Search Results (1,920)

Adhesion between fused deposition modelling (FDM) printed polymers and textile substrates is critical for durable printed-on-textile hybrids. Since no dedicated test standard exists for additively manufactured textile interfaces, many studies use T-peel methods adapted from adhesive-bond standards. However, printed-on-textile joints are often governed by polymer penetration into the fabric and mechanical interlocking, rather than by a discrete adhesive layer. This work evaluates a fixture-based perpendicular (normal-separation) tensile method, using a circular dolly printed directly onto a cotton plain-weave substrate and a fully 3D-printable, threaded, self-aligning clamping assembly. Three representative filaments, namely polyethylene terephthalate glycol-modified (PETG), polylactic acid (PLA), and thermoplastic polyurethane (TPU), were tested using both the proposed pull-off method and an ISO 11339-type T-peel benchmark, with n = 8 specimens per polymer. The perpendicular method produced complete datasets for all polymers and clearly differentiated adhesion performance (TPU > PLA > PETG). In contrast, for T-peel, the standard evaluation window (25–125 mm) was completed for all PETG specimens but only for a subset of PLA specimens and a single TPU specimen. In the remaining tests, premature substrate failure prevented completion of this window, so the results could not be evaluated. Microscopy confirmed distinct interlocking morphologies across polymers, supporting the observed differences in failure behavior between peel and normal separation. Overall, the results indicate that perpendicular dolly pull-off testing is a practical and reproducible alternative for quantifying adhesion across a wider range of printed-on-textile bonding conditions. Full article

Objectives: To evaluate the effectiveness and durability of matrix-associated autologous chondrocyte implantation with periosteal flap (pMACI) in treating knee cartilage defects using clinical scores and MRI evaluations. Methods: Data were collected from 37 knees of 17 patients, with a mean follow-up of 5 years (range: 0.1–20 years). Clinical outcomes were assessed using the Lysholm Knee Scoring Scale (LKS) and Knee Injury and Osteoarthritis Outcome Score (KOOS). Tissue quality was quantitatively evaluated using MRI T1ρ and T2 mapping (biochemical) and MR observation of cartilage repair tissue: MOCART 2.0 (morphological). A linear mixed model was used to identify factors affecting outcomes, including etiology (trauma, OCD, OA), graft site, and defect size. Results: At the 20-year follow-up, clinical scores remained significantly improved from baseline (mean LKS: 55.6 to 86.5; KOOS: 37.8 to 70.8). The biochemical MRI parameters (T1ρ and T2 values) stabilized at levels comparable to native cartilage across all etiologies and sites (p = 0.326 and 0.412, respectively), indicating stable long-term tissue quality. In contrast, the MOCART 2.0 scores significantly declined over time (annual rate: −1.14 points; p < 0.001). Etiology was a significant factor; the OA group showed significantly lower clinical and MOCART scores compared to the trauma/OCD groups (p < 0.05). However, no significant differences were found in LKS and KOOS based on graft site (p = 0.489) or defect size (p > 0.05). Conclusions: pMACI may be a highly durable treatment capable of maintaining biological tissue quality and providing clinical benefits for two decades. The observed morphological deterioration after 20 years likely reflects joint-wide aging—especially in OA cases—rather than graft failure, highlighting the importance of long-term MRI monitoring. Full article

Single-lap shear joints made from fabric T300/polyphenylene sulfide (T300/PPS) and unidirectional T700/low-melt polyaryletherketone (T700/LM-PAEK) laminates are joined via induction and conduction welding at different processing temperatures. The joints are tested experimentally to investigate the influence of the processing temperature on the damage evolution in the specimens which is tracked using digital image correlation. Cracks grow rapidly in the unwelded parts of the joint interface but assume a stable steady-state propagation rate when reaching the fully welded overlap region. It is found that higher welding temperatures lead to longer weld lengths, which improve the strength and stiffness of the specimens and delay damage initiation. An accelerated crack growth rate indicates that the structure is close to its ultimate load after which the joint fails abruptly as the crack growth becomes unstable. Induction welding temperatures at the upper end of the recommended processing window (330 C for T300/PPS and 385 C for T700/LM-PAEK) result in the joints with the highest load-carrying capacity and slowest crack propagation, but also the least damage tolerance. Full article

Background: Asymptomatic structural joint abnormalities are prevalent among athletes, yet studies on their multi-joint distribution and comparisons with low-activity controls remain lacking. This article evaluated the prevalence and characteristics of asymptomatic structural abnormalities across joints in collegiate athletes compared with controls using 3.0-T MRI. Methods: The cross-sectional study enrolled 53 asymptomatic elite collegiate athletes (high physical activity, HPA) and 84 healthy volunteers (low physical activity, LPA) aged 18–25 years. All participants were asymptomatic with no history of joint trauma or surgery. Generalized estimating equation (GEE) logistic regression was employed to identify independent risk factors for joint abnormalities after evaluation. Results: A total of 666 joints were analyzed. Participants with at least one joint abnormality were significantly more common in the HPA group than LPA group (49.1% vs. 6.0%, p < 0.001). At the joint level, overall abnormality prevalence was 13.5% versus 2.2%, respectively. In the HPA group, knee joints were the most frequently affected (24.2%), predominantly involving meniscal lesions. Shoulder pathologies consisted exclusively of supraspinatus tendon lesions (6.8%), while ankle abnormalities were primarily bone marrow edema (5.9%). GEE analysis identified high physical activity (adjusted OR = 5.23; 95% CI: 1.55–17.71; p = 0.008) and elevated BMI (adjusted OR = 1.09 per kg/m²; 95% CI: 1.03–1.15; p = 0.001) as independent risk factors. Conclusions: Asymptomatic abnormalities are highly prevalent and demonstrate intra-individual clustering across multiple joints. MRI-based surveillance represents a promising strategy for early risk identification and injury prevention. Full article

Cutaneous T-cell lymphoma (CTCL), primarily mycosis fungoides (MF) and Sézary syndrome (SS), has long been characterized as a neoplasm of mature memory T cells, based on monoclonal T-cell receptor (TCR) rearrangements and tissue-resident memory (TRM)/central memory (TCM) T-cell phenotypes. This review synthesizes converging population-genetic, multi-omic, and single-cell evidence to argue that this characterization is incomplete and that a progenitor-based model better accounts for the full spectrum of disease biology. We present evidence that initiating mutations arise in hematopoietic stem or early lymphoid progenitor survive thymic selection, and diversify after TCR assembly, resulting in branched evolution across both blood and skin. In SS, paired analyses reveal > 200 shared variants between CD34⁺ progenitors and Sézary cells, as well as signal-joint T-cell receptor excision circle (sjTREC) positivity, providing direct progenitor-level evidence. In MF, convergent signals, multiple malignant clonotypes per lesion, greater blood–skin than skin–skin clonotype overlap, and compartment-specific CNV subclones, implicate hematogenous seeding and reseeding. Population-scale lymphoid clonal hematopoiesis and lymphoid-pattern mosaic chromosomal alterations define a compatible antecedent state. Spatial single-cell atlases and trajectory analyses map site-conditioned programs in skin, including Th2-skewed cytokines, microbial responses, and UV signatures, that select and expand subclones and explain inter- and intra-patient heterogeneity. This framework reconciles mature immunophenotypes with upstream initiation and clarifies why compartment-focused therapies often reshape rather than eradicate disease. It yields testable predictions and actionable implications: trials should pair multicompartment cytoreduction with strategies that attenuate progenitor-derived reservoirs, restore immune balance, and repair skin barrier dysfunction. A progenitor-initiated, niche-adapted model provides a coherent scaffold for more durable control in CTCL. Full article

Rheumatoid arthritis (RA) has traditionally been managed after the onset of clinically apparent synovitis; however, accumulating evidence indicates that disease-related immune abnormalities precede clinical diagnosis by several years. This preclinical phase is characterized by systemic autoimmunity, early musculoskeletal symptoms, and subclinical inflammation in genetically and environmentally susceptible individuals. In this review, we summarize current concepts regarding the pathogenesis, risk stratification, and therapeutic interception of preclinical RA. Particular attention is given to the mucosal origin hypothesis and to the roles of immunosenescence, peripheral helper T cells, and fibroblast-like synoviocytes in early disease evolution. Recent advances in clinical, serological, and imaging-based risk stratification have improved the identification of individuals at high risk of progression to clinical RA, and emerging intervention trials have shown that selected therapies may delay disease onset or reduce early inflammatory burden. Although complete prevention of RA has not yet been achieved, these findings support a paradigm shift from the treatment of established RA toward earlier, risk-adapted intervention before irreversible joint damage occurs. Future efforts should focus on refining predictive biomarkers, optimizing the timing and intensity of intervention, and establishing safe, individualized preventive strategies. Full article

With the development of intelligent transportation systems, vehicular applications demonstrate diverse characteristics, including computation-intensive processing and stringent latency requirements. Traditional computation offloading strategies struggle to cope with the highly dynamic, multi-node, and multi-task concurrent vehicular network environment and generally overlook the risk of cross-zone communication failures caused by high-speed mobility. To address this issue, this paper designs a computation offloading algorithm based on multi-agent reinforcement learning. This method comprehensively considers four heterogeneous features including queue load, communication links, task attributes, and computing resources, establishes a multi-layer collaborative computing architecture integrating task migration and result return mechanisms, and further constructs an optimization model aimed at minimizing the weighted sum of latency and energy consumption. This model is formalized as a multi-agent Markov decision process, and an improved Multi-Agent Proximal Policy Optimization(MAPPO)-based MATPPO-T algorithm is designed to solve it, achieving one-step joint optimization of task offloading, resource allocation, and task result migration. Experimental results demonstrate that the proposed method reduces the total system cost by approximately 22% on average compared to benchmark algorithms such as MAPPO and PPO, while consistently maintaining the lowest offloading overhead and fastest convergence speed, validating its robustness and scalability in dynamic vehicular edge networks. Full article

Backscatter communication (BackCom) has emerged as an energy-efficient and low-cost communication paradigm, in which wireless devices transmit information by reflecting incident signals rather than actively generating radio frequency signals. Owing to the extremely low power consumption and hardware cost, BackCom is particularly suitable for Internet of Things (IoT) devices with stringent low energy and cost constraints. However, due to the severe double channel attenuation inherent in backscatter links, conventional ground-based deployment of transmitters and receivers often suffers from poor communication quality and low energy efficiency. Unmanned aerial vehicles (UAVs), with their high mobility and favorable line-of-sight (LoS) links, can act as dynamic aerial transmitters and receivers in BackCom, thereby mitigating channel attenuation and improving both communication reliability and energy efficiency. To enhance the data collection efficiency of UAV-assisted BackCom systems under a limited mission duration, this paper proposes a joint optimization method for communication resource allocation and UAV trajectory design under task time constraints. Specifically, a mixed-integer non-convex optimization problem is formulated to maximize the number of devices served by the UAV within a given task duration. The original problem is then decomposed into two subproblems, namely communication resource allocation optimization and UAV trajectory optimization. An iterative algorithm based on Block Coordinate Descent (BCD) and Successive convex approximation (SCA) is developed to obtain an efficient solution. Simulation results demonstrate that the proposed method can effectively increase the number of served devices within the specified mission time limit. Full article

Future fusion power plants like DEMO must be remotely maintained for safety, including breeding blankets (BBs) weighing up to 180$\mathrm{t}$. The BB vertical transporter (BBVT), a crane-like redundant robot with 7 joints, has been previously designed for handling the five unique BB segments per sector. This includes grasping, preloading and collision-free spatial manipulation of BB segments in a space-constrained environment, necessitating advanced motion planning and real-time control. To achieve this, the challenge of obtaining accurate and performant inverse kinematic (IK) solutions for the redundant BBVT must be addressed. Therefore, a kinematic model is presented, and the redundant IK probelm is solved analytically for task-relevant cases, including derivation and analysis of the Jacobian. The model is verified by comparison with an MSC Adams model. Meanwhile, the analytical IK is found to be 53× to 84× faster than a gradient projection-based numerical solver in Matlab while providing multiple solutions. The IK and Jacobian are applied to create collision-free waypoints, verified in Matlab, for handling each BB segment while minimizing static joint loads in key configurations. A first-order estimate of the total BB handling time for a maintenance of nine days is calculated. These developments support the feasibility of the BBVT robot for the BB maintenance task in DEMO, and underpin future efforts in modelling dynamics and achieving real-time resilient control. Full article

Understanding dry-out-induced weakening of reservoir and caprock rocks driven by gas displacement is critical for ensuring the operational safety and efficiency of underground gas storage (UGS). Using core samples from the Xiangguosi UGS collected from different regions and stratigraphic intervals, we quantify the evolution of dynamic elastic parameters during simulated downhole dry-out with a joint ultrasonic and nuclear magnetic resonance (NMR) monitoring system. The results show that as water saturation (S_w) decreases, the dynamic bulk modulus (K_d) and P-wave velocity (V_p) decline by varying degrees across specimens, with reductions ranging from 3.0% to 50.48% and from 1.34% to 17.56%, respectively, whereas the dynamic shear modulus (G_d) and S-wave velocity (V_s) show only minor variations throughout the process. These findings demonstrate that the sensitivity of dynamic parameters to dry-out is strongly specimen-dependent. Further analysis indicates that the dry-out response is highly variable and depends on a combination of petrophysical properties. Among these, the heterogeneity of the initial pore structure acts as an important factor, with its influence shaped by mineralogy and bulk frame rigidity. Cores with multimodal pore size distributions and well-developed macropores (long T₂ components) respond more strongly to dry-out, whereas higher clay mineral contents tend to mitigate modulus degradation by retaining water under stronger capillary confinement. Based on these observations, we propose a conceptual model of pore support and skeleton constraint. The model suggests that dry-out weakening arises from a progressive loss of pore fluid volumetric support to the rock skeleton as free water is preferentially displaced from meso- and macropores. These findings provide key experimental evidence and mechanistic insights for using geophysical methods to monitor dry-out zone expansion and to assess long-term formation stability in UGS. Full article

In IIoT edge computing, multi-edge server collaborative scheduling faces two core issues due to random task arrivals, heterogeneous resources, and complex topology: traditional model-driven methods cannot make dynamic decisions in dynamic environments, and conventional MARL fails to characterize inter-node topological dependencies and load correlations. To address this, this paper investigates the joint optimization of task offloading, computing resource allocation, and SFC orchestration in IIoT, constructs a cloud-edge-end collaborative architecture, and models the problem as a POMDP to minimize the overall system cost under multiple constraints. A graph-guided value-decomposition MARL method is proposed, which extracts spatial topology and neighborhood-load features of edge nodes via a GNN and combines them with the QMIX framework to realize multi-agent centralized training and distributed execution. Simulations show that the algorithm converges stably under different server scales and task loads, significantly outperforms benchmark algorithms, and can suppress performance degradation in high-load scenarios, demonstrating its robustness and scalability in complex industrial environments. Full article

Temporomandibular disorders (TMDs) are the prevalent causes of orofacial pain and dysfunction of the temporomandibular joint (TMJ) and masticatory muscles. Previous studies have revealed that proinflammatory cytokines play a key role in promoting inflammation, pain, and degeneration within the TMJ. In this context, the present systematic review synthesizes current evidence on various cytokines involved in the pathophysiology of TMDs and evaluates their associations with clinical signs and structural TMJ damage. A PRISMA-guided search (PROSPERO: CRD420251163290) was conducted in PubMed/MEDLINE, Embase, Scopus, and the Cochrane Library to identify human-based, in vivo, and in vitro studies (January 2014 to September 2025) that assessed the roles of proinflammatory cytokines in TMDs. The following data were extracted from the identified studies: cytokine profiles, sampling methods, clinical outcomes, and TMJ structural changes. Study quality and risk of bias were systematically evaluated. A total of 15 studies (clinical, animal, and mechanistic) were included in the review. Tumor necrosis factor-alpha (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6), and interleukin-17 (IL-17) consistently emerged as the major contributors to synovitis, cartilage degradation, nociceptive sensitization, and bone resorption. Human studies showed that high levels of TNF-α, IL-1β, and IL-6 and chemokines such as C-C motif chemokine ligand 2 (CCL2) and regulated on activation, normal T-cell expressed and secreted (RANTES) were associated with TMJ pain, restricted mandibular motion, crepitus, malocclusion, and erosive changes on imaging. An increased ratio of TNF to soluble TNF receptor in synovial fluid correlated with both pain and condylar damage, suggesting that loss of cytokine control contributes to progressive joint destruction. TMDs, particularly inflammatory and degenerative subtypes, are cytokine-driven pathologies rather than purely mechanical disorders. TNF-α, IL-1β, and IL-6 are the promising candidate biomarkers of local inflammation and structural joint pathology. Standardized longitudinal studies are required to validate cytokine-based diagnostics and develop anti-cytokine therapeutics. Full article

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterised by persistent joint inflammation and systemic immune dysregulation. While bone marrow activation has been linked to RA pathogenesis, direct access to bone marrow tissue for progenitor analysis remains limited by ethical and technical constraints. Analysis of progenitor cells in peripheral blood can serve as a surrogate reflecting bone marrow activation. In this study, we analysed peripheral blood cells from 12 RA patients and 9 healthy controls using high-dimensional spectral flow cytometry with a nine-marker panel (CD45, CD31, CD235, CD133, CD34, CD105, CD271, CD90, PDPN). Flow Self-Organizing Map (FlowSOM) clustering identified 20 distinct cell populations. Additionally, a complementary flow cytometry panel was used to assess CD31 expression on immune subsets in peripheral mononuclear cells (PBMCs) from 9 RA and 9 healthy donors of this cohort. RA patients showed increased CD45⁺CD31⁻ immune cells, but not their putative progenitors. Conversely, putative CD45⁺CD31^int progenitors and CD45⁺CD31^int mature cells were reduced, along with CD31 expression on T cells. Levels of CD235a⁺ putative erythroid precursors and CD45⁺CD31⁺ progenitors were significantly increased in RA patients. Three putative stromal cell populations were detected in circulation. Together, these findings reveal expanded erythroid precursor populations and reduced CD31 expression on T cells in RA. Our data underscore broad systemic alterations in cellular homeostasis in RA patients. In conclusion, our results suggest that the loss of CD31 expression on immune cell precursors plays a role in age-associated immune remodelling and immune activation in RA and provides the rationale for further studies on erythroblast differentiation and the functional role of erythroblasts in chronic inflammation. Full article

Accurate calibration is essential for ensuring the performance of magnetic gradient tensor (MGT) arrays. Existing calibration methods generally rely on mechanical rotation to obtain magnetic responses under multiple orientations. However, for large-scale cubic MGT arrays, rotating the entire array using a high-precision non-magnetic turntable is often costly and impractical, while manual rotation is difficult to control and may introduce array-center offsets. To address these limitations, this paper proposes a rotation-free scalar calibration framework for cubic MGT arrays, in which a tri-axial Helmholtz coil system generates constant-magnitude magnetic fields with randomized orientations while compensating for ambient magnetic drifts. Based on the acquired data, a hierarchical calibration algorithm is developed to estimate sensor-level intrinsic errors and array-level misalignment errors. Experimental results show that the proposed method reduces the joint tensor invariant $C_T$ from $9.07\times {10}^3$ nT/m to 11.51 nT/m, corresponding to a 99.87% reduction. In addition, compared with a conventional rotation-based fast calibration method, the proposed framework further decreases the mean and RMS of the joint $C_T$ by 62.7% and 63.1%, respectively. These results demonstrate that the proposed framework improves the spatial consistency of the MGT array and provides a practical calibration solution for large-scale MGT array systems. Full article