Search Results (6,289)

This study evaluates the post-earthquake damage of a 17-story plan-irregular reinforced concrete (RC) building damaged during the 2024 Hualien earthquake. A three-dimensional numerical model was constructed in ETABS, utilizing nonlinear component characteristics derived from the mechanics-based Seismic Evaluation of RC Building (SERCB) framework to execute nonlinear dynamic time-history analysis (NDTHA). The actual triaxial ground motion records from the 3 April 2024 earthquake were applied as the seismic input. To correlate analytical outcomes with physical seismic damage, a displacement-based ductility development index (D) was adopted to quantitatively associate simulated plastic hinge responses with field-observed damage states ranging from Slight (DS I) to Collapse (DS V). Post-earthquake reconnaissance revealed that structural damage was primarily concentrated in the perimeter RC shear walls between the 1st and 6th stories. The predicted wall damage states spanned from Moderate (DS II) to Severe (DS IV), whereas the primary beam–column frame exhibited only Slight damage (DS I). Quantitative comparison demonstrates exact damage state match rates of 63.6% (7/11) for Frame 1 and 71.4% (5/7) for Frame 2, with all remaining discrepancies bounded within a minor one-class margin. These analytical results show high consistency with field observations, confirming that NDTHA incorporating SERCB-based plastic hinge modeling can effectively reproduce the nonlinear seismic behavior and localized damage distribution of torsionally irregular RC structures. The findings extend traditional laboratory-scale component validation to full-scale building damage reconnaissance, providing robust empirical evidence for cross-validating physical seismic damage against dynamic simulation predictions. Full article

The extended Kalman filter (EKF) remains one of the most widely used tools for state estimation, tracking, forecasting, and data assimilation in nonlinear stochastic dynamical systems. This paper does not propose a replacement for the EKF or a modification of the filter itself. Instead, it investigates how the classical EKF may fail when used as a default estimation tool in a unified but practically interpretable nonlinear tracking problem. A stochastic moving-target observation model with angular and range measurements from two identical independent radar channels co-located at the origin of the coordinate system is used as the test environment. To the standard EKF scheme, we add only the technique of linear pseudomeasurements: the EKF is kept in its classical recursive form, and only the observation representation is changed, while the filtering algorithm itself remains unchanged. Within this framework, several systematic model modifications are considered: inaccurate state initialization, absence of prior information about the mean motion parameter, jump-like changes of motion parameters, and incorrect specification of observation-noise characteristics. The experiments show that EKF instability is not limited to explicit divergence. It may also appear as hidden degradation of estimation quality, coordinate-selective failure, physically counterintuitive accuracy behavior, and cases in which the filter remains formally bounded but performs worse than a simple direct estimate based on current measurements. In several experiments, unstable behavior becomes visible only when the Monte Carlo sample size is increased. The results provide a classification of qualitatively different EKF failure modes and support practical diagnostic criteria for testing EKF applicability in nonlinear observation models. Full article

Background: Biomechanical evidence concerning sport-specific physiotherapy in elite kayaking remains limited. Objective: This study aimed to evaluate joint range of motion (ROM), muscle activation, and bilateral footrest force before and after a six-week physiotherapy programme. Methods: Twenty-two elite male kayakers participated in a non-randomised prospective controlled cohort study (study group, n = 11; control group, n = 11). Three-dimensional motion analysis, surface electromyography, and footrest-force measurements were obtained during ergometer kayaking. Results: No between-group difference in ROM change was statistically significant (p ≥ 0.398). Only right pectoralis major activation showed a significant exploratory between-group difference in change (1.40%MVC, 95% CI 0.62–2.18; p = 0.002). Footrest force increased bilaterally within the study group (both p < 0.001) but not within the control group (right, p = 0.908; left, p = 0.815). Exploratory summary-statistic estimates favoured the study group for right and left force change (both p < 0.001). Mean bilateral footrest force correlated with mean bilateral trunk rotation in the pooled sample (Spearman’s ρ = 0.953, p < 0.001). Conclusions: The programme was associated with increased bilateral footrest force during simulated paddling. ROM and most EMG changes were descriptive. The non-randomised design, small sample, and exploratory analysis preclude causal conclusions; clinical and performance applications require prospective evaluation using direct outcomes. Full article

The three-dimensional (3D) documentation of the Similaun mummy (Ötzi the Iceman) and the associated Copper Age equipment and clothing presents unique challenges due to diverse material properties and strict conservation constraints. This study presents a comprehensive digital preservation workflow, primarily utilizing Structure from Motion (SfM) close-range photogrammetry (a method that reconstructs precise 3D geometry from overlapping 2D digital photographs), integrated with Image-Based Modeling (IBM) and Neural Radiance Field (NeRF) algorithms (a machine learning approach that models a complex scene as a continuous volumetric function method). To overcome the non-Lambertian properties of the mummy’s protective ice layer and wet skin (surfaces that reflect light specularly rather than diffusely, creating glares that can disorient standard reconstruction algorithms), a specialized Polarized Light Photography (PLP) strategy was implemented using custom-built hardware. This integration required advanced anatomical segmentation to resolve postural discrepancies caused by taphonomic processes. The resulting web-based application provides the scientific community with a metrically accurate digital twin, featuring interactive tools for cross-sectioning and X-ray visualization. By adopting a Free/Libre and Open-Source Software (FLOSS) ecosystem, this project establishes a sustainable, modular framework for future forensic investigations and diachronic monitoring, ensuring the long-term digital life of one of the world’s most significant archaeological finds. Full article

Needle roller bearings are characterized by rolling elements with relatively high length-to-diameter ratios and are widely used in mechanical systems with limited radial installation space. In gear transmission systems, periodic impact loads induced by gear meshing may be superimposed on steady radial loads, thereby altering the dynamic response of the bearing. However, the effects of the amplitude and frequency of periodic impact loading on the dynamic characteristics of needle roller bearings remain insufficiently understood. In this study, a needle roller bearing test rig capable of applying periodic impact loading was developed, and a multi-sensor measurement system was configured to measure outer-ring vibration, inner-ring motion, cage motion, and the friction torque of the bearing system. Dynamic tests were conducted under different amplitudes and frequencies of periodic impact loading. A reduction in bearing motion stability was observed under periodic impact loading, as evidenced by increased outer-ring vibration and enlarged cage motion in both the horizontal and vertical directions. As the loading amplitude increased, the RMS values of outer-ring acceleration, inner-ring displacement, and cage displacement increased, while an increase in the mean friction torque was also observed. The inner-ring trajectory expanded along the loading direction, and the whirling range of the cage trajectory increased. As the loading frequency increased, the RMS values of outer-ring acceleration, inner-ring displacement, and cage displacement increased, and the mean friction torque increased. In contrast, the whirling range of the cage trajectory decreased. These findings clarify the distinct effects of periodic impact-loading amplitude and frequency on bearing vibration, internal motion, and friction-torque characteristics and provide experimental support for the dynamic performance evaluation of needle roller bearings under impact conditions. Full article

Background and Objectives: This study aimed to compare the clinical, functional, and graft-related outcomes of two tibial fixation constructs used in primary hamstring autograft anterior cruciate ligament reconstruction (ACLR): tibial cortical button fixation and bioabsorbable interference screw fixation reinforced with a U-shaped staple. Materials and Methods: This retrospective two-center comparative cohort study included 58 patients with isolated anterior cruciate ligament injuries who underwent primary ACLR and had a minimum postoperative follow-up of 12 months. Patients were classified into the cortical button group (n = 26) or the U-staple group (n = 32) according to the initial graft diameter, which strictly dictated the tibial fixation construct documented in the operative report. Both the semitendinosus and gracilis tendons were used in each group. A shorter quadrupled graft construct was prepared in the cortical button group, whereas a longer doubled graft construct was used in the U-staple group. Donor-site pain measured using the visual analog scale (VAS), graft diameter, International Knee Documentation Committee (IKDC) score, Lysholm score, knee range of motion (ROM), Lachman and pivot-shift findings, and graft failure were compared between the groups. Graft failure was defined as magnetic resonance imaging (MRI) evidence of graft discontinuity or insufficiency accompanied by grade 2–3 Lachman laxity or a positive pivot-shift test. Numerical variables were analyzed using the Mann–Whitney U test, whereas categorical variables were compared using the Pearson chi-square or Fisher’s exact test, as appropriate. Results: Donor-site pain was significantly higher in the cortical button group than in the U-staple group [median VAS score: 2.5 (2.0–4.0) vs. 2.0 (0–2.0), respectively; p = 0.007]. Graft diameter was also significantly greater in the cortical button group [10.0 mm (10.0–10.0) vs. 9.0 mm (8.0–9.0); p < 0.001]. In contrast, IKDC scores were significantly higher in the U-staple group [71.0 (51.5–78.0) vs. 60.0 (55.0–62.8); p = 0.017]. No significant differences were observed in Lysholm scores (p = 0.701), knee ROM (p = 0.508), positive pivot-shift findings (11.5% vs. 6.3%; p = 0.648), clinically relevant Lachman laxity (30.8% vs. 18.8%; p = 0.287), or graft failure rates (11.5% vs. 18.8%; p = 0.495). Conclusions: No significant between-group differences were observed in Lysholm scores, knee ROM, clinical stability, or graft failure rates after hamstring autograft ACLR. The U-staple group demonstrated lower donor-site pain and higher IKDC scores, whereas the cortical button group had larger graft diameters, likely reflecting the shorter quadrupled graft configuration. Overall, neither tibial fixation construct showed a consistent advantage across all clinical outcomes. Full article

Hybrid CNN–Transformer (HCT) synthesis for automated neurodevelopmental diagnostics is an effective approach to constructing intelligent detection systems that are not merely oriented toward feature classification but primarily toward solving spatiotemporal pattern recognition problems in motor disorder assessment. In neurodevelopmental diagnostics, existing automated methods rely on fixed, single-model architectures that process spatial or temporal motion features independently, failing to adapt to the heterogeneous motor irregularities characteristic of developmental coordination disorder and degrading detection sensitivity and generalization across diverse patient populations. There is therefore a pressing need for models capable of simultaneously capturing intra-frame spatial coordination patterns and inter-frame temporal movement dependencies against interrelated diagnostic criteria including accuracy, sensitivity, and motor irregularity specificity. To address this challenge, this paper proposes HCT, a novel framework that integrates ResNet-based spatial feature extraction from optical flow maps and pose estimation skeletons with multi-head self-attention Transformer encoding for modeling long-range temporal dependencies across multi-frame motion sequences. Unlike conventional single-stream approaches, where spatial and temporal processing remain confined to independent architectures, HCT decouples spatiotemporal feature learning through a cross-modal fusion pipeline, constructing a unified discriminative architecture that captures motor coordination dependencies between motion imaging inputs and multiple diagnostic criteria simultaneously. The convolutional encoder generates diverse joint displacement features, which are consolidated through cross-modal attention fusion into a robust, unified embedding with enhanced generalization and resilience to inter-individual motor variability. Integration within neurodevelopmental assessment frameworks facilitates reliable developmental coordination disorder classification, motor irregularity prediction, and interpretable diagnostic decision support, advancing the accuracy, flexibility, and clinical validity of intelligent motor disorder diagnostic systems. Full article

Adhesive capsulitis is characterized by shoulder pain, stiffness, and limited range of motion. Although multimodal rehabilitation is commonly used, it is unclear which combination of physiotherapy interventions is optimal. The aim of this exploratory study was to compare the short-term effects of TECAR therapy combined with proprioceptive neuromuscular facilitation (PNF) with those of standard physiotherapy in women with stage II adhesive capsulitis. This was a prospective, longitudinal, non-randomized, and exploratory study in which participants were assigned either the TECAR + PNF group or the standard physiotherapy group. Both intervention groups were given treatment three times a week for four weeks. Pain intensity and upper-limb disability were measured using the Visual Analog Scale (VAS) and the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire. Shoulder flexion, abduction, internal rotation and external rotation were measured using goniometry. Within-group changes were analyzed with the Wilcoxon signed-rank test, and exploratory baseline-adjusted analyses were conducted with ANCOVA. Both groups showed statistically significant improvements in pain and disability as a result of treatment. The median reduction on the VAS was about 5.00 points in the TECAR + PNF group and 2.00 points in the standard physiotherapy group. The median DASH scores fell by about 43.25 points and 16.00 points, respectively. Exploratory ANCOVA models showed that the TECAR + PNF group had more favourable adjusted VAS and DASH scores after treatment. Nevertheless, the groups differed at baseline in abduction, internal rotation, and external rotation, and a full pre–post analysis of changes in range of motion was not available. Therefore, the mobility results cannot be regarded as providing evidence of treatment superiority. We can conclude that in this small, non-randomised pilot study, the combination of TECAR and PNF led to greater short-term reductions in pain and upper-limb disability compared with standard physiotherapy. Nevertheless, these findings are still only preliminary and hypothesis-generating, and it is essential to carry out larger, adequately powered randomised controlled trials with concealed allocation, balanced baseline characteristics, complete analyses of changes in range of motion, and longer follow-up periods in order to confirm their clinical relevance and determine their comparative effectiveness. Full article

Background: The rotator cable is thought to contribute to load transmission and preservation of shoulder function in rotator cuff tears; however, its detectability on arthroscopy and magnetic resonance imaging (MRI), agreement between these modalities, and clinical relevance remain incompletely defined. This study evaluated rotator cable visibility on arthroscopy and MRI, factors associated with arthroscopic cable visibility, and its relationship with preoperative active shoulder motion. Methods: This retrospective cross-sectional study included 128 patients who underwent shoulder arthroscopy for supraspinatus tears between January 2019 and February 2023. Arthroscopic video recordings were reviewed for rotator cable visibility. Standardized preoperative MRI review was available in 58 patients. Agreement between MRI and arthroscopic visualization was assessed using Cohen’s kappa and percentage agreement measures. Multivariable binary logistic regression was performed to identify factors independently associated with arthroscopic cable non-visibility. Results: The rotator cable was visible arthroscopically in 79 of 128 patients (61.7%) and on MRI in 38 of 58 patients (65.5%). Overall agreement between MRI and arthroscopy was 67.2% (95% CI, 53.7–79.0%), with a Cohen’s kappa of 0.315 (95% CI, 0.090–0.540; p = 0.011), indicating fair agreement. Positive and negative percent agreement were 78.8% and 52.0%, respectively. Although increasing age was associated with cable non-visibility in univariable analysis, this association did not remain statistically significant after multivariable adjustment. Higher Lafosse grade was independently associated with cable non-visibility in the overall cohort (adjusted OR, 1.43 per grade; 95% CI, 1.04–1.97; p = 0.028), whereas increasing tear size was independently associated with cable non-visibility among patients with full-thickness tears (adjusted OR, 2.78 per category; 95% CI, 1.19–6.52; p = 0.019). The unadjusted association between massive tear size and reduced MRI cable visibility did not remain significant after false discovery rate adjustment (q = 0.276). No statistically significant associations were detected between cable visibility or MRI-measured cable dimensions and preoperative active abduction or forward elevation. Conclusions: MRI and arthroscopy demonstrated fair agreement in the assessment of rotator cable visibility. After multivariable adjustment, cable non-visibility was more closely associated with tear-related characteristics than with patient age. No statistically significant associations were detected between cable characteristics and the assessed preoperative range-of-motion measures; however, smaller or moderate associations cannot be excluded, particularly within the MRI subgroup. Rotator cable visibility should primarily be interpreted as a marker of detectability and tear morphology rather than as a direct surrogate for structural integrity or shoulder function. Full article

This study proposes a multi-source perceptual information fusion method to improve the accuracy and stability of dairy cow behavior monitoring. Existing machine vision approaches are often affected by lighting conditions, occlusion, and complex cowshed environments, while single wearable inertial measurement unit (IMU) devices may confuse similar behaviors such as eating, ruminating, standing, and lying. To address these limitations, a wireless collar was developed to synchronously collect nine-axis IMU data and ultra-wideband (UWB) ranging data in real time. Combined with manual behavioral observations, a dataset covering seven behaviors—eating, ruminating, standing, lying, drinking, sleeping, and lateral trunk contact—was constructed. By integrating neck-motion features extracted from the IMU data with spatial-distance features obtained from the UWB data, an IMU–UWB dual-branch fusion model was developed to automatically classify dairy cow behaviors. The results indicate that the proposed method can effectively reduce confusion among similar behaviors and improve the recognition of behaviors with limited samples. This approach enables more comprehensive assessment of dairy cows’ daily activities and health status, providing technical support for health monitoring, early disease warning, and intelligent dairy farm management. Full article

This single-site industrial case study compares a leased diesel shunting locomotive with a battery-electric shunting locomotive used for the same class of in-plant railway tasks at the Seza Cement Plant. The evidence base comprises plant leasing and fuel records, equipment specifications, site-reported electricity indicators, operator-reported operational observations, direct CO₂ calculations, and documented occupational safety and health (OSH) functions; it is not a controlled or statistically replicated time–motion experiment. The diesel system incurred a monthly lease cost of USD 10,000 and consumed approximately 1800 L/month, equivalent to 21,600 L/year. Cross-checking the direct CO₂ calculation with 2.692 and 2.683 kg CO₂/L factors gives 58.1 and 58.0 t CO₂/year, respectively. The approximately 24-month payback is treated as a plant-reported investment indicator and evaluated through a normalized sensitivity model because disaggregated costs for locomotive purchase, charging infrastructure, battery replacement, and historical maintenance are not available in the case-study dataset. Operational evidence is reported descriptively: the 20–40% reduction in task time is an operator-reported range rather than a statistical mean; the 7–9 min value refers to the complete 10-wagon weighing maneuver; and 25 loaded wagons (approximately 1450 t) represents the maximum documented field movement rather than a manufacturer-rated capacity. A force-balance check shows that this maximum movement is feasible only if total equivalent resistance remains below approximately 5.41 N/kN, using the 77 kN catalog tractive effort as an upper bound. The battery-electric locomotive produces no local exhaust emissions at the point of use and incorporates SIL 2 remote-control functions, a deadman function, emergency-stop controls, camera support, lighting, and warning systems; these features indicate risk-control capability but do not constitute a measured accident-rate reduction. The study therefore contributes facility-scale, evidence-bounded information for low-speed, repetitive industrial shunting within a defined operating area rather than a general proof of battery-electric superiority across railway applications. Full article

This study presents the first evaluation of the degree of nonlinearity in site response at strong-motion stations in Türkiye during the 6 February 2023 Kahramanmaraş earthquake sequence (Mw 7.8 and Mw 7.5) using earthquake horizontal-to-vertical spectral ratios (eHVSRs). The analysis uses 2050 weak-motion and 175 strong-motion records from 24 AFAD stations in the Kahramanmaraş and Hatay regions, where some of the strongest ground motions and most severe damage were observed. The selected stations cover a broad range of site conditions, from soft alluvial deposits to relatively stiff sites, as characterized by Vs30. Conventional assessments of nonlinear site response generally rely on peak ground-motion measures and one-dimensional site proxies, particularly Vs30. In contrast, this study evaluates nonlinear behavior within a record-based framework that accounts for the combined influence of source characteristics, propagation path, local site conditions, and basin-related wave effects. Nonlinear site response is quantified by comparing strong-motion and weak-motion eHVSR spectra, where the weak-motion reference is derived from records with peak ground velocity (PGV) lower than 1 cm/s. A principal methodological contribution is the use of record-specific S-wave windows selected according to the event-dependent energy content of each record, rather than a uniform fixed-duration window. This energy-based procedure focuses on the dominant S-wave energy while reducing pre-event noise and late-arriving coda effects. Incorporating record-specific S-wave duration improves degree of nonlinearity (DNL) estimates, proving that nonlinear response is driven not just by peak amplitude and near-surface stiffness but also by duration-dependent cyclic deformation demand. The proposed framework provides record-based constraints for empirical ground-motion models and regional three-dimensional physics-based earthquake simulations. Full article

Accurate remaining useful life (RUL) prediction of lithium-ion batteries is critical for reliable operation of the system. The performance evolution of lithium-ion batteries shows long-range dependence and capacity regeneration. However, existing performance evolution models fail to properly consider the joint effect of long-range dependence and capacity regeneration, and consequently have a deficiency in mechanism interpretability, which may limit the prediction accuracy of RUL. To address this gap, this paper separately characterizes the degradation and regeneration processes of the discharge capacity, and proposes a novel discharge capacity evolution model incorporating fractional Brownian motion and the Poisson capacity regeneration process. For the estimation problem of the model parameters caused by the Poisson regeneration, we approximately transform the proposed model to one with independent increments according to the weak convergence theorem, and then develop a maximum likelihood estimation method. From a limit perspective and using the theory of total probability, we derive the distribution of RUL, and provide the point estimation of RUL. Finally, we utilize the data set of lithium-ion batteries produced by NASA to verify the effectiveness of the proposed method, and the mean absolute errors of the proposed method are declined by at least 24% compared to the existing methods. Full article

Skeleton-based action recognition has attracted considerable research interest because skeleton data are inherently robust to illumination changes, viewpoint variation, background clutter, and camera motion. Nevertheless, extracting informative representations from skeleton sequences remains a challenging problem, as it requires capturing both the spatial co-occurrence patterns among body joints and the fine-grained kinematic cues that distinguish different actions. In this paper, we propose a single-stream architecture that constructs an action-specific skeleton graph directly from motion and processes it with a kinematic-aware Transformer. Rather than relying on a fixed skeleton topology, a motion-guided dynamic-graph construction module infers a per-frame adjacency matrix from short-term motion cues through a differentiable edge predictor and Gumbel-Softmax sparsification, allowing the model to discover action-driven connections between distant joints that lack direct bone connectivity (e.g., coordinated hand motion during clapping). Each joint is described by kinematic node features that combine its 3D position, instantaneous velocity, and limb-angle encodings within a single descriptor, so that both motion dynamics and higher-order limb configurations are available to the spatial encoder from the outset. A graph-attention network (GAT) encodes the spatial configuration of every frame over the learned graph, and the resulting sequence of frame descriptors is processed by a Transformer encoder that models long-range temporal dependencies; a learnable classification token aggregates the sequence, and a multi-layer perceptron (MLP) produces the final action classification. The entire model is trained end-to-end from action labels alone. We conduct a comprehensive ablation study and evaluate the proposed method on the large-scale NTU RGB+D 60 and NTU RGB+D 120 benchmarks, where the results demonstrate that our approach achieves competitive performance compared to state-of-the-art architectures. Full article

Flexible pressure sensors serve as core sensing components for wearable health monitoring systems, electronic skins for soft robots, and flexible human–machine interaction devices. Benefiting from the interfacial electric double-layer polarization effect, iontronic sensing delivers far higher pressure response sensitivity than conventional parallel-plate capacitive sensors, endowing it with distinctive advantages in the detection of weak physiological signals. Nevertheless, current dense ionic thin-film dielectric layers suffer from limited deformation space under compression and poor low-pressure sensing capability. Mainstream high-precision micropillar arrays are fabricated via photolithography, 3D printing, and metal etching molds, which require costly equipment and complicated fabrication procedures, making large-area mass production unfeasible. Random frosted concave-convex microstructures feature disordered dimensions, leading to severe device hysteresis and narrow linear ranges, which fail to achieve ultrahigh sensitivity alongside a wide pressure detection range simultaneously. To address the aforementioned multiple bottlenecks, this paper proposes a low-cost resin template replication process to fabricate TPU-based ionic thin-film dielectric layers with ordered micropillar array microstructures. Combined with inkjet-printed silver conductive PI flexible electrodes, an iontronic flexible pressure sensor with a sandwich layered structure is constructed. Multi-dimensional investigations including microscopic morphology characterization, electromechanical sensing performance calibration, and human wearable application tests are systematically implemented to thoroughly elucidate the synergistic enhancement mechanism of the arrayed micropillars. Test results demonstrate that the effective pressure detection range of the sensor spans 0–1038 kPa, accommodating ultra-low pressures such as pulse signals as well as medium-to-high-pressure loads including joint bending. The sensitivity reaches 23.27 kPa⁻¹ within the low-pressure range of 0–200 kPa and remains stable at 3.52 kPa⁻¹ in the high-pressure range of 200–1038 kPa, with piecewise linear fitting correlation coefficients of 0.93 and 0.96 respectively. Both the response time and recovery time of the device are 40 ms, and the hysteresis error throughout the loading-unloading cycle is merely 2.62%. After 20,000 consecutive cyclic loading-unloading tests, the peak capacitance output only decays by 5.1%, verifying outstanding mechanical fatigue resistance and electrical stability. Validations in multi-scenario applications prove that the sensor can accurately capture human physiological and motion signals including radial artery pulses, laryngeal deformation induced by multi-syllable vocalization, and multi-angle bending of fingers and elbow joints, suitable for home-based health monitoring, quantitative rehabilitation training, flexible tactile interaction and other scenarios. The entire fabrication process eliminates high-precision micro-nano processing equipment such as photolithography systems, plasma etchers and 3D printers; only general chemical raw materials and conventional laboratory instruments are adopted. The reusable templates enable low manufacturing costs and large-area coating forming, offering a novel low-cost technical solution for the engineering implementation and industrialization of high-performance iontronic flexible pressure sensors. Full article