Search Results (102)

Differential planetary roller lead screw (DPRS) serves as a quintessential actuating mechanism within the electromechanical braking (EMB) systems of vehicles, where its operational reliability is paramount to ensuring braking safety. Considering different braking intensities, how assembly errors affect the contact stress in DPRS was analyzed via the finite element method. Firstly, the braking force of the EMB system that employed DPRS was verified by the braking performance of legal provisions. Secondly, a rigid body dynamics model of DPRS was established to analyze the response time, braking clamping force, and axial contact force of DPRS under varied braking intensities. Finally, a finite element model of DPRS was constructed. The impact of assembly errors in the lead screw and rollers on the contact stress were investigated within the DPRS mechanism based on this model. The results indicate that as braking intensity increases, the deviation of the lead screw exerts a greater influence on the contact stress generated by the engagement between the lead screw and rollers compared to that between the nut and rollers. The skewness of the rollers also affects the contact stress generated by the engagement of both the lead screw with rollers and the nut with rollers. When assembly errors reach a certain threshold, the equivalent plastic strain is induced to exceed the critical value. This situation significantly impairing the normal operation of DPRS. This study provides guidance for setting the threshold of assembly errors in DPRS mechanisms. It also holds significant implications for the operational reliability of EMB systems. Full article

This paper presents a comparative study examining the effects of carbon nanotubes (CNTs) and expanded graphite (EG) on the thermal, mechanical, morphological, electrical, and piezoresistive properties of poly(ethylene-co-methacrylic acid) (EMAA) nanocomposites. To this end, different amounts of carbonaceous fillers (EG and CNTs separately) were added to the EMAA thermoplastic matrix, and the relative electrical percolation thresholds (EPTs) were determined. The effect of filler concentration on thermo-oxidative degradation and the EMAA crystallinity was investigated via thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), respectively. Dynamic mechanical analysis (DMA) demonstrated that both fillers enhance the Young’s and storage moduli, as well as the glass transition temperature, with a greater improvement for the bidimensional nanofiller, most likely due to the cumulative effect of more extensive EG-matrix interactions. In tensile tests, a very relevant difference was detected in the Gauge Factor (G.F.) and the elongation at break of the two typologies of nanocomposites. The G.F. of EMAA 10% CNT and EMAA 15% EG were found to be 0.5 ± 0.08 and 165 ± 14, respectively, while elongation at break was about 68% for EMAA 10% CNT and 8% for EMAA 15% EG. Emission Scanning Electron Microscopy (FESEM) and Tunneling Atomic Force Microscopy (TUNA) have contributed to explaining the differences between EG- and CNT-based nanocomposites from a morphological point of view, underlying the pivotal role of the filler aspect ratio and its structural features in determining different mechanical and piezoresistive performance. The comprehensive analysis of EMAA-EG and EMAA-CNT nanocomposites provides a guide for selecting the best self-sensing system for the specific application. More specifically, EMAA-CNT nanocomposites with high elongation at break and lower sensitivity to small strains are suitable for movement sensors in the soft robotic field, where high deformation has to be detected. On the other hand, the high sensitivity at a low strain of EMAA-EG systems makes them suitable for integrated sensors in more rigid composite structures, such as aeronautical and automotive components or wind turbines. Full article

In fiber Bragg grating (FBG) sensing demodulation systems, high-precision peak detection is a core requirement for demodulation algorithms. However, practical spectral signals are often susceptible to environmental noise interference, which leads to significant degradation in the accuracy of traditional demodulation methods. This study proposes a self-adaptive K-SVD (SAK-SVD) denoising algorithm based on adaptive window parameter optimization, establishing a closed-loop iterative feedback mechanism through dual iterations between dictionary learning and parameter adjustment. This approach achieves a synergistic enhancement of noise suppression and signal fidelity. First, a dictionary learning framework based on K-SVD is constructed for initial denoising, and the peak feature region is extracted by differentiating the denoised signals. By constructing statistics on the number of sign changes, an adaptive adjustment model for the window size is established. This model dynamically tunes the window parameters in dictionary learning for iterative denoising, establishing a closed-loop architecture that integrates denoising evaluation with parameter optimization. The performance of SAK-SVD is evaluated through three experimental scenarios, demonstrating that SAK-SVD overcomes the rigid parameter limitations of traditional K-SVD in FBG spectral processing, enhances denoising performance, and thereby improves wavelength demodulation accuracy. For denoising undistorted waveforms, the optimal mean absolute error (MAE) decreases to 0.300 pm, representing a 25% reduction compared to the next-best method. For distorted waveforms, the optimal MAE drops to 3.9 pm, achieving a 63.38% reduction compared to the next-best method. This study provides both theoretical and technical support for high-precision fiber-optic sensing under complex working conditions. Crucially, the SAK-SVD framework establishes a universal, adaptive denoising paradigm for fiber Bragg grating (FBG) sensing. This paradigm has direct applicability to Raman spectroscopy, industrial ultrasound-based non-destructive testing, and biomedical signal enhancement (e.g., ECG artefact removal), thereby advancing high-precision measurement capabilities across photonics and engineering domains. Full article

Introduction: Intermittent claudication, an early symptom of peripheral artery disease, can be treated by cilostazol to alleviate symptoms and improve walking distance. Our previous investigation focused on cilostazol-induced alterations in the thermodynamic properties of plasma, utilizing differential scanning calorimetry (DSC) as a potential monitoring tool. The current proof-of-concept study aimed to enhance the interpretation of DSC data through deconvolution techniques, specifically examining protein transitions within the plasma proteome during cilostazol therapy. Results: Notable differences in thermal unfolding profiles were found between cilostazol-treated patients and healthy controls. The fibrinogen-associated transition exhibited a downward shift in denaturation temperature and decreased enthalpy by the third month. The albumin-related transition shifted to higher temperatures, accompanied by lower enthalpy. Transitions associated with globulins showed changes in thermal stability, while the transferrin-related peak demonstrated increased structural rigidity in treated patients compared to controls. Discussion: These observations suggest that cilostazol induces systemic changes in the thermodynamic behavior of plasma proteins. DSC, when combined with deconvolution methods, presents a promising approach for detecting subtle, therapy-related alterations in plasma protein stability. Materials and methods: Ten patients (median age: 58.6 years) received 100 milligrams of cilostazol twice daily. Blood samples were collected at the baseline and after 2 weeks, 1 month, 2 months, and 3 months of therapy. Walking distances were also assessed. The DSC curves were retrieved from the thermal analysis investigated by deconvolution mathematical methods. Conclusions: Although the exact functional consequences remain unclear, the observed biophysical changes may reflect broader molecular adaptations involving protein–protein interactions, post-translational modifications, or acute phase response elements. Full article

With increasing demand for high-precision motion control systems, high operational speed and load capacity are imposed with piezoelectric stick-slip actuators based on compliant mechanisms, yet their performances are often constrained by the step size and move speed. In this paper, a novel piezoelectric stick-slip actuator featuring flexure beams and a trapezoidal driving foot is proposed for high dynamic performance and load requirements. The trapezoidal structure consists of a trapezoidal driving foot to differentiate the friction in the stick and slip phases, four flexure beams for the high resonant frequency due to distributed compliance and the high load capacity due to structural geometry, and a rigid rod for motion transmission. At first, the mechanism design and the working principle are described in detail. Then, its dominant performances are predicted through finite element analysis, including the step size and the first natural frequency. On this basis, the structural parameters are optimized through the genetic algorithm. As a result, the forward displacement in the stick phase can be obtained as 4.8 $\mathsf{\mu }$m through FEA simulations, where the first natural frequency can be observed as 627 Hz. Full article

The dynamic study of current and rapid movements of rigid and multibody mechanical systems, according to differential principles from dynamics, is based on advanced concepts from analytical mechanics: kinetic energy, higher-order acceleration energies, and their absolute time derivatives. In advanced dynamics, the study will extend to higher-order acceleration energies. This paper, reflecting the authors’ research, presents new and revised formulations in advanced kinematics and dynamics, with a focus on acceleration energies of the higher order. Explicit and matrix representations of the defining expressions for higher-order acceleration energies, relevant to the current and rapid movements of rigid bodies and multibody mechanical systems, are presented. These formulations include higher-order absolute time derivatives of advanced concepts, following the specific equations from analytical dynamics. Based on the authors’ findings, acceleration energies play a central, decisive role in formulating higher-order differential equations, which describe both rapid and transient motion behavior in rigid and multibody systems. Full article

This study investigates the institutional innovation pathways for integrating comprehensive transportation networks into China’s territorial spatial planning system, with a focus on resolving the conflicts between ecological conservation and infrastructure development. By proposing a ‘constraint-coupling-innovation’ framework, this research addresses the gaps in existing spatial governance mechanisms, particularly the insufficient alignment between transportation planning and the ‘three zones and three lines’ (ecological conservation, agricultural production, and urban development zones with binding redline) system. The study employs mixed-method approaches, including geospatial conflict analysis (GIS), AI-driven policy coordination tools, and case studies from the Yangtze River Economic Belt. It demonstrates that rigid ecological constraints (e.g., ecological sensitivity veto power) can reduce planning conflicts effectively, while adaptive governance models enhance land use efficiency and stakeholder collaboration. Key findings reveal a significant negative correlation (R² = 0.75) between ecological protection redline (EPR) coverage and transportation network density, underscoring the necessity for differentiated governance strategies in high-conflict regions. A comparative analysis with the EU’s Natura 2000 sites and TEN-T networks further highlights China’s unique hierarchical governance model, which integrates top-down ecological mandates with localized technological innovations, such as digital twins and polycentric decision making. This study contributes to global debates on sustainable spatial planning by offering actionable pathways for balancing infrastructure expansion with ecological resilience, while also proposing institutional reforms, such as a National Transportation Spatial Governance Index (NTSGI), to standardize ecological compliance. These insights provide both theoretical advancements in spatial institutionalism and practical tools for policymakers navigating the dual challenges of urbanization and climate resilience. Full article

In contrast to the majority of model-based terminal sliding mode control (TSMC) approaches that rely on the plant physical model and/or data-driven adaptive pointwise model, this study treats the unknown dynamic plant as a total uncertainty in a black box with enabled control inputs and attainable outputs (either measured or estimated), which accordingly proposes a model-free (MF) nonsingular terminal sliding mode control (MFTSMC) for higher-order dynamic systems to reduce the tedious modelling work and the design complexity associated with the model-based control approaches. The total model-free controllers, derived from the Lyapunov differential inequality, obviously provide conciseness and robustness in analysis/design/tuning and implementation while keeping the essence of the TSMC. Three simulated bench test examples, in which two of them have representatively numerical challenges and the other is a two-link rigid robotic manipulator with two input and two output (TITO) operational mode as a typical multi-degree interconnected nonlinear dynamics tool, are studied to demonstrate the effectiveness of the MFTSMC and employed to show the user-transparent procedure to facilitate the potential applications. The major MFTSMC performance includes (1) finite time ($2.5\pm 0.05$ s) dynamic stabilization to equilibria in dealing with total physical model uncertainty and disturbance, (2) effective dynamic tracking and small steady state error $0\pm 0.002$, (3) robustness (zero sensitivity at state output against the unknown bounded internal uncertainty and external disturbance), (4) no singularity issue in the neighborhood of TSM $\sigma =0$, (5) stable chattering with low amplitude ($\pm 0.01$) at frequency 50 mHz due to high gain used against disturbance $d(t)=100+30\sin (2\pi t)$). The simulation results are similar to those from well-known nominal model-based approaches. Full article

Background/Objectives: Hypertrophic cardiomyopathy (HCM) is a common genetic cardiac disorder marked by abnormal thickening of the left ventricular myocardium, often leading to arrhythmias and heart failure. Mutations in sarcomeric protein genes, particularly MYBPC3, which encodes cardiac myosin-binding protein C (cMyBP-C), are major contributors to HCM pathogenesis. This study aims to investigate the structural and functional effects of two HCM-associated missense mutations, p.S236G and p.E334K, located within the C0–C2 domains of cMyBP-C. Methods: Following in silico analysis, a bacterial expression system was applied, enabling the discrete C0–C2 domains of wild-type (cMyBP-C^WT) and mutant (cMyBP-C^S236G and cMyBP-C^E334K) cMyBP-C proteins to be expressed and purified as recombinant proteins. Structural and stability changes were assessed using circular dichroism (CD), differential scanning calorimetry (DSC), and chemical denaturation assays. Functional impact on actin binding was also evaluated in vitro. Results: CD analysis revealed altered secondary structure in both mutants compared to the wild-type protein. Thermal and chemical stability assays indicated increased stability in the cMyBP-C^E334K mutant, suggesting that it exhibits a more rigid conformation. This increased rigidity corresponded with a significant reduction in the actin-binding affinity relative to the wild-type protein. Conclusions: Our findings demonstrate specific detrimental effects of the p.E334K mutation and underscore the importance of understanding the structural and functional consequences of HCM-associated mutations to assist the development of targeted therapeutic strategies. Full article

Scaffolds play a crucial role in tissue engineering as regenerative templates. Fabricating scaffolds with good biocompatibility and appropriate mechanical properties remains a major challenge in this field. This study proposes a method for preparing multi-material scaffolds, enabling the 3D printing of collagen and thermoplastic elastomers at room temperature. Addressing the previous challenges such as the poor printability of pure collagen and the difficulty of maintaining structural integrity during multilayer printing, this research improved the printability of collagen by optimizing its concentration and pH value and completed the large-span printing of thermoplastic elastomer using a precise temperature-control system. The developed hybrid scaffold has an interconnected porous structure, which can support the adhesion and proliferation of fibroblasts. The scaffolds were further treated with different post-treatment methods, and it was proven that the neutralized and cross-linked collagen scaffold, which has both nano-fibers and a certain rigidity, can better support the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs). The research results show that the collagen thermoplastic elastomer hybrid scaffold has significant clinical application potential in soft tissue and hard tissue regeneration, providing a versatile solution to meet the diverse needs of tissue engineering. Full article

The plant cell wall (CW) is a physical barrier that plays a dual role in plant physiology, providing structural support for growth and development. Understanding the dynamics of CW growth is crucial for optimizing crop yields. In this study, we employed onion (Allium cepa L.) epidermis as a model system, leveraging its layered organization to investigate growth stages. Microscopic analysis revealed proportional variations in cell size in different epidermal layers, offering insights into growth dynamics and CW structural adaptations. Fourier transform infrared spectroscopy (FTIR) identified 11 distinct spectral intervals associated with CW components, highlighting structural modifications that influence wall elasticity and rigidity. Biochemical assays across developmental layers demonstrated variations in cellulose, soluble sugars, and antioxidant content, reflecting biochemical shifts during growth. The differential expression of ten cell wall enzyme (CWE) genes, analyzed via RT-qPCR, revealed significant correlations between gene expression patterns and CW composition changes across developmental layers. Notably, the gene expression levels of the pectin methylesterase and fucosidase enzymes were associated with the contents in cellulose, soluble sugar, and antioxidants. To complement these findings, machine learning models, including Support Vector Machines (SVM), k-Nearest Neighbors (kNN), and Neural Networks, were employed to integrate FTIR data, biochemical parameters, and CWE gene expression profiles. Our models achieved high accuracy in predicting growth stages. This underscores the intricate interplay among CW composition, CW enzymatic activity, and growth dynamics, providing a predictive framework with applications in enhancing crop productivity and sustainability. Full article

Dynamically modeling the flexible characteristics of large-scale jointed composite spacecraft is challenging. In this study, a dynamic modeling method for rigid–flexible composite spacecraft is proposed based on the absolute nodal coordinate formulation (ANCF). First, the spacecraft in the jointed composite is simplified as a rigid body, and the docking mechanisms between spacecraft are approximated using the fully parameterized beam model. Next, regarding the constraints between the beam and the rigid body, the beam’s absolute nodal coordinates are converted into rigid body coordinates. This allows the dynamic equations to be simplified using independent coordinates, reducing the model dimension. Finally, system damping is increased through the mean stress noise reduction method, which suppresses high-frequency components in the dynamic model and further reduces the rigidity of the dynamic equations for the composite body. This modeling method decreases the complexity of the composite body dynamics and avoids the difficulty of solving algebraic–differential equations exhibited by Lagrange multiplier methods, facilitating numerical simulations. The proposed method is applicable to both tree and mesh topologies. MATLAB simulations demonstrate that the proposed dynamic model alleviates the dimensionality disaster caused by conventional algorithms, significantly reducing computation time. The simulation results are consistent with ADAMS. The proposed model exhibits displacement errors less than 1 mm, highlighting its efficiency and accuracy. Full article

Fluorescence imaging has been widely used in fields like (pre)clinical imaging and other domains. With advancements in imaging technology and new fluorescent labels, fluorescence lifetime imaging is gradually gaining recognition. Our research department is developing the tauCAM^TM, based on the Current-Assisted Photonic Sampler, to achieve real-time fluorescence lifetime imaging in the NIR (700–900 nm) region. Incorporating fluorescence lifetime into endoscopy could further improve the differentiation of malignant and benign cells based on their distinct lifetimes. In this work, the capabilities of an endoscopic lifetime imaging system are demonstrated using a rigid endoscope involving various phantoms and an IRF-free deep learning-based method with only 6-time points. The results show that this application’s fluorescence lifetime image has better lifetime uniformity and precision with 6-time points than the conventional methods. Full article

Breast cancer is the most common cancer and the second leading cause of cancer-related death in women. In advanced stages of the disease, breast cancer can spread and metastasize to the bone, contributing to malignant progression. The roles of tissue stiffness and remodeling of the tumor microenvironment are relevant in influencing cancer progression and invasiveness, but they are still poorly understood. In this study, we aimed to investigate the effect of bone tissue stiffness on breast cancer cell behavior, using 3D cell–biomaterial systems to model the in vivo conditions. For this purpose, we developed a 3D-printable cell array, which is a tunable and reproducible platform on small scale, where each compartment could mimic the physiological cancer environment with a shape and rigidity close to bone tissue. In this system, we observed that in the highly metastatic breast cancer line MDA-MB-231, embedded in PEG–silk fibroin (PSF) hydrogel spheres in the array’s cavities, increasing stiffness promotes trans-differentiation into osteoblast-like cells and the production of breast microcalcifications. Moreover, we also tested this 3D model as a platform to evaluate the cell response to the therapy, in particular, investigating the drug sensitivity of the cancer cells to chemotherapeutics, observing a decrease in drug resistance over time in the array. Full article

Considering the two-way influence of water ecology and industrial structure, decompose and quantify the water ecological rigidity constraints into water environment constraints and water resources constraints, construct the evaluation system based on the theoretical framework of PSR, and analyze the spatio-temporal evolution characteristics of water ecological rigidity constraints of the Yangtze River Economic Belt from 2010 to 2021 by using the entropy weighting method, the method of catastrophe progression, and the kernel density estimation. Then, putting forward the types of zoning in the Yangtze River Economic Zone through K-means algorithm analysis to explore the rigid constraints of water ecology to force the path of industrial structure adjustment. The results indicate that: (1) the water ecological rigidity constraints show a decreasing trend, and the decreasing amplitude is upstream > downstream > midstream; (2) the water ecological rigidity constraints generally show the characteristic of “gradually decreasing from east to west”, and the degree of regional differences first decreases, then increases, and then decreases again; (3) it can be divided into six types, and the zoning results gradually change from the concentration in the medium-high type and high-high type to the concentration in the low-low type and medium-low type, and the rigidity constraint of water ecology is obviously improved. In light of the findings, the Yangtze River Economic Belt is divided into five types of development regions and further discusses that the industrial restructuring in different zones has different influencing effects on the regional socio-economic development, which provides suggestions for differentiated paths of water ecological protection and industrial restructuring. Full article