Search Results (44,399)

The scarcity of high-quality wood encouraged the development of various technological processes for joining wood. The finger joint is one of the most widespread technological processes for wood joining. This study aimed to determine the effect of steaming and heat modification of beech wood, as well as the type of adhesive, on the mechanical characteristics of finger joints. Samples made from un-modified beech, steamed-treated, and heat-treated beech wood were bonded with polyvinyl acetate (PVAC), non-structural, and structural polyurethane (PUR) adhesives. Compressive tests on wood materials were used to evaluate their mechanical performance. The finger joint samples were tested for their bending performance. Modulus of rupture, modulus of elasticity, and compressive strength were calculated. An analysis of variance (ANOVA) was conducted to evaluate the impact of wood modification type and adhesive used on the mechanical characteristics of the finger joints. According to the results of this study, it can be concluded that the steaming process does not influence changes in the mechanical characteristics of the finger joints. Heat treatment of beech and the type of adhesive used significantly influence the tested mechanical characteristics of the finger joints and beech wood. Heat-treated beech had lower values of modulus of rupture (70 MPa) and density (690 kg/m³) and higher values of compression strength (59 MPa) in relation to un-modified (780 kg/m³) and steamed-treated (800 kg/m³) beech wood. Full article

Electromagnetic shielding materials are pivotal for suppressing electromagnetic radiation and mitigating potential health risks that electronic devices may pose to humans. Beyond health protection, they also hold significant strategic value in safeguarding national information security and maintaining stability. In the research of electromagnetic shielding materials, continuous technological advancements and growing application demands have driven the emergence of various novel materials. Among these, liquid metal (LM) exhibits outstanding properties—including exceptional electrical conductivity, excellent fluidity, and superior deformability—which endow it with substantial potential for application in electromagnetic shielding. Looking ahead, with the continuous advancement in related technologies, liquid metal-based electromagnetic shielding materials are expected to provide effective solutions to key challenges such as electromagnetic pollution and interference. This contribution synthesizes the latest literature. First, it clarifies the nomenclature and classification of liquid metals, as well as the fundamental framework for electromagnetic shielding. Then, it systematically distills recent research advances based on four key design motifs. These motifs include monolithic liquid metal (LM) scaffolds, LM/conductive-filler blends, LM/magnetic particle composites, and architectured multifunctional architectures. Finally, this review identifies current bottlenecks in the field and outlines directions for future development, which aim to achieve ultra-lightweight, broadband, and intelligent LM-based electromagnetic shields. Full article

Time series clustering plays a vital role in various analytical and pattern recognition tasks by partitioning structurally similar sequences into semantically coherent groups, thereby facilitating downstream analysis. However, building high-quality clustering models remains challenging due to three key issues: (i) capturing dynamic shape variations across sequences, (ii) ensuring discriminative cluster structures, and (iii) enabling end-to-end optimization. To address these challenges, we propose KDiscShapeNet, a structure-aware clustering framework that systematically extends the classical k-Shape model. First, to enhance temporal structure modeling, we adopt Kolmogorov–Arnold Networks (KAN) as the encoder, which leverages high-order functional representations to effectively capture elastic distortions and multi-scale shape features of time series. Second, to improve intra-cluster compactness and inter-cluster separability, we incorporate a dual-loss constraint by combining Center Loss and Supervised Contrastive Loss, thus enhancing the discriminative structure of the embedding space. Third, to overcome the non-differentiability of traditional K-Shape clustering, we introduce Differentiable k-Shape, embedding the normalized cross-correlation (NCC) metric into a differentiable framework that enables joint training of the encoder and the clustering module. We evaluate KDiscShapeNet on nine benchmark datasets from the UCR Archive and the ETT suite, spanning healthcare, industrial monitoring, energy forecasting, and astronomy. On the Trace dataset, it achieves an ARI of 0.916, NMI of 0.927, and Silhouette score of 0.931; on the large-scale ETTh1 dataset, it improves ARI by 5.8% and NMI by 17.4% over the best baseline. Statistical tests confirm the significance of these improvements (p < 0.01). Overall, the results highlight the robustness and practical utility of KDiscShapeNet, offering a novel and interpretable framework for time series clustering. Full article

With an aging population, the number of joint replacement surgeries is on the rise. One of the most common implant materials is cobalt–chromium–molybdenum (CoCrMo) alloy. Hence, the surface properties of this alloy have attracted increasing attention. In this study, nanosecond and femtosecond laser processing, followed by annealing, was employed to modify the CoCrMo surface. The effects of the treatment conditions on the surface morphology, structure, composition, hardness, roughness, contact angle, wear properties, and corrosion current were studied. Femtosecond laser processing with an energy density of 1273 mJ/cm², followed by heat treatment at 160 °C for 2 h, produced laser-induced periodic surface structures (LIPSS) without altering the chemical composition of the alloy and rendered the surface superhydrophobic. In contrast, nanosecond laser treatment at higher laser energy densities promoted the formation of an oxide layer, which improved the hardness and corrosion resistance of the substrate. Overall, the CoCrMo samples processed using the femtosecond laser system exhibited superior corrosion and wear resistance, with a protection efficiency of approximately 92%. Full article

Background: Autologous osteochondral transplantation (AOT)—the transfer of hyaline cartilage with its underlying subchondral bone—is well established for focal osteochondral lesions, yet evidence for larger (>200 mm²) defects is limited. We assessed clinical and functional outcomes of AOT in patients with osteochondral knee lesions exceeding 200 mm². Methods: In this retrospective cohort study, 52 patients underwent AOT for full-thickness osteochondral defects of the femoral condyles or patellofemoral joint. All lesions were ≥200 mm² and treated with a standardized press-fit technique using one to four overlapping cylindrical grafts. Pain and knee function were evaluated preoperatively and at 3, 6, and 12 months postoperatively with the Visual Analogue Scale (VAS), Tegner–Lysholm Knee Score (TLKS), and Knee Society Score (KSS). Results: Mean defect size was 224.4 ± 84.5 mm². The VAS improved from 6.32 ± 1.1 preoperatively to 0.72 ± 0.6 at 12 months (p < 0.001). The TLKS rose from 58.6 ± 11.4 to 95.0 ± 6.8 and the KSS from 63.8 ± 12.2 to 97.4 ± 4.9 during the same period (both p < 0.001). Most gains occurred within the first 3–6 months and were sustained at 12 months. No major surgical complications were observed, and outcomes were unaffected by age, sex, or graft number/size. Conclusions: AOT is a safe, effective option for large osteochondral knee defects (>200 mm²), offering rapid, durable pain relief and excellent functional recovery while preserving native joint structures. Accurate donor site reconstruction and precise graft placement in the weight-bearing zone appear critical for optimal results. Longer-term prospective studies are needed to confirm durability and refine patient-selection criteria. Full article

Synovitis resolution is critical for joint homeostasis and prevents the progression of osteoarthritis (OA). Treatments like NSAIDs and intra-articular corticosteroids relieve symptoms by blocking pro-inflammatory mediators, but also impair the production of pro-resolving mediators, contributing to the likelihood of chronic synovitis. PPARγ signaling is an essential mechanism of synovitis resolution, which is decreased in OA tissues. To evaluate the potential of PPARγ agonists to promote pro-resolving pathways, equine macrophages cultured in autologous, normal, or inflamed synovial fluid (n = 10 horses) were treated with pioglitazone, geraniol, or both. Treatments modulated patterns of gene expression, increasing the expression of early drivers of resolution RELB and IL6, followed by increased NRF2 and PPARGC1A expression. Concentrations of TNF-α in conditioned synovial fluid significantly decreased as an early response to treatment, while IL10 concentrations also declined over time, suggesting increased tolerance to inflammatory stimuli and decreased compensatory feedback. Using an equine model of synovitis, intra-articular delivery of pioglitazone (n = 3 horses) or geraniol (n = 4 horses) was associated with decreased markers of synovium inflammation (geraniol) and enhanced cartilage proteoglycan preservation (geraniol and pioglitazone). In this small cohort of horses, no systemic or articular side effects were observed. Further studies optimizing treatment doses and regimens for intra-articular PPARγ agonism as a pro-resolving OA therapy are warranted. Full article

The contamination of water resources with heavy metals creates problems for using it as a source of drinking water. Adsorption is one of the most promising methods for heavy metal ion removal from natural and wastewater. The process of removing copper (II) from aqueous solutions using SiO₂ xerogel as an adsorbent has been studied. The xerogel was thoroughly characterized by transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and argon adsorption–desorption isotherms, revealing an amorphous structure with a high surface area (~347 m²/g) and uniform mesoporosity (2–14 nm pore size). The surface chemistry, dominated by silanol groups, was confirmed by XPS analysis. The adsorption process is influenced by electrostatic interactions between the positively charged Cu(II) ions and the negatively charged surface groups, with the optimal performance near neutral pH. Batch adsorption experiments demonstrated that the silica xerogel effectively removes Cu(II) ions from aqueous solutions, with removal efficiency exceeding 99% at pH values above 4.0. The maximum adsorption capacity of copper (II) ions on SiO₂ xerogel is 67.5 mg/L. Full article

This study investigates the impact of assimilating FY-3D Microwave Radiation Imager (MWRI) radiance data into the Weather Research and Forecasting (WRF) model, utilizing a 3D-Var data assimilation system, on the forecast accuracy of Typhoon Muifa (2022). The research focuses on the selection of data from different channels, land/ocean coverage, and orbits of the MWRI, along with the synergistic assimilation strategy with MWHS-2 data. Ten assimilation experiments were conducted, starting from 0600 UTC on 14 September 2022, covering a 42 h forecast period. The results show that after assimilating the microwave radiometer data, the brightness temperature deviation in the ocean area was significantly reduced compared to the simulation without data assimilation. This led to an improvement in the accuracy of typhoon track and intensity predictions, particularly for predictions beyond 24 h. Furthermore, the assimilation of land data and single-orbit data (particularly from the western orbit) further enhanced forecast accuracy, while the joint assimilation of MWHS-2 and MWRI data yielded additional error reductions. These findings underscore the potential of satellite data assimilation in improving typhoon forecasting and highlight the need for optimal land observation and channel selection techniques. Full article

Runners have a high probability of sports injuries due to improper landing patterns. This study aimed to investigate the effects of three different foot strike patterns on lower limb muscle activation in healthy young male university students without specialized sports training experience. Methods: Sixteen healthy male college students (age: 21 ± 1 years) participated in this study. They performed running with three different foot strike patterns: forefoot strike (FFS), midfoot strike (MFS), and rearfoot strike (RFS) at controlled speeds of 1.4–1.6 m/s. EMG signals from six lower limb muscles (vastus lateralis, vastus medialis, rectus femoris, tibialis anterior, lateral gastrocnemius, and medial gastrocnemius) during the stance phase were collected using a wireless EMG system (1000 Hz). Ensemble Empirical Mode Decomposition (EEMD) was employed to analyze the time–frequency characteristics of lower limb EMG signals and ankle joint co-activation patterns to investigate the corresponding neuromuscular control mechanisms. Statistical analyses were performed using repeated-measures ANOVA, and significance was set at p < 0.05. Results: The timing of maximum energy in lower limb muscles during the stance phase occurred earlier in RFS compared to FFS and MFS. At initial ground contact, the low-frequency component energy (below 60 Hz) of the medial gastrocnemius was significantly higher in MFS and RFS compared to FFS, while FFS exhibited significantly higher high-frequency component energy (61–200 Hz). The co-activation of ankle dorsiflexors and plantar flexors (TA/GM) was also significantly higher in MFS and RFS compared to FFS. During the 100 ms before foot contact, the low-frequency component energy (below 60 Hz) of the lateral gastrocnemius was significantly higher in MFS compared to FFS, and the degree of TA/GM co-activation was significantly higher in both MFS and RFS compared to FFS. Conclusions: The maximum frequency in lower limb muscles appeared earliest during the mid-stance phase in the rearfoot strike (RFS) pattern. Moreover, during the pre-activation and early stance phases, frequency differences were observed only in the medial gastrocnemius, with RFS showing significantly higher low-frequency power. Full article

We present the conceptual framework of the Astronomical Hub (AstroHub), a unified platform combining various optical instruments at a single observatory. Its major approach lies in arranging conditions for research groups to install telescopes and equipment and participate in joint projects. AstroHub is planned to integrate Virtual Observatory (VO) tools, FAIR data principles, and a telescope network to create a powerful and attractive ecosystem for both robust near-Earth object (NEO) monitoring and diverse deep space research. We provide an overview of the AstroHub development directions in the case study of the Assy-Turgen Observatory. Full article

Wheeled bipedal robots (WBRS) combine the terrain adaptability potential of legged robots with the motion efficiency of wheeled robots, but the terrain adaptability is affected by the control system. Aiming at the defect that the traditional modeling ignores the dynamic changes in head angle and center of mass height, this paper proposes a method of integrated dynamic modeling and hierarchical control. The posture balance optimizes the system performance index through the linear quadratic regulator (LQR) to control the in-wheel motor, and the state feedback matrix is designed to suppress the tipping caused by external interference. At the same time, the changes in head angle and center of mass height are included in the balance control variables. The center of mass height changes are fed back through the proportional differential (PD) control and virtual model control (VMC) algorithm to control the joint motor. Simulation experiments are carried out on multiple platforms to verify that the proposed method effectively improves the control robustness of the traditional wheeled bipedal robot through geometric-dynamic coupling modeling and LQR-PD hybrid control, providing a new method of complex terrain adaptive control. Full article

The construction of buildings using shipping containers (SCs) is a way to extend their useful life. They are constructed by modifying the structure, thermal, and acoustic conditioning by improving the envelope and creating openings for lighting and ventilation purposes. This study explores the architectural adaptation of SCs to sustainable residential housing, focusing on structural, thermal, and acoustic performance. The project centers on a case study in Madrid, Spain, transforming four containers into a semi-detached, multilevel dwelling. The design emphasizes modular coordination, spatial flexibility, and structural reinforcement. The retrofit process includes the integration of thermal insulation systems in the ventilated façades and sandwich roof panels to counteract steel’s high thermal conductivity, enhancing energy efficiency. The acoustic performance of the container-based dwelling was assessed through in situ measurements of façade airborne sound insulation and floor impact noisedemonstrating compliance with building code requirements by means of laminated glazing, sealed joints, and floating floors. This represents a novel contribution, given the scarcity of experimental acoustic data for residential buildings made from shipping containers. Results confirm that despite the structure’s low surface mass, appropriate design strategies can achieve the required sound insulation levels, supporting the viability of this lightweight modular construction system. Structural calculations verify the building’s load-bearing capacity post-modification. Overall, the findings support container architecture as a viable and eco-efficient alternative to conventional construction, while highlighting critical design considerations such as thermal performance, sound attenuation, and load redistribution. The results offer valuable data for designers working with container-based systems and contribute to a strategic methodology for the sustainable refurbishment of modular housing. Full article

Periprosthetic joint infection (PJI) caused by Streptococcus bovis (S. bovis) is rare but clinically significant due to its established association with colorectal neoplasia. Early recognition and interdisciplinary management are essential to ensure favorable outcomes. We report the case of a 68-year-old woman who presented with a chronic fistula and signs of active infection 20 years after uncemented total hip arthroplasty. Cultures from the wound identified S. bovis, prompting further evaluation. Imaging and laboratory tests supported a diagnosis of chronic PJI. A two-stage revision was performed, beginning with implant removal, debridement, and placement of a vancomycin/gentamicin-loaded spacer. Given the pathogen’s known link to gastrointestinal malignancy, the patient underwent colonoscopy, which revealed a tubulovillous adenoma with carcinoma in situ. Surgical resection was performed with curative intent. Six months later, the patient underwent successful reimplantation. At three-month follow-up, clinical and radiographic assessments showed favorable recovery. This case reinforces the importance of gastrointestinal screening in patients with S. bovis PJI, as early detection of associated colorectal lesions may impact treatment strategies and prognosis. Full article

Understanding neuromuscular adaptations resulting from specific training modalities is crucial for optimizing athletic performance and injury prevention. This in silico proof-of-concept study aimed to computationally model and predict neuromuscular adaptations induced by strength and plyometric training, integrating musculoskeletal simulations and machine learning techniques. A validated musculoskeletal model (OpenSim 4.4; 23 DOF, 92 musculotendon actuators) was scaled to a representative athlete (180 cm, 75 kg). Plyometric (vertical jumps, horizontal broad jumps, drop jumps) and strength exercises (back squat, deadlift, leg press) were simulated to evaluate biomechanical responses, including ground reaction forces, muscle activations, joint kinetics, and rate of force development (RFD). Predictive analyses employed artificial neural networks and random forest regression models trained on extracted biomechanical data. The results show plyometric tasks with GRF 22.1–30.2 N·kg⁻¹ and RFD 3200–3600 N·s⁻¹, 10–12% higher activation synchrony, and 7–12% lower moment variability. Strength tasks produced moments of 3.2–3.8 N·m·kg⁻¹; combined strength + plyometric training reached 3.7–4.2 N·m·kg⁻¹, 10–16% above strength only. Machine learning predictions revealed superior neuromuscular gains through combined training, especially pairing back squats with high-intensity drop jumps (50 cm). This integrated computational approach demonstrates significant practical potential, enabling precise optimization of training interventions and injury risk reduction in athletic populations. Full article

The efficient and high-quality welding for joining Invar alloy parts is imperative for the fabrication of composite material forming molds. The residual stress distributions and microstructural evolution during oscillating welding of Invar alloy remain inadequately characterized in the current literature, necessitating further comprehensive investigation. In this paper, laser oscillating welding with circle mode is carried out for 5 mm thick plates of Invar alloy. A finite element model for the laser oscillation welding process of Invar alloy has been established. The numerical simulations and experimental methodologies are synthetically carried out to investigate the influence of oscillating parameters on temperature field, residual stress field, and microstructure characteristics. Furthermore, the microstructural evolution of laser oscillating-welded Invar alloy is elucidated by correlating it with the characteristic distribution of the temperature field. Simulation results showed that the residual stress significantly decreases under the action of the oscillating laser. The increasing of the oscillation frequency and amplitude results in a more uniform distribution of the residual stress, and the stress peak shows a downward trend. It is indicated that the oscillation of the beam resulted in the formation of numerous fragmented fine crystals within the weld seam. Consequently, the tensile strength and elongation of the oscillating welded joint exhibit respective enhancements of 15.0% and 36.6% compared to the non-oscillating condition. Full article