Search Results (3,238)

Continuum robots offer inherent compliance and dexterity for operation in confined and unstructured environments; however, achieving hybrid multi-segment functionality typically requires application-specific redesign and tightly coupled architectures. To address this limitation, this study proposes a reconfigurable hybrid continuum robot architecture based around a multi-lumen central integration backbone that supports multiple actuation modalities and robot configurations. The proposed design combines external tendon-driven disk modules for proximal actuation with a pneumatically actuated distal tip, while internal lumens allow routing of pneumatic lines and the insertion of optional stiffening elements without structural interference. The reconfigurability of the architecture is demonstrated through two configurations: Concept-1, a two-segment hybrid system, and Concept-2, a miniaturized three-segment configuration achieved by reducing the disk diameter and extending tendon actuation to the backbone. Experimental evaluations are conducted to characterize segment-wise actuation, coupled deformation behavior, and workspace capabilities, hysteresis response, tip contact force, and phantom-based target reachability. Results show that the integration of tendon-driven and pneumatic actuation significantly expands and reorients the reachable workspace. Additional functional tests showed repeatable loading–unloading behaviour of the tendon-driven segment, a maximum pneumatic tip contact force of approximately 0.45 N, and successful access to five representative targets within a stomach-like phantom using Concept-2. A kinematic model based on a constant-curvature formulation is validated against experimental data, yielding root-mean-square errors (RMSE) of 5.44 mm and 6.12 mm for Concept-1 and Concept-2, respectively. These results demonstrate consistent model accuracy across different configurations and scales. Overall, the proposed architecture enables modular, scalable, and reconfigurable hybrid continuum robots, providing a flexible framework for applications ranging from large-scale manipulation to gastroscopy-inspired minimally invasive procedures. Full article

Volcanic super-eruptions can perturb atmospheric composition and climate-relevant radiative properties in ways that are not captured by simple scaling from Pinatubo-like events. This study presents a reduced-order regime theory for the coupled evolution of stratospheric sulfur, sulfate aerosol burden, reactive halogens, ozone loss, stratospheric thermal adjustment, and aerosol residence time. The analysis is intended as an interpretive tool for organizing sulfur-rich volcanic scenarios, comparing literature-based benchmark classes, and designing chemistry–climate model experiments, rather than as an event-specific calibration or a substitute for three-dimensional models. Four control parameters structure the response: sulfur loading relative to microphysical saturation, effective halogen strength, ash-uptake efficiency, and dynamical lifetime sensitivity, with hemispheric asymmetry treated diagnostically. An external consistency check against published Pinatubo-like, idealized 10–40 teragrams of sulfur (Tg S), Toba-like, and Los Chocoyos-like responses is used to evaluate whether the reduced theory reproduces the expected rank ordering of aerosol saturation, forcing-efficiency decline, ozone-loss amplification, ash-driven sulfur suppression, and residence-time sensitivity. This comparison does not assign pointwise error margins against three-dimensional model output; it evaluates regime membership, sign of response, rank ordering, and broad magnitude behavior. The main conclusion is that volcanic super-eruption impacts are governed by interacting regime transitions rather than by sulfur mass alone. Microphysical saturation can limit forcing efficiency, halogens can shift the system toward chemically amplified ozone depletion, ash uptake can reduce the effective sulfur burden during the early phase, and dynamical state can control persistence and hemispheric expression. By separating these mechanisms, the study provides a compact basis for interpreting large volcanic perturbations to atmospheric chemistry and for designing targeted model experiments on extreme eruption scenarios. Full article

The adsorption of aromatic hydrocarbons from liquid paraffin is essential because of their harmful nature, long-lasting presence, and detrimental effects on the quality of the product. In this study, we investigated the adsorption of naphthalene from liquid paraffin by using a nanoclay-based adsorbent prepared from boron enrichment process waste. The characterization of the prepared adsorbent was carried out by using X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), X-ray Photoelectron Spectroscopy (XPS) and N₂ adsorption–desorption techniques, which confirmed the development of a layered nanostructure containing boron that possesses a porous and high-surface-area format appropriate for the adsorption. The hydrothermal treatment significantly increased the BET surface area from 35.42 to 112.15 m²/g, indicating the successful formation of a porous nanostructure. The kinetic and isotherm parameters of the adsorption process were calculated from experimental data. The adsorption of naphthalene followed pseudo-second-order kinetics and the isotherm fit well to the Langmuir model. Adsorption experiments revealed that the optimum adsorption performance was achieved at pH 4.0, and equilibrium was reached within 90 min. The adsorption kinetics were best described by the pseudo-second-order model (R² > 0.99), while the equilibrium data showed excellent agreement with the Langmuir isotherm model (R² = 0.995), suggesting monolayer adsorption. The maximum adsorption capacity of BNC was determined as 365.20 mg/g, which was more than twice that of the raw BEW (247.59 mg/g). Thermodynamic analysis indicated that the adsorption process was spontaneous at lower temperatures and exothermic, with a ΔH° value of −15.42 kJ/mol for BNC. The results suggest that the adsorption occurs through a multi-step process, beginning with external film diffusion, followed by pore diffusion and surface interaction. Based on the kinetic, isotherm, and spectroscopic data, a supramolecular adsorption mechanism is suggested, which encompasses π-π interactions, van der Waals forces, and surface complexation between naphthalene and the nanoclay structure. These results indicate that boron enrichment process waste-derived nanoclay is a sustainable, economical, and efficient adsorbent for removing naphthalene from liquid paraffin. Full article

Addressing the urgent demand for high-precision pressure measurement in real-time barometric monitoring, aerospace, and industrial control, this paper presents a high-accuracy MEMS resonant pressure sensor based on electrostatic excitation and piezoresistive detection. The sensor incorporates a symmetric double-ended fixed-finger comb-drive resonator structure, driven into stable vibration at its natural frequency by an alternating electrostatic force. Piezoresistors integrated at the root of the resonant beams transduce the mechanical vibration into a frequency output, enabling precise external pressure measurement. Experimental results show that the developed sensor achieves an accuracy of 0.009% FS over a pressure range of 0–350 kPa across an operating temperature span from −30 °C to 50 °C, with a room-temperature repeatability error below 0.008% FS, demonstrating excellent measurement stability. Building on this performance, a real-time atmospheric pressure monitoring experiment was conducted, yielding a mean absolute percentage error of less than 0.05%, highlighting the sensor’s potential for engineering practicality. This work provides an effective technique for a high-precision, high-stability resonant pressure sensor, with clear potential for deployment in real-time barometric monitoring, aerospace, and industrial control applications. Full article

Background/Objectives: Standard mechanical compression applied during screening mammography is a primary barrier that reduces patient compliance. Current guidelines attempt to standardize compression based solely on the one-dimensional “breast thickness” measured by the device. This study aimed to investigate the effects of three-axis anatomical breast dimensions, applied compression force, menstrual cycle phases, and BI-RADS breast density patterns on pain scores during mammography within a comprehensive biomechanical model. Methods: This retrospective cohort study included 443 female patients who underwent routine screening or diagnostic mammography. Patients with a history of breast implants, lactation, or prior breast surgery that could alter tissue biomechanics were excluded. Maximum pain scores (1–10 on a Visual Analog Scale [VAS]) were recorded. Transverse, anteroposterior, and superoinferior breast biometric measurements for each patient were calculated using advanced radiological workstations. Data were analyzed using One-Way ANOVA and Multiple Linear Regression (OLS) models. Results: The mean age of the participants was 49.7 ± 9.4 years, the mean applied compression force was 62.4 ± 10.3 N, and the mean pain score was 2.03 ± 2.12 (range: 1–10). The multiple linear regression analysis was statistically significant overall (F = 2.516, p = 0.015). Having a BI-RADS Type D (extremely dense) breast pattern was identified as the strongest independent factor associated with an increased pain score (p = 0.082, coefficient = 1.219). Age showed a trend toward a negative effect on pain (p = 0.072), while compression force showed a trend toward a positive effect (p = 0.067). Conversely, breast thickness (p = 0.231) and the three-dimensional mean breast size index (p = 0.568) demonstrated no independent predictive power. The menstrual cycle phase did not reach independent significance in the multivariate regression model (p = 0.117); however, non-parametric univariate analysis revealed a significant difference in pain across hormonal groups (Kruskal–Wallis H = 10.04, p = 0.039), with actively menstruating and luteal-phase women reporting higher pain than menopausal women. Conclusions: The pain experienced during mammography depends on the internal fibroglandular architecture (elasticity and stiffness) of the tissue rather than its external volumetric dimensions. Notably, neither device-measured breast thickness nor manually calculated three-dimensional breast dimensions independently predicted pain, challenging the widespread assumption that breast size drives mammographic discomfort. “One-size-fits-all” or thickness-based compression strategies should be abandoned in routine practice. Instead, “personalized compression” protocols that prioritize patient comfort without compromising image quality should be developed, particularly for younger patients and those with BI-RADS Type D, and to a lesser extent Type C, density patterns. Full article

Background: Upper-limb strength characteristics are considered important determinants of shooting stability in precision sports; however, the specific relationships between upper-limb strength variables and shooting performance in elite air pistol athletes remain insufficiently understood. Therefore, this study aimed to investigate the associations between upper-limb-specific strength characteristics and shooting performance in elite air pistol shooters. Methods: A prospective observational cohort study was conducted using a purposive total population sample from an elite training camp. Isometric peak force and rate of force development of nine upper-limb muscle actions, including handgrip, elbow flexion and extension, and shoulder joint movements, were assessed using a Vald Dynamo handheld dynamometer. Official scores from an international selection competition were used as indicators of shooting performance. Ridge regression analysis was applied to examine the relationships between strength variables and shooting performance while addressing multicollinearity among predictors. Results: Twenty-four elite air pistol athletes at national master level or above were recruited. Ridge regression revealed distinct coefficient patterns between upper-limb task-specific strength characteristics and total shooting score. After within-sex standardization of strength predictors, larger positive ridge coefficients were observed for handgrip RFD, elbow flexion peak force, shoulder external rotation RFD, elbow extension peak force, and selected shoulder variables, whereas negative coefficients were observed for shoulder internal rotation RFD, handgrip peak force, shoulder extension RFD, elbow extension RFD, and selected shoulder variables. These findings suggest that shooting performance is associated with the balance and coordination of task-specific upper-limb strength characteristics rather than maximal strength alone. Conclusions: These findings suggest that coordinated upper-limb task-specific strength balance is associated with shooting performance in elite air pistol athletes. These findings may help inform individualized conditioning and monitoring strategies; however, longitudinal intervention studies are needed to determine whether modifying upper-limb strength balance can improve shooting outcomes. Full article

The conventional robotic position control is gradually being replaced by force control, which is commonly used in humanoid robot applications that require force interaction with the environment, force transmission, or contact. A high-back-drive-efficiency actuator with a high-torque-density permanent magnet motor connecting the low-ratio planetary reducer is widely applied in interactive robotic systems without a torque/force sensor. This paper proposes a high-torque-density permanent magnet motor with an external rotor structure, which can realize torque enhancement by the increased air-gap diameter and better space utilization by the internal planetary reducer, i.e., the reducer inside the stator. First, the motor topologies with different slot/pole number combinations are introduced. Then, the optimization of a slot/pole number combination is elaborated for the maximum torque and torque mass density. In addition, the influence of the slot/pole number combination on the torque characteristic and overload capability is investigated by the finite element (FE) method. The experimental results of the prototype motor are provided to verify the analysis. Full article

Intelligent manufacturing has become a new driving force for the comprehensive green transformation and development of the lithium industry, representing both an intrinsic requirement and a strategic direction for promoting high-quality development in the sector. This study examines whether intelligent manufacturing can effectively enhance the green total factor productivity of the lithium industry from the dual perspectives of internal motivation and external pressure, based on relevant data from Chinese A-share listed lithium companies between 2010 and 2023. The study finds that: (1) Intelligent manufacturing can significantly enhance the green total factor productivity of the lithium industry. (2) Heterogeneity analysis indicates that the level of regional environmental regulations and the intensity of green competition within the industry are positively correlated with the extent of improvement in the lithium industry’s green total factor productivity. (3) Mechanism analysis reveals that intelligent manufacturing influences green total factor productivity through two pathways: green technological innovation and ESG disclosure. Furthermore, the intrinsic incentive effect of green technological innovation is stronger than the extrinsic pressure driven by ESG disclosure. (4) Further analysis reveals that the “Intelligent Manufacturing Pilot Project” policy and the “Comprehensive Green Transformation of Economic and Social Development” policy provide strong support and driving force for the intelligent manufacturing and green development of the lithium industry. Full article

Graphene-reinforced aluminum-based materials perfectly combine the excellent properties of graphene and aluminum, achieving superior lightweight structural characteristics. This study focuses on 1:2 internal resonance, analyzing the amplitude–frequency and force–amplitude responses of a graphene-platelet-reinforced aluminum-based truncated conical shell under multiple external excitations. Considering three different graphene distributions, an improved Halpin–Tsai mechanical model is used to predict the effective Young’s modulus of the GPL-enhanced aluminum-based truncated conical shell. Under temperature effects, based on the Reissner–Mindlin theory and von-Karman geometric nonlinear strain–displacement relationships, Hamilton’s principle and the Galerkin method are employed to derive the motion equations of the GPL-enhanced aluminum-based truncated conical shell. Through multiscale perturbation analysis, the averaged equations in polar coordinates are further derived. Based on the combined averaged equations, the amplitude–frequency and force–amplitude response curves of the system are plotted, investigating the influence of graphene distribution, graphene content, external excitation amplitude, tuning parameters, and graphene plate geometrical dimensions on its vibration characteristics. The analysis results indicate that graphene content is one of the primary factors affecting the vibration characteristics of graphene-reinforced aluminum-based truncated cones. Full article

Demand-side management is increasingly important for low-carbon transport governance. However, many studies assume relatively stable travel preferences and pay limited attention to behavioural changes under sudden external shocks. This study proposes an Event–Behaviour–Resilience framework and applies Natural Language Processing to Sina Weibo data to examine travel responses to extreme heat and refined oil price adjustments. The results show asymmetric response patterns. Oil price increases were associated with cost-based low-carbon substitution, with new-energy vehicle intentions accounting for 64.4% of the share. In contrast, extreme heat was associated with both trip reduction and motorised travel. Travel reduction reached 52.4%, while ride-hailing or taxi responses accounted for 24.6%. A quadratic fitting analysis identified 38.0–39.0 °C as an observed transition interval, within which high-carbon motorised willingness began to exceed low-carbon slow mobility willingness. Group-level analysis showed unequal behavioural flexibility. While 80.0% of the general population reduced travel under extreme heat, the forced mobility group showed limited travel reduction and maintained a high level of low-carbon willingness at 86.87%. XGBoost-SHAP results indicated that temperature, emotional valence, and behavioural constraints contributed to low-carbon mobility intention. These findings suggest that behavioural responses can help identify spatial interventions for low-carbon transport, especially in relation to heat exposure, mobility flexibility, and access to adaptive travel options. Full article

Rockburst is one of the major geological hazards in the construction of deep-buried and high-geotemperature tunnels. Using triaxial compression tests and acoustic emission (AE) techniques, this paper conducts a preliminary exploratory investigation on the deformation and failure characteristics, mechanical parameters, acoustic emission responses and energy evolution laws of typical rockburst-prone rocks under confining pressures of 10–30 MPa and temperatures of 100–250 °C. The results show that within the research scope, sandstone exhibits brittle characteristics including compaction, linear elasticity, crack initiation and propagation, stable crack propagation stage, accelerated crack propagation stage, and stress drop stage. Within a certain range, peak strength and damage strength increase with the rise in confining pressure and temperature. The elastic modulus increases with rising confining pressure. The damage point may be the critical point of energy conversion and acoustic emission activity. After damage, the work done by external forces is mainly converted into dissipated energy. With the intensification of surrounding rock damage, the ratio of elastic strain energy to total energy gradually decreases, while the ratio of dissipated energy to total energy gradually increases. Acoustic emission activity increases significantly at the damage point and reaches its peak at the peak strength. The cumulative acoustic emission ring count and cumulative energy increase slowly before the peak and grow rapidly after the peak. Under thermo-mechanical action, new cracks in sandstone preferentially initiate along grain boundaries, and the inconsistent deformation between grains will promote the formation of transgranular cracks. The connection, convergence and final penetration of cracks lead to sample failure. The elevation of temperature and confining pressure can enhance the bearing capacity of sandstone, indicating that a high-temperature and high-stress environment may be conducive to the occurrence of rockbursts. The research results provide scientific support for an in-depth understanding of the mechanical behavior and instability risk of rockburst in deep-buried and high-geotemperature tunnels, and can provide a theoretical basis for rockburst prevention and control of high-geotemperature tunnels of the CZ Railway. Full article

Robust quadruped locomotion in real-world environments remains challenging because external disturbances, sensor noise, and model uncertainties are coupled with intermittent foot–ground contact. Reinforcement learning has shown strong capability in generating agile locomotion, but many existing methods handle unobserved disturbances through implicit latent representations or domain randomization. This paper presents a disturbance-aware locomotion framework that integrates state and disturbance estimation with learning-based control. The core component is a deep generalized-momentum-based Kalman filter, which combines generalized momentum disturbance modeling with adaptive covariance inference to estimate the base velocity and external disturbance force. These physically meaningful estimates are incorporated into the policy observation space, reducing the gap between privileged simulation states and deployable onboard observations. The framework was evaluated in a simulation and on a quadruped robot platform under disturbance and outdoor locomotion scenarios. Compared with the baseline and ablated variants, the proposed method reduced estimation and tracking errors, limited impact-induced torque peaks, and improved locomotion success rates under the evaluated conditions. The results suggest that explicit disturbance estimation can complement a latent adaptation for quadruped locomotion under impact-rich conditions. Full article

This paper examines changes in the macroeconomic indicators of the member countries of the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) following their accession to the agreement. This study aims to identify shifts in the structural comparability of national economies and to assess the processes of macroeconomic convergence in the context of sustainable development. To achieve this objective, reference pools of CPTPP member countries are constructed, and their digital profiles are developed based on key macroeconomic indicators and grouped into three blocks: (1) indicators of economic growth and the state of the real sector, including GDP (constant 2015 US$), GDP growth, annual %, gross capital formation, % of GDP, unemployment, total % of total labor force, and national estimate; (2) indicators of foreign economic activity and trade openness, including exports of goods and services, % of GDP, imports of goods and services, % of GDP, external balance on goods and services (% of GDP), foreign direct investment, net inflows, % of GDP, and trade, and % of GDP; (3) indicators of financial and macroeconomic stability including inflation, consumer prices, annual %, central government debt, % of GDP, and gross savings, and % of GDP. Based on the digital profiles, similarities/differences in the economies were examined by applying linear discriminant analysis (LDA). The empirical framework covers two periods: (1) 2013–2017 (pre-accession) years and (2) 2019–2023 (post-accession) years. The results indicate that the economies of member countries in 2013–2017 exhibited a high degree of heterogeneity. In contrast, the 2019–2023 period demonstrates a tendency toward partial convergence of macroeconomic parameters, as evidenced by a reduction in distances between country profiles in the discriminant space. While interpreting the results, it is acknowledged that the 2019–2023 period coincided with the effects of the global crisis caused by the COVID-19 pandemic, which significantly impacted international trade dynamics. For most countries, this period was characterized by a decline in several macroeconomic indicators and investment activity, an increase in debt burdens, and enhanced heterogeneity in economic dynamics, which was taken into account when interpreting macroeconomic convergence processes within the CPTPP. The scientific novelty of the study lies in its application of an approach based on the analysis of the structural similarity of the macroeconomic profiles of CPTPP countries, which complements traditional assessments of the effects of economic and trade integration. The practical significance of the findings is associated with their potential use in evaluating the prospects for CPTPP expansion and in modeling alternative scenarios of participation and sustainable development within international trade agreements under conditions of global economic transformation. Full article

Rotor imbalance and abnormal vibration are classical operating conditions in rotating machinery and can often be identified by conventional vibration analysis. However, the development of low-power, self-powered, and distributed sensing nodes remains important for long-term condition monitoring, particularly in scenarios where external power supply, wiring, and maintenance are constrained. Existing vibration sensors, including piezoelectric and capacitive types, are constrained by power consumption and degraded performance under low-frequency and weak excitation. To address this issue, a magnetically repulsive cushion triboelectric nanogenerator (MRCT) is proposed to enable self-powered vibration sensing. The magnetic-repulsion cushion allows the upper friction layer to undergo stable contact–separation motion under a non-contact restoring force, while the microstructured strip electrode array (MSEA) enhances the triboelectric output and signal stability. A hybrid convolutional neural network–gated recurrent unit (CNN-GRU) deep-learning model is employed to extract time-domain and frequency-domain features from the collected signals, enabling real-time identification of rotor vibration amplitude, frequency, and imbalance weight. Experimental results show that the MRCT provides stable output, a high signal-to-noise ratio, and an identification accuracy above 98% for predefined rotor imbalance-weight states under laboratory conditions. In addition, a shaft-misalignment-related abnormal vibration condition was examined on the motor platform. The corresponding time-domain and frequency-domain analyses show that the MRCT voltage signal exhibits distinguishable signal variations under normal and misalignment-related conditions, including spectral changes around the 2× rotational frequency. A laboratory-scale AIoT-oriented demonstration further verifies the feasibility of integrating MRCT signal acquisition, CNN-GRU inference, wireless transmission, and GUI-based visualization. It should be noted that the present work mainly focuses on imbalance-state recognition, while the misalignment-related experiment provides an additional sensor-response verification. Broader validation involving mechanical looseness, bearing defects, variable-speed operation, cross-machine testing, and long-term industrial conditions remains necessary. Full article

Sea anemones detect external stimuli through the deformation of their soft tentacles, which exhibit multi-directional force sensitivity. Inspired by this mechanism, we designed a capacitive three-dimensional force flexible tactile sensor composed of a hollow hemisphere and a hollow cylinder. The device was fabricated using 3D printing combined with a Layer-By-Layer assembly process. For normal forces, the sensor achieved sensitivities of approximately 0.66 N⁻¹ in the 0–1 N range and 0.15 N⁻¹ in the 2–10 N range. For tangential forces, the four symmetrically distributed electrodes exhibited opposite monotonic capacitance variation trends. The sensor exhibited a force resolution of 0.02 N, a lower detection limit of 0.04 N, a hysteresis error as low as 3.5%, and a response/recovery time of up to 50 ms under a 0–10 N load. Moreover, the device demonstrated good stability under 1000 load–unload cycles and over a temperature range from 20 °C to 100 °C. Its utility was further validated through multi-scenario applications, including game controller manipulation, gripper-based object recognition, Morse code and Huffman coding transmission, as well as multi-joint human motion detection. These results demonstrate that the proposed bioinspired sensor offers a promising solution for flexible force sensing, human–machine interaction, and wearable health monitoring. Full article