increase with increasing SF content. However, when the SF content exceeds a certain level, the fiber spacing becomes too dense, weakening the effective bridging effect between fibers, resulting in a decrease in Y₂ at excessively high SF contents; PPF can suppress crack formation within a certain content range, but its effect on Y₁ is relatively weak. Due to agglomeration and water absorption, both Y₂ and Y₃ decrease when the PPF content is too high. It was determined that the optimal solution occurs when the mass fraction of NS is 2.15%, and the volume fractions of SF and PPF are 1.37% and 0.063%, respectively, with Y₁, Y₂, and Y₃ being 69.94 MPa, 5.49 MPa, and 1.99, respectively. Experimental verification confirmed that the relative error is within 5%. A microscopic analysis of the optimal solution revealed that an appropriate amount of NS refines the concrete structure through physical and chemical reactions, improves the interface transition zone, and enhances the bond strength between the fibers and the matrix. Meanwhile, PPF and SF distribute stress, respectively delaying the propagation of microcracks and macrocracks during different loading stages. These findings provide a reference for practical engineering applications. Full article

Water saturation is a key factor influencing the mechanical behavior and stability of tunnel rock masses in water-bearing strata. However, current research based on physical model tests has yet to systematically reveal its intrinsic relationship with rock failure modes. To address this gap, this study systematically investigated the effects of water saturation levels (0%, 33%, 58%, and 100%) on the failure mechanisms of four typical tunnel cross-section models: wall-arch, horseshoe, circular, and square. The results indicate the following: (1) Water saturation exerts a significant deteriorating effect on the mechanical properties of tunnel models. As saturation increases, peak stresses generally decrease across all models, but the extent of deterioration varies markedly by tunnel shape: at low saturation (≤58%), peak stress follows the order Wall-Arch > Horseshoe > Circular > Square; at high saturation (>58%), this relationship reverses to Circular > Square > Wall-Arch > Horseshoe. (2) The failure mechanism is significantly controlled by saturation, exhibiting distinct transition characteristics: At low saturation, capillary effects dominate, with matrix suction enhancing material strength, resulting in brittle failure with crack concentration. At high saturation, pore water pressure effects prevail, reducing effective stress and leading to plastic failure dominated by distributed shear slip. Notably, square tunnels consistently exhibit pronounced flexural failure characteristics across all saturation levels. (3) Energy evolution analysis indicates the following: as saturation increases, the total energy U of specimens decreases, the dissipation rate of dissipated energy U_d accelerates, the energy inflection point advances, and failure precursors manifest earlier. The energy dissipation factor n of high-saturation specimens decreases more significantly with increasing strain, confirming that moisture accelerates energy dissipation and promotes premature material instability. (4) Significant differences exist in the response characteristics to moisture effects among tunnel types: Square tunnels consistently exhibit pronounced flexural failure; Circular tunnels demonstrate optimal stress distribution properties under high water content conditions; Wall-arch and horseshoe-shaped tunnels are most sensitive to saturation changes, with their failure modes transitioning from tensile-dominated to shear failure as water content increases. This study reveals the coupled mechanism between water saturation and tunnel cross-sectional shape in influencing rock mass stability. Full article

In a network invaded by a mutant according to the birth–death updating rule and uniform initialization, in order to minimize the amplifying effect of any directed network, the adjacency matrix is modified at each time step up to a given time horizon, subject to resource constraints. The fixation probability of an invasive mutant is deduced from the first eigenvector of the resulting modified Markov transition matrix. Large-scale minimization is solved numerically for a representative sample of directed graphs of dimensions 6 to 8. The effects of the determinants of the optimal reduction of the fixation probability are estimated using a Heckman selection model. The number of neighbors, the heterogeneity of the incoming edge weights, and the homogeneity of the outgoing edge weights of the initial network increase the likelihood that the graphs are amendable. Among the amended networks, the reduction in the fixation probability is greater when the outgoing edge weights of the initial network are heterogeneous, those of its incoming edges are homogeneous, and the sequence of modifications increases the variance of the outgoing edge weights and decreases that of the incoming edge weights, thereby creating a trade-off, which is estimated numerically. Full article

The accurate inference of hidden states from non-stationary physiological signals remains a significant challenge in stochastic process modeling. This paper proposes an Adaptive Sticky Hidden Markov Model (Sticky-HMM) framework designed to enhance the robustness of state decoding in noisy environments. To address the “state-flickering” issue inherent in traditional HMMs, we incorporate a “Sticky” parameter into the transition matrix, imposing a temporal penalty on spurious state switching to maintain continuity. Furthermore, we introduce a Dynamic Prior Strategy that adaptively calibrates self-transition probabilities by mapping frequency-domain features of the observed sequence to the model’s parameter space. The proposed decoding process employs a two-pass refinement strategy and the Viterbi algorithm in the logarithmic domain to ensure numerical stability. The model’s efficacy was validated using a high-fidelity dataset of simulated apnea events. This work provides a computationally efficient and mathematically rigorous approach that demonstrates strong potential for long-term respiratory health monitoring. Full article

Modeling immune cell recruitment within a wound-relevant microenvironment remains challenging. Here, we developed a novel skin-derived extracellular matrix (ECM) hydrogel model to study monocyte (THP-1) entry and phenotypic changes within a dermal fibroblast-populated (NHDF) matrix. The main novelty of this study is that it compares the effects of fibroblast-derived soluble signals and active monocyte infiltration in a 3D biomimetic model. Signaling by fibroblast-secreted soluble factors enhanced a pro-angiogenic secretome (e.g., >3-fold upregulation of VEGFA at day 1) and promoted endothelial tube formation (increasing network junctions to 1.16 ± 0.16 vs. 0.93 ± 0.23 in monoculture). In contrast, this paracrine signaling did not induce the matrix-driven pro-fibrotic response in hydrogels. Crucially, physical immune infiltration restricted monocyte penetration (mean depth of 8.92 ± 2.27 μm vs. 121.1 ± 15.9 μm in monoculture at day 5), reduced hydrogel-induced myofibroblast activation (decreasing α-SMA+ cells from 79.1% to 54.3% upon initial contact), and was associated with slower collagen loss during the early phase. (retaining a high-density collagen ratio of 3.46 ± 0.33 vs. 2.02 ± 0.29 in monoculture at day 1). These observations were accompanied by a shift toward a matrix-stabilizing profile, including increased TIMP expression and reduced pro-fibrotic markers. (ACTA2 and COL1A1). By including active immune infiltration (which was absent in previous tSVF models), we capture the transition from inflammation to the proliferation stage. Although the later stages of extensive ECM remodeling appear suppressed here, they may occur as repair progresses. Overall, our findings highlight that the immune cell is a key regulatory component for coordinating matrix preservation and vascular support. Importantly, this model replicates the early phases of wound healing, a stage where the monocyte–fibroblast secretome supports endothelial network formation. We established this innovative 3D ECM hydrogel system as a practical and physiologically relevant platform to investigate immune–matrix–stromal crosstalk. Full article

Indoor Environmental Quality (IEQ) plays a vital role in occupant health and productivity. However, current Building Management Systems (BMS) often struggle in sustaining optimal IEQ levels due to limitations in data management and lack of occupant-centric feedback loops. To address these gaps, this research synthesizes the state-of-the-art methods for IEQ monitoring, assessment, and control within Building Automation Systems (BAS), identifying both technological and methodological advancements, as well as highlighting the challenges and potential opportunities for future innovations. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, this multi-stage literature review analyzes 176 publications from 1997 to 2024, with a focus on the decade of rapid technological evolution from 2014 to 2024. The review focuses on high-impact journals indexed in Scopus to ensure quality while acknowledging the potential bias inherent in a single-database search. The synthesis reveals a methodological shift in monitoring from sparse, zone-level sensing towards dense, multi-modal systems that incorporate physiological data via wearables and behavioral recognition through computer vision. Assessment techniques are evolving from static models such as the Predicted Mean Vote (PMV) towards adaptive, personalized frameworks supported by Digital Twins and integrated simulations. Furthermore, control logic is transitioning toward Reinforcement Learning and Model Predictive Control to proactively manage occupancy surges and environmental variables. This evolution of monitoring approaches, assessment techniques, and control strategies is represented within the study’s Three-Tiered Developmental Trajectory, providing a novel Body of Knowledge (BOK) for mapping the transition of building systems from reactive tools to autonomous, occupant-centric agents. This study also introduces a Cross-Modal Interaction Matrix to systematically analyze the systemic trade-offs between IEQ domains. Furthermore, by establishing the “Implementation Frontier,” this work identifies the specific technical and ethical bottlenecks, such as “false vacancy” sensing errors, fragmented data silos, and the ethical complexities of high-resolution data collection that prevent academic innovations from becoming industry standards. To bridge these gaps, we conclude that the next generation of “cognitive buildings” must prioritize three pillars: resolving binary sensing limitations, harmonizing data via vendor-neutral APIs, and adopting privacy-preserving architectures to ensure scalable, interoperable, and occupant-centric optimization. Full article

The endothelial protein C receptor (EPCR) is an important component of the protein C (PC) system, recognised for its diverse roles in blood coagulation, inflammation, and stem cell regulation. Wound healing is a complex physiological process that can be divided into four distinct but overlapping phases: haemostasis, inflammation, proliferation and remodelling. Recently, EPCR has emerged as a key regulator in wound repair and regeneration. During haemostasis, EPCR enhances the conversion of PC to its activated form (APC) to optimise local and systemic anticoagulation. In the inflammatory phase, EPCR modulates immune cell activity, inhibits inflammatory factors, and maintains tissue barrier integrity. As the process transitions to the proliferative phase, EPCR promotes endothelial and epithelial cell proliferation, migration, neovascularisation and re-epithelization, and mediates the expression of matrix metalloproteinases to facilitate tissue reconstruction. Finally, during the remodelling phase, EPCR exerts a potential antifibrotic effect by regulating fibroblast activation and collagen deposition via the Transforming growth factor (TGF)-β1/Smad3 pathway, ensuring functional repair. While therapeutic potential has been shown in animal models, translating EPCR-mediated therapies to clinical application faces many challenges, including wound heterogeneity, dosage control, targeted delivery, and potential bleeding risks. Studies have shown that local drug delivery strategies, non-anticoagulant APC variants, and individualised treatment based on EPCR expression will be the key directions for future development. Additionally, EPCR may serve as a potential biomarker for assessing wound severity and guiding personalised interventions. Full article

Background: Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense desmoplastic stroma that actively drives malignant progression. However, the specific contributions of E3 ubiquitin ligases within the cancer-associated fibroblast (CAFs) compartment to the PDAC landscape remain largely elusive. Methods: Pancreatic tissue samples were collected from the First Affiliated Hospital of Harbin Medical University. Gene expression was analyzed by RT-PCR, and single-cell RNA sequencing (scRNA-seq) data were integrated for cell subtype identification. Kaplan-Meier survival analysis assessed gene expression and survival. Pseudotime analysis and CellChat evaluated fibroblast transitions and intercellular communication. Cell lines were transfected with RBX1 siRNAs, and protein levels were measured by Western blotting. Proliferation was assessed using colony formation and EdU staining. Statistical analyses were performed using R (v4.4) and GraphPad Prism 8.0. Results: Thirteen E3 ubiquitin ligases were significantly upregulated in PDAC and correlated with unfavorable clinical outcomes. Among these, RBX1 was identified as a candidate preferentially expressed in CAF populations and strongly associated with poor prognosis. Single-cell transcriptomic profiling and pseudotime analysis further revealed that RBX1-positive CAFs were predominantly involved in extracellular matrix remodeling and pro-tumorigenic pathways. Functional assays demonstrated that silencing RBX1 markedly inhibited PAAD cell proliferation and tumor growth both in vitro and in xenograft models. Mechanistically, RBX1 was found to upregulate Tenascin C (TNC) expression, while ectopic overexpression of TNC partially rescued the growth suppression induced by RBX1 knockdown. Conclusions: Our findings suggest that RBX1 facilitates PDAC progression through a CAF-related mechanism and TNC regulation, positioning RBX1 as a potential therapeutic target for PDAC intervention. Full article

This paper investigates the stability of telehandlers operating on inclined terrain through a sequential methodological approach. In a first stage, stability is assessed using quasi-static methods based on force and moment equilibrium, including the load transfer matrix and the stability pyramid. These approaches account for gravitational and inertial effects through equivalent external forces and moments applied at the global centre of gravity, enabling efficient evaluation of load redistribution and proximity to rollover thresholds under generalized quasi-static conditions. The application of these methods highlights intrinsic limitations when addressing structurally complex machines such as telehandlers equipped with a pivoting rear axle and evolving mass distribution due to boom motion. In particular, quasi-static approaches require a priori assumptions regarding the effective rollover axis and cannot fully capture the coupled geometric and contact interactions between rear axle articulation limits, centre of gravity migration, tyre–ground interface behaviour, and support polygon evolution. To overcome these limitations, a nonlinear dynamic multibody model based on the three-dimensional Bond Graph (3D Bond Graph) methodology is introduced. The model is implemented within a virtual tilt–rotation test platform and validated against experimental results obtained from ISO 22915-14 stability tests. The comparison confirms compliance with normative requirements and demonstrates that the dynamic framework captures condition-dependent rollover mechanisms and transitions between distinct virtual rollover axes that cannot be fully explained by quasi-static formulations. Unlike most previous studies, which focus on fixed configurations or forward-driving scenarios, the proposed framework analyzes stability evolution under spatial inclination while accounting for structural articulation constraints. The explicit identification of rollover axis transitions induced by rear axle articulation provides a deeper mechanistic interpretation of telehandler stability and supports the use of high-fidelity dynamic simulation as a complementary tool for test interpretation, experimental planning, and the development of predictive stability and operator assistance systems. Full article

Engineering sizing of seasonal underground thermal energy storage (SUTES) systems remains constrained by the complex coupling of heat and moisture transport in unsaturated porous media. Neglecting these coupling effects can lead to significant errors in the design of borehole length and spacing. This study presents a three-dimensional numerical investigation of a coaxial borehole heat exchanger (CBHE) field over a full annual cycle, including storage, transition, extraction, and recovery stages. A coupled heat–moisture transfer model for the soil–CBHE system is developed and validated against experimental data, yielding mean relative errors of 6.8% for temperature and 7.7% for volumetric water content. The model is then used to quantify the sensitivity of SUTES performance to the initial volumetric water content (θ₀). Increasing θ₀ from 0.20 to 0.40 m³·m⁻³ enhances the average heat injection rate per unit depth by 6.6% (from 53.84 to 57.39 W·m⁻¹) and the heat extraction rate by 7.1% (from 23.73 to 25.41 W·m⁻¹). This enhancement is primarily attributed to increased effective thermal conductivity and heat capacity, together with moisture migration and the associated latent-heat effects within the soil matrix. While the variations in seasonal energy and exergy efficiencies are within 1 percentage point, radial soil-temperature uniformity and effective heat diffusion are significantly improved in moister soils. These findings clarify the coupled transport mechanisms in borehole seasonal storage and provide engineering guidance for sizing CBHE fields in unsaturated formations. Full article

This study investigates the early-age bond behavior between steel reinforcement and lightweight alkali-activated concrete (LWA-AAC) using pull-out tests and modeling. Deformed and plain steel bars with different diameters were embedded in two LWA-AAC matrices to examine the effects of curing age, matrix strength, confinement, and bar surface geometry. The bond of plain bars is governed primarily by adhesion and friction and shows weak dependence on matrix strength or confinement. In contrast, the bond strength of deformed bars increases with curing age and matrix strength, while reduced confinement promotes a transition from ductile pull-out to brittle splitting failure. This confinement-sensitive transition highlights the dominant role of matrix tensile capacity in controlling bond stability in LWA-AAC. Compared with lightweight ordinary Portland cement (OPC) concrete, LWA-AAC exhibits more brittle bond behavior, characterized by smaller peak slip, steeper post-peak softening, and lower residual bond stress. Existing OPC-based bond models show limited applicability to LWA-AAC due to differences in failure mechanisms and confinement sensitivity. New empirical models incorporating matrix tensile strength and geometric confinement are proposed to predict bond parameters and bond–slip responses, providing a mechanism-informed basis for the design of reinforced LWA-AAC structures. Full article

Existing ferroresonance fault identification methods often suffer from high misclassification rates, strong threshold dependency, and insufficient noise resistance. To bridge this gap, we propose a novel ferroresonance fault recognition method based on the Markov transition field (MTF) and three-branch Gaussian clustering (TBGC). Firstly, a symplectic geometric algorithm is employed to denoise the resonance feature signal, extract effective dominant modes, and reshape the series. Secondly, the reshaped feature series is converted into a Pixel matrix image employing the MTF. Subsequently, the gray-level co-occurrence matrix (GLCM) is utilized to extract the two-dimensional texture features of MTF images corresponding to different resonance types and construct corresponding TBGC models. Finally, the overvoltage sequence to be recognized is input into the TBGC model after feature extraction, and accurate discrimination of ferroresonance types is achieved based on cosine similarity. The analysis of fault recording data indicates that this method achieves 100% discrimination accuracy in eight test cases, surpassing the comparative method (maximum accuracy of 62.5%) by 37.5%, thereby validating its effectiveness and accuracy in ferroresonance identification. Full article

Global high-mountain ecosystems are increasingly subjected to intensified anthropogenic disturbances, which facilitate the spread of invasive alien plants and threaten agricultural sustainability and ecological security. Using Laojun Mountain in Yunnan as the study area, this research investigates the relationship between the distribution patterns of invasive plants and land-use changes, based on data from 38 transect surveys conducted in 2023 and 30-m-resolution land-use data spanning 2003–2023. The analysis incorporates a random forest model and a land-use transition matrix. The key findings are as follows: (1) Variable importance analysis revealed elevation as the most critical factor influencing invasion occurrence (mean decrease in Gini index: 8.0), followed by slope, aspect, and land-use type. (2) Cultivated land exhibited the highest probability of invasion, with high-risk areas (>0.8) concentrated in agricultural zones in the central-southern and northeastern regions. (3) From 2003 to 2023, cultivated land increased by a net area of 20.85 km², primarily due to conversion from forests (19.57 km²) and grasslands, while grassland area decreased by 24.70 km². This study concludes that agricultural expansion has intensified habitat fragmentation and anthropogenic disturbances, creating favorable conditions for invasive plant establishment. It is recommended that invasive species monitoring and ecological restoration efforts be strengthened in agroforestry transition zones to enhance landscape resilience against biological invasions. Full article

To enable autonomous route planning for UAV swarms in dynamic air–terrestrial cooperative navigation scenarios within GNSS-denied environments, this paper proposes a lightweight framework based on the Artificial Potential Field (APF) method. In the considered architecture, UAVs act as mobile transit navigation nodes that relay positioning information from sparse ground anchors to terrestrial users. For TOA-based cooperative positioning, the instantaneous geometric configuration of the UAV swarm significantly affects the overall system accuracy. Therefore, the impact of UAV positions on the end-to-end navigation performance is rigorously analyzed, yielding a comprehensive Dilution of Precision (DOP) matrix for the entire air–terrestrial system. By applying the Schur complement, the global performance metric is decomposed, resulting in a scalar evaluation function that directly reflects the geometric quality of the configuration. In practical scenarios involving dynamic and heterogeneous users, real-time trajectory adaptation of the UAV swarm is essential to continuously optimize user positioning accuracy. To this end, an APF-based autonomous joint route planning approach is developed. The potential field is constructed directly from the derived geometric evaluation model, where its negative gradient generates virtual forces that autonomously guide the UAV swarm. This elegantly bridges high-level navigation performance optimization with low-level motion control of the swarm. The simulation results show a 76.1% improvement in the average comprehensive GDOP for users compared to the baseline of hovering UAVs, validating the effectiveness and real-time capability of the proposed lightweight framework. Full article