Search Results (37,076)

Although total knee replacements have an insignificant impact on patients’ mobility and quality of life, real-time performance monitoring remains a challenge. Monitoring the load over time can improve surgery outcomes and early detection of mechanical imbalances. Triboelectric nanogenerators (TENGs) present a promising approach as a self-powered sensor for load monitoring in TKR. A TENG was fabricated with dielectric layers consisting of Kapton tape and 3D-printed thermoplastic polyurethane (TPU) matrix incorporating CNT and BTO fillers, separated by an air gap and sandwiched between two copper electrodes. The sensor performance was optimized by varying the concentrations of BTO and CNT to study their effect on the energy-harvesting behavior. The test results demonstrate that the BTO/TPU composite that has 15% BTO achieved the maximum power output of 11.15 $\mathsf{\mu }$W, corresponding to a power density of 7 $\mathrm{mW}/{\mathrm{m}}^2$, under a cyclic compressive load of 2100 N at a load resistance of 1200 M$\Omega$, which was the highest power output among all the tested samples. Under a gait load profile, the same TENG sensor generated a power density of 0.8 $\mathrm{mW}/{\mathrm{m}}^2$ at 900 M$\Omega$. By contrast, all tested CNT/TPU-based TENG produced lower output, where the maximum generated apparent power output was around 8 $\mu$W corresponding to a power density of 4.8 $\mathrm{mW}/{\mathrm{m}}^2$, confirming that using BTO fillers had a more significant impact on TENG performance compared with CNT fillers. Based on our earlier work, this power is sufficient to operate the ADC circuit. Furthermore, we investigated the durability and sensitivity of the 15% BTO/TPU samples, where it was tested under a compressive force of 1000 N for 15,000 cycles, confirming the potential of long-term use inside the TKR. The sensitivity analysis showed values of 37.4 mV/N for axial forces below 800 N and 5.0 mV/N for forces above 800 N. Moreover, dielectric characterization revealed that increasing the BTO concentration improves the dielectric constant while at the same time reducing the dielectric loss, with an optimal 15% BTO concentration exhibiting the most favorable dielectric properties. SEM images for BTO/TPU showed that the 10% and 15% BTO/TPU composites showed better morphological characteristics with lower fabrication defects compared with higher filler concentrations. Our BTO/TPU-based TENG sensor showed robust performance, long-term durability, and efficient energy conversion, supporting its potential for next-generation smart total knee replacements. Full article

With the rapid development of unmanned aerial vehicle (UAV) technology, quadrotor UAVs have demonstrated extensive application potential in various fields. However, due to parameter uncertainties and strong coupling, the flight attitude of quadrotors is prone to external disturbances, posing challenges for achieving precise control and stable flight. In this paper, we address the tracking control problem under unknown command rate variations by proposing a Modified Linear Active Disturbance Rejection Control (LADRC) strategy, aiming to enhance flight stability and anti-disturbance capability in complex environments. First, based on the attitude dynamics model of quadrotors, an LADRC technique is adopted to realize three-channel decoupling-free control. By integrating a parameter estimator, the proposed method can compensate unknown disturbances in real time, thereby improving the system’s anti-disturbance ability and dynamic response performance. Second, to further enhance system robustness, a linear extended state observer (LESO) is designed to accurately estimate the tracking error rate and total disturbances. Additionally, a Levant differentiator is introduced to replace the traditional differentiation component for optimizing the response speed of command rate. Finally, a modified LADRC controller incorporating error rate estimation is constructed. Simulation results validate that the proposed scheme maintains good tracking accuracy under high-frequency disturbances, providing an effective solution for stable UAV flight in complex scenarios. Compared with traditional control methods, the modified LADRC strategy exhibits significant advantages in tracking performance, anti-disturbance capability, and dynamic response. This research not only offers a novel perspective and solution for quadrotor control problems but also holds important implications for improving UAV performance and reliability in practical applications. Full article

The replacement of polyvinylidene fluoride (PVDF) with environmentally friendly binders offers potential advantages in the development of aqueous lithium-ion batteries (ALIBs) and flow batteries (FBs) incorporating solid charge carriers (so-called solid boosters). This study investigates the electrochemical stability of ethyl cellulose and cross-linked gluten as substitutes for PVDF in LiMn₂O₄ (LMO) cathodes for aqueous Li-ion battery electrodes and solid boosters for FBs. The millimetre-scaled solid booster beads must be easily produced on a large scale, and at the same time, their charging and discharging must be reversible over long durations under electrolyte tank conditions. The binders were tested under standardized conditions for discharge capacity and cycling stability. Our results demonstrate that ethyl cellulose and cross-linked gluten can rival the electrochemical stability of PVDF, maintaining initial discharge capacities near 100 mAh g⁻¹ at 0.2 C for LMO cathodes and exhibiting reasonable capacity retention over hundreds of cycles. This work supports the feasibility of sustainable electrode processing, provides promising directions for scalable, eco-friendly electrode fabrication methods, and highlights promising binder candidates for use in aqueous energy storage systems. Full article

In the domain of automatic parking systems, parking space detection and localization represent fundamental challenges that must be addressed. As a core research focus within the field of intelligent automatic parking, they constitute the essential prerequisite for the realization of fully autonomous parking. Accurate and effective detection of parking spaces is still the core problem that needs to be solved in automatic parking systems. In this study, building upon existing public parking space datasets, a comprehensive panoramic parking space dataset named PSEX (Parking Slot Extended) with complex environmental diversity was constructed by integrating the concept of GAN (Generative Adversarial Network)-based image style transfer. Meanwhile, an improved algorithm based on PP-Yoloe (Paddle-Paddle Yoloe) is used to detect the state (free or occupied) and angle (T-shaped or L-shaped) of the parking space in real-time. For the many and small labels of the parking space, the ResSpp in it is replaced by the ResSimSppf module, the SimSppf structure is introduced at the neck end, and Silu is replaced by Relu in the basic structure of the CBS (Conv-BN-SiLU), and finally an auxiliary detector head is added at the prediction head. Experimental results show that the proposed SimSppf_mepre-Yoloe model achieves an average improvement of 4.5% in mAP50 and 2.95% in mAP50:95 over the baseline PP-Yoloe across various parking space detection tasks. In terms of efficiency, the model maintains comparable inference latency with the baseline, reaching up to 33.7 FPS on the Jetson AGX Xavier platform under TensorRT optimization. And the improved enhancement algorithm can greatly enrich the diversity of parking space data. These results demonstrate that the proposed model achieves a better balance between detection accuracy and real-time performance, making it suitable for deployment in intelligent vehicle and robotic perception systems. Full article

Engine knock remains a critical limitation in spark-ignition engine design. Future hybrid powertrains employ downsized engines operating on Atkinson cycles, creating different knock conditions compared to modern naturally aspirated or turbocharged engines. At the same time, petroleum-based gasoline is increasingly being replaced by biofuels and electrofuels. This study evaluates knock behavior in projected hybrid engine architectures and examines the chemical composition of emerging fuel blends. The analysis shows that hybrid engines benefit from fuels with lower sensitivity, defined as the difference between the Research and Motor Octane Numbers. This is because the higher end-gas temperatures associated with the Atkinson cycle shift the value of K, which is an interpolation factor used to capture the relationship between fuel sensitivity and anti-knock performance. In conventional engines, K is negative, favoring fuels with higher sensitivity. In hybrid engines, the increased engine temperatures result in K becoming positive, favoring low-sensitivity fuels. Using low-sensitivity fuels allows hybrid engines to operate with higher geometric compression ratios and advanced thermodynamic cycles while reducing knock constraints. Biofuels and electrofuels can meet these requirements by producing paraffinic and naphthenic hydrocarbons with high octane quality and low sensitivity. These findings emphasize the need to align renewable fuel development with hybrid engine requirements to improve thermal efficiency, reduce emissions, and reduce reliance on energy-intensive refinery processes for octane enhancement. Full article

Myoglobin (Mb), a heme-containing protein, plays crucial roles in storing and transporting oxygen in muscle cells. Various Mb structures have been extensively determined using conventional cryogenic crystallography, providing valuable information for understanding the molecular mechanisms of the protein. However, this approach has limitations attributable to cryogenic temperatures and radiation damage. Serial femtosecond crystallography (SFX) using X-ray free-electron lasers is an emerging technique that enables the determination of biologically relevant room-temperature structures without causing radiation damage. In this study, we assessed the crystallization, collection, and processing of SFX diffraction data of Mb from equine skeletal muscle. Needle- and needle cluster-shaped Mb crystals were obtained using the microbatch method. Fixed-target SFX data collection was performed at the Pohang Accelerator Laboratory X-ray Free Electron Laser, yielding 1389 indexed diffraction patterns. The phase problem was solved by molecular replacement. The preliminary Mb structure determined at 2.3-Å resolution in this study exhibited subtle structural differences in the heme environment compared with previously reported Mb structures determined by SFX. These results both confirm the feasibility of myoglobin SFX experiments and establish a foundation for future time-resolved studies aiming to visualize ligand binding and oxygen transport. Full article

Accurate pedestrian detection from a robotic perspective has become increasingly critical, especially in complex environments such as crowded and high-density populations. Existing methods have low accuracy due to multi-scale pedestrians and dense occlusion in complex environments. To address the above drawbacks, a dense pedestrian detection network architecture based on YOLOv8n (DPDN-YOLOv8) was introduced for complex environments. The network aims to improve robots’ pedestrian detection in complex environments. Firstly, the C2f modules in the backbone network are replaced with C2f_ODConv modules integrating omni-dimensional dynamic convolution (ODConv) to enable the model’s multi-dimensional feature focusing on detected targets. Secondly, the up-sampling operator Content-Aware Reassembly of Features (CARAFE) is presented to replace the Up-Sample module to reduce the loss of the up-sampling information. Then, the Adaptive Spatial Feature Fusion detector head with four detector heads (ASFF-4) was introduced to enhance the system’s ability to detect small targets. Finally, to accelerate the convergence of the network, the Focaler-Shape-IoU is utilized to become the bounding box regression loss function. The experimental results show that, compared with YOLOv8n, the mAP@0.5 of DPDN-YOLOv8 increases from 80.5% to 85.6%. Although model parameters increase from $3\times {10}^6$ to $5.2\times {10}^6$, it can still meet requirements for deployment on mobile devices. Full article

The replacement of synthetic preservatives with natural alternatives is increasingly important in bakery production. This study examined the antifungal activity of thyme essential oil (TEO) against bread spoilage molds and its impact on product quality and consumer acceptance. TEO was tested at concentrations from 0 to 200 ppm against Aspergillus flavus and Penicillium expansum in bread and a model system, with mold responses modeled using the Gompertz equation. Because TEO affects the sensory qualities of bread, the kinetic parameters of mold growth were used to estimate the minimum inhibitory concentration (MIC), thereby ensuring a mold-free shelf life without significantly altering sensory properties. Bread samples were analyzed for pH, moisture, water activity, texture, specific volume, and sensory attributes (odor, flavor, texture, and acceptability). Residual thymol and carvacrol (measured using GC-MS) were also evaluated. The retention of thymol and carvacrol in baked bread was 75–80%. The tested TEO concentrations did not alter the moisture content, pH, or water activity of bread, while the specific volume was reduced and the width-to-height ratio increased as the TEO concentration increased. At concentrations below 100 ppm, TEO enhanced bread softness, while higher levels (>150 ppm) slightly increased hardness. Sensory testing showed no significant differences in color or texture (p > 0.05). At 50 ppm, TEO imparted a subtle thyme aroma and flavor, improving the sensory profile. At 100 and 150 ppm, the aroma and flavor became more pronounced and were well accepted. However, at 200 ppm, the thyme aroma and flavor decreased overall acceptance. In bread, the MIC of TEO for A. flavus ranges from 104.2 ppm (200 h delay) to 120.8 ppm (250 h), and for P. expansum, from 106.6 ppm (200 h) to 123.6 ppm (250 h). The MICs (100–125 ppm) fall within sensory acceptable scores, indicating that TEO can delay mold growth while maintaining bread quality. Moderate levels of TEO extended the mold-free shelf life of bread by providing microbial control and preserving its sensory properties. Full article

Semi-flexible pavement (SFP) relies primarily on the properties of cementitious grouting material (CGM), which plays a crucial role in providing durability and crack resistance. This paper investigates the performance of CGMs containing recycled waste glass (RWG) as a replacement to fine granite aggregate (FGA) and their effect on SFP mixtures. Two high-fluidity glass-cementitious grouts (Glcement grouts) were developed and tested at five RWG replacement levels (0%, 30%, 50%, 70%, and 100%). The results indicated that CGM with 70% RWG provided the most balanced performance, with a flowability of 11.8 s, low drying shrinkage (0.04%), and water absorption not exceeding 1.9%. The mechanical properties were significantly enhanced, achieving a high compressive strength of 121.9 MPa and a high flexural strength of 13.9 MPa. Microstructural analysis confirmed a refined interfacial transition zone with low porosity (5.36%), contributing to superior durability. Furthermore, the SFP mixture injected with Glcement exhibited high mechanical performance, attributed to improved interlocking within voids. In conclusion, replacing FGA with RWG in CGM optimizes both mechanical and durability properties, promoting sustainable and low-carbon pavement construction. Full article

The Black-winged Kite Algorithm (BKA) is a novel heuristic optimization algorithm proposed in 2024, which has demonstrated superior optimization performance on most CEC benchmark functions and several engineering problems. To further enhance its convergence accuracy and solution quality, this paper proposes a Modified Black-winged Kite Algorithm (MBKA). First, a three-phase attacking strategy is designed to replace the original BKA’s attacking mechanism, thereby enhancing population diversity and improving solution quality. Additionally, a Lévy–Cauchy migration strategy is incorporated to achieve a more effective balance between exploration and exploitation. The effectiveness of MBKA is assessed through extensive experiments on 18 classical benchmark functions, the CEC-2017 and CEC-2022 test suites, and two real-world engineering optimization problems. The results indicate that MBKA consistently outperforms the original BKA and several state-of-the-art algorithms in both convergence accuracy and convergence speed across most test cases. Full article

Building maintenance is a critical component of ensuring long-term performance, safety, and cost-efficiency in both conventional and critical infrastructures. While traditional contracting approaches have often led to inefficiencies and rigid procurement systems, recent developments in performance-based maintenance, digital technologies, and multi-objective optimization provide opportunities to enhance both operational reliability and energy performance. From a resilience perspective, the ability to sustain functionality, adapt maintenance intensity, and recover performance under resource or operational stress is essential for ensuring infrastructure continuity and resilience. This study develops and validates an optimization model for the operation and maintenance of large campus infrastructures, addressing the persistent imbalance between over-maintenance, where costs exceed optimal levels by up to 300%, and under-maintenance, which compromises performance continuity and weakens resilience over time. The model integrates maintenance efficiency indicators, building performance indices, and energy-efficiency retrofits, particularly LED-based lighting upgrades, within a multi-choice goal programming framework. Using datasets from 15 campuses comprising over 2000 buildings, the model was tested through case studies, sensitivity analyses, and simulations under varying facility life cycle expectancies. The facilities were analyzed for alternative life cycles of 25, 50, 75, and 90 years, and the design life cycle was set for 50 years. The results show that the optimized approach can reduce maintenance costs by an average of 34%, with savings ranging from 1% to 55% across campuses. Additionally, energy retrofit strategies such as LED replacement yielded significant economic and environmental benefits, with payback periods of approximately 2–2.5 years. The findings demonstrate that integrated maintenance and energy-efficiency planning can simultaneously enhance building performance, reduce costs, and support sustainability objectives, offering a practical decision-support tool for managing large-scale campus infrastructures. Full article

This study uses the case of substituting natural river sand with molybdenum tailings in concrete production in China to propose a methodological framework for evaluating the life cycle environmental impact of concrete materials. This approach addresses the mechanical performance adaptability and environmental friendliness, as well as the resource utilization of solid waste. The resource consumption, environmental impact, and economic costs are systematically analyzed using a life cycle assessment (LCA) approach, and the circular economy potential of tailings-based concrete is explored. A three-dimensional evaluation framework is constructed, encompassing raw material production, transportation, and construction stages. The environmental impacts of concrete with different molybdenum tailings replacement rates and strength grades are quantified using a willingness-to-pay (WTP) model. The results indicate that increasing the dosage of molybdenum tailings can significantly reduce environmental indicators such as global warming potential and acidification potential value. Specifically, C30 concrete with a 100% replacement rate shows an 8.5% reduction in total WTP compared to ordinary concrete, with a 2.85% reduction in energy consumption during the production stage. High-strength concrete further optimizes the environmental cost per unit strength through the “strength dilution effect,” with a 44.9% reduction in carbon footprint for 60 MPa concrete compared to 30 MPa concrete. Regional analysis reveals that the environmental contribution of the production stage dominates in short-distance transportation scenarios, while logistics optimization has a significant emission reduction effect in long-distance transportation scenarios. The study demonstrates that the proposed LCA methodology provides a scientific approach for the development of green building materials and the sustainable resource utilization of solid waste through case-informed generalization. Full article

There is a growing global trend toward reducing the consumption of natural resources and newly produced construction materials by replacing them with secondary raw materials. Concrete derived from construction and demolition waste can be recycled multiple times and is considered environmentally sustainable. This study evaluates the feasibility of reinforcing weak subsoil using crushed recycled concrete. Concrete obtained from the demolition of residential buildings was crushed under laboratory conditions to produce material with grain sizes corresponding to sands, and mixtures were subsequently prepared containing up to 30% fine fraction. The case study focuses on circular wind turbine foundations supported by symmetrically arranged columns made of four different materials, located beneath the foundation slab. The analyzed subsoil is characterized by strong stratification, low bearing capacity, and high compressibility. The calculation results indicate that the bearing capacity conditions for all foundations were met within similar ranges of the safety factor for the given loads, both for low- and high-power turbines. However, foundation deformations increased with turbine size and bending moments, and were nearly twice as large for recycled aggregates compared to recycled concrete. Numerical simulations demonstrate that recycled aggregate without fine fraction, as well as with fine fraction, and recycled concrete can provide load-bearing performance comparable to conventional concrete under low loading conditions, while offering significant environmental benefits. Full article

Much focus is being dedicated to the development of innovative technologies for producing biodegradable polymers from plant biomass. It is proposed that annual and perennial herbaceous plants, such as miscanthus, be used as promising sources of cellulose. The component composition of miscanthus allows us to consider it as a raw material for obtaining cellulose. This paper proposes methods for cooking miscanthus lignocellulose raw materials, which allow sulfate cellulose to be obtained with a high yield (up to 52%). In the process of obtaining chemical–thermomechanical pulp, the product yield is 71%. The possibility of replacing unbleached sulfate pulp with a semi-finished product from miscanthus for paper production is considered. For all types of raw materials obtained, acceptable paper-forming properties are observed. The best strength and deformation properties are obtained for sulfate cellulose. The addition of this cellulose to the composition of waste paper fluting significantly increases the sheet density, elasticity, and energy capacity without losing tensile strength. Using miscanthus raw materials along with waste paper of grade MS 5B makes it possible to make a composite product. The resulting products have optimal mechanical properties for creating the middle layer of corrugated cardboard. Miscanthus cellulose can be considered a promising raw material for enhancing waste paper fluting. Altering the system composition utilizing miscanthus and waste paper enables a broad modification of the mechanical and optical qualities of the resultant paper. The recommended concentration of miscanthus fraction in waste paper fluting is 30%. Full article

The Artificial Intelligence Forecasting System (AIFS), recently released by the European Centre for Medium-Range Weather Forecasts (ECMWF), represents a paradigm shift in global weather prediction by replacing traditional physically based methods with machine learning-based approaches. This study examines the sensitivity of the Weather Research and Forecasting (WRF) model to differentiate initial and boundary conditions, comparing the new AIFS with two well-established global models: IFS and GFS. The analysis focuses on the implications for air quality applications, particularly the influence of each global model on key meteorological variables involved in pollutant dispersion modelling. While overall forecast accuracy is comparable across models, some differences emerge in the spatial pattern of the wind field and vertical profiles of temperature and wind speed, which can lead to divergent interpretations in source attribution and dispersion pathways. Full article