Search Results (3,619)

This work presents the experimental and numerical investigation of a novel acoustic metamaterial based on sustainable and biodegradable components: cork membranes and honeycomb cores made from treated aramid paper. The design exploits the principle of localized resonance induced by tensioned membranes coupled with subwavelength cavities, aiming to achieve high sound absorption at low (250–500 Hz) and mid frequencies (500–1400 Hz) with minimal thickness and environmental impact. Three configurations were analyzed, varying the number of membranes (one, two, and three) while keeping a constant core structure composed of three stacked honeycomb layers. Acoustic performance was measured using an impedance tube (Kundt’s tube), focusing on the normal-incidence sound absorption coefficient in the frequency range of 250–1400 Hz. The results demonstrate that increasing the number of membranes introduces multiple resonances and broadens the effective absorption bandwidth. Numerical simulations were performed to predict pressure field distributions. The numerical model showed good agreement with the experimental data, validating the underlying physical model of coupled mass–spring resonators. The proposed metamaterial offers a low-cost, modular, and fully recyclable solution for indoor sound control, combining acoustic performance and environmental sustainability. These findings offer promising perspectives for the application of bio-based metamaterials in architecture and eco-design. Further developments will address durability, high-frequency absorption, and integration in hybrid soundproofing systems. Full article

The integration of a real-time image processing system using multiple webcams with a variable rate spraying system mounted on the back of an unmanned tractor presents an effective solution to the labor shortage in agriculture. This research aims to design and fabricate a low-cost, variable-rate, remote-controlled sprayer specifically for use in sugarcane fields. The primary method involves the modification of a 15-horsepower tractor, which will be equipped with a remote-control system to manage both the driving and steering functions. A foldable remote-controlled spraying arm is installed at the rear of the unmanned tractor. The system operates by using a webcam mounted on the spraying arm to capture high-angle images above the sugarcane canopy. These images are recorded and processed, and the data is relayed to the spraying control system. As a result, chemicals can be sprayed on the sugarcane accurately and efficiently based on the insights gained from image processing. Tests were conducted at various nozzle heights of 0.25 m, 0.5 m, and 0.75 m. The average system efficiency was found to be 85.30% at a pressure of 1 bar, with a chemical spraying rate of 36 L per hour and a working capacity of 0.975 hectares per hour. The energy consumption recorded was 0.161 kWh, while fuel consumption was measured at 6.807 L per hour. In conclusion, the development of the remote-controlled variable rate sprayer mounted on an unmanned tractor enables immediate and precise chemical application through remote control. This results in high-precision spraying and uniform distribution, ultimately leading to cost savings, particularly by allowing for adjustments in nozzle height from a minimum of 0.25 m to a maximum of 0.75 m from the target. Full article

The safety of lithium-ion batteries during transportation is critically important. However, current standards exhibit limitations, as their environmental testing parameter thresholds fail to fully encompass actual transportation conditions. To enhance both safety and standard applicability, in this study, we focused on four representative environmental conditions: temperature, vibration, shock, and low atmospheric pressure. Field measurements were conducted across road, rail, and air transport modes using a self-developed data acquisition system based on the NearLink communication technology. The measured data were then compared with the threshold values defined in current international and national standards. The results reveal that certain measured values exceeded the upper limits prescribed by existing standards, indicating limitations in their applicability under extreme transport conditions. Based on these findings, we propose revised testing parameters that better reflect actual transport risks, including a temperature cycling range of 72 ± 2 °C (high) and −40 ± 2 °C (low), a shock acceleration limit of 50 gn, adjusted peak frequencies in the vibration PSD profile, and a minimum pressure threshold of 11.6 kPa. These results provide a scientific basis for optimising safety standards and improving the safety of lithium-ion battery transportation. Full article

Background/Objectives: Nelumbo nucifera Gaertn. (lotus) seeds have traditionally been used to treat hypertension, though their mechanisms remain unclear. This study investigated the antihypertensive effects of lotus seed extract (LSE) and its mechanisms in rats with N^ω-nitro-L-arginine methyl ester (L-NAME)-induced hypertension. Methods: Male Sprague Dawley rats received L-NAME (40 mg/kg/day) in drinking water and were treated orally with LSE (5, 10, or 100 mg/kg/day), captopril (5 mg/kg/day), or a combination of LSE and captopril (2.5 mg/kg/day each) for 5 weeks. Hemodynamic parameters and histological changes in the left ventricle and aorta were assessed. Mechanistic studies included measurements of plasma nitric oxide (NO) metabolites, malondialdehyde (MDA), superoxide dismutase (SOD) activity, angiotensin II (Ang II), angiotensin-converting enzyme (ACE) activity, and protein expression via western blot. Results: L-NAME elevated systolic blood pressure and induced cardiovascular remodeling, oxidative stress, and renin-angiotensin system activation. LSE treatment reduced blood pressure, improved antioxidant status, increased NO bioavailability, and downregulated gp91^phox and AT₁R expression. The combination of low-dose LSE and captopril produced stronger effects than LSE alone, with efficacy comparable to captopril. Conclusions: These findings suggest that LSE exerts antihypertensive effects via antioxidant activity and inhibition of the renin-angiotensin system, supporting its potential as an adjunct therapy for hypertension. Full article

To address the data acquisition limitations of traditional flow balance methods that stem from insufficient flow rate measurements, this study establishes a pipeline flow calculation model based on the pressure data and proposes a pipeline leak identification approach for product oil pipelines. Firstly, field leak tests are designed and conducted on a product oil pipeline in East China by discharging oil in a valve chamber to simulate the leak process. Subsequently, combining the Bernoulli equation with the Leapienzon formula, a calculation model is established for flow rate prediction using the pressure data monitored at the stations and valve chambers along the pipeline. By analyzing the instantaneous flow rate changes at each pipeline section and pressure drops at each station and valve chamber, a dual-parameter collaborative threshold is set based on the flow balance principle, and leaks are identified when both parameters exceed the threshold simultaneously. Finally, the proposed flow rate calculation model and leak identification method are validated with respect to the field test data. The results show that the flow rate model yields a relative error as low as 0.48%, and the leak identification method accurately captured all six leak events in the field test, indicating very good stability and accuracy, with great potential for leak identification and alarm systems for product oil pipelines in engineering applications. Full article

The high-proportion integration of renewable energy sources, represented by wind power and photovoltaics, into active distribution networks (ADNs) can effectively alleviate the pressure associated with advancing China’s dual-carbon goals. However, the high uncertainty in renewable energy output leads to increased system voltage fluctuations and localized voltage violations, posing safety challenges. Consequently, research on optimal dispatch for ADNs with a high penetration of renewable energy has become a current focal point. This paper provides a comprehensive review of research in this domain over the past decade. Initially, it analyzes the voltage impact patterns and control principles in distribution networks under varying levels of renewable energy penetration. Subsequently, it introduces optimization dispatch models for ADNs that focus on three key objectives: safety, economy, and low carbon emissions. Furthermore, addressing the challenge of solving non-convex and nonlinear models, the paper highlights model reformulation strategies such as semidefinite relaxation, second-order cone relaxation, and convex inner approximation methods, along with summarizing relevant intelligent solution algorithms. Additionally, in response to the high uncertainty of renewable energy output, it reviews stochastic optimization dispatch strategies for ADNs, encompassing single-stage, two-stage, and multi-stage approaches. Meanwhile, given the promising prospects of large-scale deep reinforcement learning models in the power sector, their applications in ADN optimization dispatch are also reviewed. Finally, the paper outlines potential future research directions for ADN optimization dispatch. Full article

Intratumoral injections of macromolecules, such as biologics and immunotherapeutics, show promise in overcoming dose-limiting side effects associated with systemic injections and improve treatment efficacy. However, the retention of injectates in the tumor microenvironment is a major underappreciated challenge. High interstitial pressures and dense tumor architectures create shear forces that rapidly expel low-viscosity solutions post-injection. Injectable hydrogels may address these concerns by providing a viscoelastic delivery vehicle that shields loaded therapies from rapid expulsion from the tumor. A chitosan–glycerol hydrogel was thus developed and characterized with the goal of improving the injection retention of loaded therapeutics. The gelation parameters and mechanical properties of the hydrogel were explored to reveal a shear-thinning gel that is injectable through a 27-gauge needle. Biocompatibility studies demonstrated that the chitosan–glycerol hydrogel was nontoxic. Retention studies revealed significant improvements in the retention of model therapeutics when formulated with the chitosan–glycerol hydrogel compared to less-viscous solutions. Finally, release studies showed that there was a sustained release of model therapeutics of various molecular sizes from the hydrogel. Overall, the chitosan–glycerol hydrogel demonstrated injectability, enhanced retention, biocompatibility, and sustained release of macromolecules, indicating its potential for future clinical use in intratumoral macromolecule delivery. Full article

As the core equipment for efficient wastewater treatment, the internal structure of microporous aeration bioreactors directly determines the mass transfer efficiency and treatment performance. Based on Computational Fluid Dynamics (CFD) technology, this study explores the optimization mechanism of a Spherical Grid-Structured on the internal flow field of the reactor through a 3D numerical simulation system, aiming to improve the aeration efficiency and resource utilization. This study used a combination of experimental and numerical simulations to compare and analyze different configurations of the Spherical Grid-Structure. The simulation results show that the optimal equilibrium of the flow field inside the reactor is achieved when the diameter of the grid sphere is 2980 mm: the average flow velocity is increased by 22%, the uniformity of the pressure distribution is improved by 25%, and the peak turbulent kinetic energy is increased by 30%. Based on the Kalman vortex street theory, the periodic vortex induced by the grid structure refines the bubble size to 50–80 microns, improves the oxygen transfer efficiency by 20%, increases the spatial distribution uniformity of bubbles by 35%, and significantly reduces the dead zone volume from 28% to 16.8%, which is a decrease of 40%. This study reveals the quantitative relationship between the structural parameters of the grid and the flow field characteristics through a pure numerical simulation, which provides a theoretical basis and quantifiable optimization scheme for the structural design of the microporous aeration bioreactor, which is of great significance in promoting the development of low-energy and high-efficiency wastewater treatment technology. Full article

Taconis oscillations represent spontaneous excitation of acoustic modes in tubes with large temperature gradients in cryogenic systems. In this study, Taconis oscillations in hydrogen and helium systems are enhanced with a porous material resulting in a standing-wave thermoacoustic engine. A theoretical model is developed using the thermoacoustic software DeltaEC, version v6.4b2.7, to predict system performance, and an experimental apparatus is constructed for engine characterization. The low-amplitude thermoacoustic model predicts the pressure amplitude, frequency, and temperature gradient required for excitation of the standing-wave system. Experimental measurements, including the onset temperature ratio, acoustic pressure amplitudes, and frequencies, are recorded for different stack materials and geometries. The findings indicate that, independent of stack, hydrogen systems excite at smaller temperature differentials than helium (because of different properties such as lower viscosity for hydrogen), and the stack geometry and material affect the onset temperature ratio. However, pressure amplitude in the excited states varies minimally. Initial measurements are also conducted in a cooling setup with an added regenerator. The configuration with stainless-steel mesh screens produces a small cryogenic refrigeration effect with a decrease in temperature of about 1 K. The reported characterization of a Taconis-based thermoacoustic engine can be useful for the development of novel thermal management systems for cryogenic storage vessels, including refrigeration and pressurization. Full article

Based on the principle of symmetry, we propose a variable step-size FxLMS algorithm with double nonlinear functions cooperative coupling (DNVSS-FxLMS), aiming to optimize the contradiction between convergence rate and steady-state error in the active pressure pulsation control system of hydraulic systems. The algorithm innovatively couples two types of nonlinear mechanisms (rational-fractional and exponential-function-based), constructing a refined error-step mapping relationship to achieve a balance between rapid convergence and low steady-state error. Simulation experiments were conducted considering the complex time-varying operating environment of a simulation-based hydraulic system. The results demonstrate that, when the system undergoes unstable random changes, the DNVSS-FxLMS algorithm converges at least twice as fast as traditional and existing variable step size algorithms, while reducing steady-state error by 2–5 dB. The proposed DNVSS-FxLMS algorithm exhibits significant advantages in convergence rate, steady-state error reduction, and tracking capability, providing a highly efficient and robust solution for real-time active control of hydraulic system pressure pulsation under complex operating conditions. Full article

Accurate micro gas flow measurement is critical for medical ventilator calibration, environmental gas monitoring, and semiconductor manufacturing. Laminar flowmeters are widely employed in micro gas flow measurement applications owing to their inherent advantages of high linearity, the absence of moving components, and a broad measurement range. Nevertheless, due to the low measurement accuracy under micro gas flow caused by nonlinear errors and a relatively complex structure, traditional laminar flow measurement devices exhibit limitations in micro gas flow measurement scenarios. This study proposes a novel micro gas flow measurement method based on a single capillary laminar flow element, which simplifies the structure and enhances applicability in the field of micro gas flow. Through structural optimization with precise control of the capillary length–diameter ratios and theoretical error correction based on computational analysis, nonlinear errors were effectively reduced while improving the measurement accuracy in the field of micro gas flow. The proposed methodology was systematically validated through computational fluid dynamics simulations (ANSYS Fluent 2021 R1) and experimental investigations using a dedicated test platform. The experimental results show that the relative error of the measurement system within the full measurement range is less than ±0.6% (1–10 cm³/min; cm³/min means cubic centimeter per minute), and its accuracy is superior to 1% of reading (1% Rd) or 1.5% of reading (1.5% Rd) of conventional laminar flowmeters. The fitting curve of the flow rate versus the pressure difference derived from the measurement results maintains an excellent linear correlation (R² > 0.99), thus confirming that this method has practical application value in the field of micro gas flow measurement. Full article

With the continuous increase in urban population, the subway is the main way to alleviate traffic congestion. However, the construction environment of subway stations is complex, and the safety risks are extremely high. Therefore, it is of great practical significance to scientifically and systematically evaluate the safety vulnerability of subway station construction. This paper takes the Chengdu subway project as an example, and establishes a metro station construction safety vulnerability evaluation index system based on the driving forces–pressures–state–impacts–responses (DPSIR) theory with 5 first-level indexes and 23 second-level indexes, and adopts the fuzzy hierarchical analysis method (FAHP) to calculate the subjective weights, and the improved Harris Hawks optimization–projection pursuit method (HHO-PPM) to determine the objective weights, combined with game theory to calculate the comprehensive weights of the indicators, and finally uses the improved cloud model of Bayesian feedback to determine the vulnerability level of subway station construction safety. The study found that the combined empowerment–improvement cloud model assessment method is reliable, and the case study verifies that the vulnerability level of the project is “very low risk”, and the investigations of safety hazards and the pressure of surrounding traffic are the key influencing factors, allowing for the proposal of more scientific and effective management strategies for the construction of subway stations. Full article

The Santurbán paramo is a sensitive high-mountain ecosystem exposed to pressures from extractive and agricultural activities, as well as increasing tourism. In response, this study presents a context-aware recommendation system designed to support sustainable tourism through the integration of deep neural networks and ontology-based semantic modeling. The proposed system delivers personalized recommendations—such as activities, accommodations, and ecological routes—by processing user preferences, geolocation data, and contextual features, including cost and popularity. The architecture combines a trained TensorFlow Lite model with a domain ontology enriched with GeoSPARQL for geospatial reasoning. All inference operations are conducted locally on Android devices, supported by SQLite for offline data storage, which ensures functionality in connectivity-restricted environments and preserves user privacy. Additionally, the system employs geofencing to trigger real-time environmental notifications when users approach ecologically sensitive zones, promoting responsible behavior and biodiversity awareness. By incorporating structured semantic knowledge with adaptive machine learning, the system enables low-latency, personalized, and conservation-oriented recommendations. This approach contributes to the sustainable management of natural reserves by aligning individual tourism experiences with ecological protection objectives, particularly in remote areas like the Santurbán paramo. Full article

Many commercial wearable sensor systems typically rely on a single continuous cardiorespiratory sensing modality, photoplethysmography (PPG), which suffers from inherent biases (i.e., differences in skin tone) and noise (e.g., motion and pressure artifacts). In this research, we present a wearable device that provides robust estimates of cardiorespiratory variables by combining three physiological signals from the upper arm: multiwavelength PPG, single-sided electrocardiography (SS-ECG), and bioimpedance plethysmography (BioZ), along with an inertial measurement unit (IMU) providing 3-axis accelerometry and gyroscope information. We evaluated the multimodal device on 16 subjects by its ability to estimate heart rate (HR) and breathing rate (BR) in the presence of various static and dynamic noise sources (e.g., skin tone and motion). We proposed a hierarchical approach that considers the subject’s skin tone and signal quality to select the optimal sensing modality for estimating HR and BR. Our results indicate that, when estimating HR, there is a trade-off between accuracy and robustness, with SS-ECG providing the highest accuracy (low mean absolute error; MAE) but low reliability (higher rates of sensor failure), and PPG/BioZ having lower accuracy but higher reliability. When estimating BR, we find that fusing estimates from multiple modalities via ensemble bagged tree regression outperforms single-modality estimates. These results indicate that multimodal approaches to cardiorespiratory monitoring can overcome the accuracy–robustness trade-off that occurs when using single-modality approaches. Full article

This work proposes a new method to refill fuel cell electric vehicle hydrogen tanks from a storage system in hydrogen refueling stations. The new method uses the storage tanks in cascade to supply hydrogen to the refueling station dispensers. This method reduces the hydrogen compressor power requirement and the energy consumption for refilling the vehicle tank; therefore, the proposed alternative design for hydrogen refueling stations is feasible and compatible with low-intensity renewable energy sources like solar photovoltaic, wind farms, or micro-hydro plants. Additionally, the cascade method supplies higher pressure to the dispenser throughout the day, thus reducing the refueling time for specific vehicle driving ranges. The simulation shows that the energy saving using the cascade method achieves 9% to 45%, depending on the vehicle attendance. The hydrogen refueling station design supports a daily vehicle attendance of 9 to 36 with a complete refueling process coverage. The carried-out simulation proves that the vehicle tank achieves the maximum attainable pressure of 700 bars with a storage system of six tanks. The data analysis shows that the daily hourly hydrogen demand follows a sinusoidal function, providing a practical tool to predict the hydrogen demand for any vehicle attendance, allowing the planners and station designers to resize the elements to fulfill the new requirements. The proposed system is also applicable to hydrogen ICE vehicles. Full article