Search Results (381)

Population mobility links cities, propelling the spatiotemporal spread of urban pandemics and adding complexity to disease dynamics. It also closely shapes, and is shaped by, the selection and intensity of intervention measures. Revealing the multistage spatial-temporal dynamics of cross-regional epidemic continuity under this interaction is often overlooked but critically important. This study innovatively applies a self-organizing map (SOM) neural network to classify cities into six distinct types based on population mobility characteristics: high-inflow core (HIC), low-inflow core (LIC), low-inflow sub-core (LISC), high-outflow semi-peripheral (HOSP), equilibrious semi-peripheral (ESP), and low-outflow peripheral (LOP). Building on this, we propose a novel SEIR-AHQ theoretical framework and construct an epidemiological model using network-coupled ordinary differential equations (ODEs). This model captures the dynamic interplay between inter-city population mobility and intervention measures, and quantifies how heterogeneous city types shape the evolution of epidemic transmission across the coupled mobility network. The results show that: (1) Cities with stronger population mobility face significantly higher infection risks and longer epidemic durations, characterized by “higher peaks and longer tails” in infection curves. HIC cities experience the greatest challenges, and LOP cities experience the least. (2) Both higher transmission rates and delayed intervention timings lead to exponential growth in infections, with nonlinear effects amplifying small changes disproportionately. (3) Intervention efficacy follows a “diminishing marginal returns” pattern, where the incremental benefits of increasing intervention intensity gradually decrease. This study offers a novel perspective on managing interregional epidemics, providing actionable insights for crafting tailored and effective epidemic response strategies. Full article

This study addresses structural distortions in the IMO Carbon Intensity Indicator (CII) for short-voyage training vessels and proposes corrective strategies combining denominator adjustments with controllable pitch propeller (CPP) mode optimization. Using 2024 operational data from a training ship, we computed monthly and annual CII values, identifying significant inflation when time-at-sea fractions are low due to extensive port stays. Two correction methods were evaluated: a hybrid denominator approach converting port-stay CO₂ to equivalent distance, and a Braidotti functional correction. The CPP operating maps for combination and fixed modes revealed a crossover point at approximately 12 kn (~50% engine load), where the combination mode shows superior efficiency at low speeds and the fixed mode at higher speeds. The hybrid correction effectively stabilized CII values across varying operational conditions, while the speed-band CPP optimization provided additional reductions. Results demonstrate that combining optimized CPP mode selection with hybrid CII correction achieves compliance with required standards, attaining a B rating. The integrated framework offers practical solutions for CII management in short-voyage operations, addressing regulatory fairness while improving operational efficiency for training vessels and similar ship types. Full article

This article presents aircraft propeller optimal design technology; including an algorithm and OpenVINT 5 code. To achieve greater geometric flexibility, the proposed technique implements Class-Shape Transformation (CST) parameterization combined with Bézier curves, replacing the previous fully Bézier-based system. Performance improvements in the optimization process are accomplished through deep learning models and a genetic algorithm, which substitute XFOIL and Differential Evolution-based approaches, respectively. The scientific novelty of the article lies in the application of a neural network to predict the aerodynamic characteristics of profiles in the form of contour diagrams, rather than scalar values, which execute the neural network repeatedly per ISM algorithm iteration and speed up the design time of propeller blades by 32 times as much. A propeller for an aircraft-type UAV was designed using the proposed methodology and OpenVINT 5. A comparison was made with the results to solve a similar problem using numerical mathematical models and experimental studies in a wind tunnel. Full article

Flapping-Wing Aerial Vehicles (FWAVs), which take inspiration from the flight of birds and insects, have gained increasing attention over the past decades due to advantages such as low noise, biomimicry and safety, enabled by the absence of propellers. These features make them particularly suitable for applications in natural environments and operations near humans. However, their complexity introduces significant challenges, including difficulties in take-off and landing as well as limited endurance. Perching represents a promising solution to address these limitations. By equipping these drones with a perching mechanism, they could land on branches to save energy and later exploit the altitude to resume flight without requiring human intervention. Specifically, this review focuses on perching mechanisms based on grasping. It presents designs developed for flapping-wing platforms and complements them with systems originally intended for other types of aerial robots, evaluating their applicability to FWAV applications. The purpose of this work is to provide a structured overview of the existing strategies to support the development of new, effective solutions that could enhance the use of FWAVs in real-world applications. Full article

Introduction: Perforator-based fasciocutaneous flaps are particularly suitable for soft tissue reconstruction of the lower extremities. The most commonly used flap is the microvascular Anterior Lateral Thigh Flap (ALT). Pedicled propeller-type flaps are less frequently utilized due to higher complication rates. The aim of this study was to compare postoperative perfusion patterns of these fundamentally different flaps to increase their basic understanding. Methods: A retrospective data analysis was performed (2017–2022), including patients who underwent flap reconstruction of the lower extremity either with a perforator-based pedicled Propeller flap or free tissue transfer with an ALT flap. Only patients with documented postoperative perfusion monitoring of the flap using the laser Doppler spectrophotometry system (LDSP) were included. Demographic data, comorbidities and perioperative data as well as perfusion profiles given by the LDSP were analyzed. Results: Seven patients who received a propeller flap and 18 who received a free ALT were identified. Defects were most often due to trauma (Propeller flap n = 5; 71.1%; ALT n = 7; 38.9%) and chronic wounds (Propeller flap n = 1; 14.3%; ALT n = 5; 27.8%). The most common complication was prolonged wound healing (Propeller flap n = 3; 42.9%; ALT n = 8; 44.4%). In cases with postoperative surgical complications, a distinctly delayed recovery in perfusion of propeller flaps was seen during the first 72 h after surgery. Conclusions: Propeller and ALT flaps exhibit distinct perfusion patterns, with Propeller flaps showing a congestion-prone profile (elevated rHB, delayed hyperperfusion) and ALT flaps an inflow-dependent, ischemia-driven profile (lower rHB and SO₂). Full article

Currently, the integration of deep learning technology with metasurface holographic imaging technology has propelled the development of optical imaging. Owing to the precise control of metasurfaces over the characteristics of light waves, holographic imaging technology can produce corresponding three-dimensional images after processing. Therefore, their integration enables the acquisition of high-quality images. The number of articles on metasurface design using neural network-based deep learning methods is increasing day by day; however, reviews on this topic remain scarce. This review introduces the development of neural networks and the relevant content on metasurface design using the four types of networks and the applications of deep learning-designed metasurface holographic imaging technology, thereby enhancing readers’ systematic understanding of such technologies. Full article

Evaluating green data centers is a multi-attribute decision problem. To enhance the rigor and precision of green data center assessment, this study verifies the weighting of the national green data center evaluation index system using the Analytic Hierarchy Process (AHP) with the participation of 19 domain experts from various data center sectors. The aim is to gain an in-depth understanding of the perspectives and priorities of different types of institutions regarding evaluation indicators and to investigate the underlying reasons for these perspectives and priorities. Through an analysis of expert sample distribution, this paper reveals the preferences of financial, internet, research, and design, as well as technical consulting service institutions, regarding indicators such as energy-efficient utilization, computational resource utilization, green low-carbon development, scientific layout, and intensive construction. Specifically, financial institutions tend to place a relatively lower emphasis on energy efficiency due to their focus on transaction speed and security. In contrast, internet companies prioritize efficient utilization of computational resources. Research and design institutions consider scientific layout and intensive construction more crucial, while technical consulting service institutions emphasize green and low-carbon development. Meanwhile, we identified substantial discrepancies among experts in determining the weights of specific indicators, suggesting a lack of consensus within the industry about the correlation between these indicators and green data centers. To propel the sustainable development of green data centers, future assessments should refine evaluation dimensions, consider disparities such as data center types and embrace regional differences, actively adopt novel technologies and innovative practices, and establish mechanisms for long-term monitoring and evaluation. Full article

A self-propelled multi-duct air-delivered sprayer was developed to address the challenges of dense canopies and low pesticide utilization in closed-canopy apple orchards. It featured an intelligently adjustable spray bar and formed a directional air curtain via a centrifugal fan and a duckbill air outlet to improve droplet penetration. Using CFD simulations, the air duct size and the air outlet distance were optimized, and the field orthogonal test was carried out with driving speed, nozzle pressure, and nozzle type as factors. The results showed that the optimal parameters were an air duct size of 230 × 110 mm, an air outlet distance of 350 mm, and a fan speed of 2160 r/min. Compared to liquid pump independent operation, liquid pump–fan cooperative operation significantly increased droplet deposition density (p < 0.05) and reduced the degree of dispersion. All three factors significantly influenced deposition density (p < 0.05), and nozzle type had the greatest influence on deposition density, followed by nozzle pressure, and then driving speed. Optimal performance was obtained at a 0.3 m/s driving speed, a 3 MPa nozzle pressure, and a 6502 nozzle type. Under the optimal combination of operating parameters, field verification tests demonstrated that cooperative operation achieved higher average coverage (60.54% vs. 48.30%) and average deposition density (71.34 vs. 60.54 droplets/cm²), with a more uniform coefficient of variation in droplet coverage on leaves (a range of 13.37–19.07% vs. 9.70–22.67%). These results indicate that the sprayer exhibits strong penetration and provides good uniform coverage, effectively increasing droplet deposition across different canopy heights. Full article

Ammonium perchlorate (AP), as the most commonly used oxidizer in composite solid propellants, achieving its rapid decomposition at lower temperatures, is one of the key items used to improve propellant performance. Copper-based catalysts, due to their good performance in promoting AP decomposition and improving propellant combustion characteristics, are currently one of the most widely used catalyst types. However, the catalytic performance of copper-based catalysts for the decomposition of ammonium perchlorate, including the decomposition products, changes in the kinetic process during the decomposition, and the combustion process needs further research and clarification in terms of the influencing factors and mechanisms. Based on this question, to further analyze the essence of copper-based catalysts and the decomposition mechanism of CuO-catalyzed ammonium perchlorate, as well as its relationship with particle size, this paper compared and studied the effects of two different particle size CuO catalysts (small-diameter CuO-S and large-diameter CuO-L) on the thermal decomposition and combustion performance of AP. The results indicate that the decomposition of AP catalyzed by CuO mainly includes two stages: the initial low-temperature decomposition stage accelerated by the electron transfer mechanism and the subsequent second stage accelerated by the adsorption and conversion of intermediates by the catalyst. The two stages are controlled by different properties and are related to the particle size of the catalyst. This work provides in-depth research on CuO catalysts for the thermal decomposition of AP. Full article

Ship stiffened panels, typically flat plates reinforced with various types of stiffeners, form a substantial part of a ship’s structure and are susceptible to resonance, especially in areas such as the after peak structure, engine room, and accommodation compartments. These vibrations are primarily excited by main engine and propeller forces. Conventional methods such as finite element analysis (FEA) and plate theory are widely used to estimate vibration frequencies, but they are time-consuming and computationally intensive when applied to numerous stiffened panels. This study proposes a machine learning approach using an artificial neural network (ANN) algorithm to efficiently predict the vibration frequencies of ship stiffened panels. A crude oil tanker is chosen as the case study, and FEA is conducted to generate the vibration frequency and mass data for panels across critical regions. The input layer features for the ANN include panel area, thickness, number and area of stiffeners, fluid density, number of fluid contact sides, and overall structural stiffness. The ANN model predicts two outputs: the fundamental vibration frequency and the mass of the panel structure. To evaluate the model performance, hyperparameters such as the number of hidden neurons are optimized. The results indicate that the ANN achieves accurate predictions while significantly reducing the time and resources required compared with conventional methods. This approach offers a promising tool for accelerating the local vibration analysis process in ship structural design. Full article

Heavy metals such as zinc, manganese, nickel, cobalt, copper, iron, and molybdenum are required in minute quantities to maintain optimal biological functions. However, most other heavy metals are not required for living cells; thus, their accumulation within cells and tissues poses a serious threat to human health and the environment. Phytoremediation can offer a safe, inexpensive, and ecologically sustainable technique to clean habitats contaminated with heavy metals. Several herbaceous and woody plants have been identified and utilized as potential candidates for phytoremediation, and the technique has transformed from being in the formative stage, where it was confined to laboratories and greenhouses, to becoming a widely applied technology involving field trials across the globe. However, recently, several field studies have shown promising results that can propel the large-scale implementation of this technology at industrial sites and in urban agriculture. The commercialization of this technique is possible if an interdisciplinary approach is employed to increase its efficiency. Identification of the genetic mechanisms and the cell signaling pathways involved in phytoremediation may support biotechnological intervention through OMICS and CRISPR approaches, resulting in an improvement in the efficiency of the process. This review presents a comprehensive overview of phytoremediation with a focus on the current assessment and future perspectives of the technique. It illustrates the concept of phytoremediation, the ecological and commercial benefits, and the types of phytoremediation. The candidate plants and factors that influence phytoremediation are discussed. The physiological and molecular mechanisms, along with perspectives on the future of the technique, are also illustrated. This review presents clear and updated information on this rapidly evolving technology, thus providing the public and private sectors with essential knowledge on phytoremediation mechanisms. This may assist in policy development for the management of heavy metals while accelerating the development of transgenic plants or other tools that might be more efficient in phytoremediation. Full article

Aiming at the gas injection technique for maintaining the performance of liquid-propellant rocket engines over a wide throttling range, an experimental study was conducted using the head cavity of a certain type gas generator as the object. White oil and water were selected as the substitute working liquids, while gaseous helium (GHe) and gaseous nitrogen (GN₂) were used as injected gases. Pressures at typical positions were measured, and the phase distribution at the head cavity inlet and nozzle outlets was visually captured. The effects of flow rate, gas type and liquid type were tested and compared. The results indicate that, injecting gas could significantly increase the pressure of head cavity, and improve the nozzle atomization effect at low-thrust conditions. The nozzle pressure drop increases linearly with the gas injection rate at a given liquid flow rate. Across varying liquid flow rates, a fixed amount of gas injection results in nearly constant multiplicative increases in the nozzle pressure drop. GHe is recommended as the preferred injecting gas due to its superior pressurization capability compared to GN₂. This work could provide fundamental data for understanding gas injection mechanisms and promote its mature application in the development of deep-throttling technology. Full article

The development of dynamic missions of small satellites requires the development of efficient, compact, and reliable propulsion systems (PSs). This paper investigates a propellant storage and supply system (PSSS), utilizing alternative solid-state propellants in the form of wire. To establish the background to the suggested solutions implemented in the proposed system, two types of comparative analysis were performed. The first one compared different types of propellant management system designs while the second juxtaposes a variety of propellants. It is shown that the solid-state systems for small satellite operations are advantageous, while the selection of propellants should be focused on safe operations and operational requirements. The principle of operation and structural design of the proposed wire-based solid-state propellant management system are discussed, including the assessment of its engineering realization. The strategies to mitigate the potential problems with the system’s operations such as propellant unwanted deposition and corrosive effects are suggested. An example of using the proposed system is provided, which considers a deep space dynamic mission case. The proposed PSSS architecture is dedicated to increasing the energy efficiency, resilience to environmental factors, and suitability for small satellite platforms, including that of the CubeSat format. Full article

This study explores the effectiveness of 3D Digital Image Correlation (DIC) for measuring displacement and strain of a propeller undergoing angular motion. Traditional methods, such as strain gauges, face limitations including physical interference, technical difficulties in sensor connections, and restricted measurement points, leading to inaccuracies in capturing true conditions. To overcome these challenges, this research utilizes non-contact 3D DIC technology, enabling measurement of surface displacements and deformations without interfering with the tested component. Experiments were conducted using the model aircraft propellers mounted on a custom-built test stand for partial angular motion. The 1 Mpx high-speed cameras captured strain and displacement data across the propeller blades during motion. The DIC strain measurements were then compared to strain gauge data to evaluate their accuracy and reliability. The results demonstrate that 3D DIC enables precise displacement measurements, while strain measurements are subject to certain limitations. Displacement measurements were achieved with a noise level of ±10 μm, while strain measurement noise ranged from 26 to 174 µm/m depending on direction. Strain gauge measurements were also performed for verification of the DIC measurements and calibration of the filtering procedure. Two types of non-metallic materials were used in the study: Nylon LGF60 PA6 for the propeller and 3D-printed PC ABS for the cantilever beam used in strain measurement validation. This study underscores the potential of DIC for monitoring rotating components, with a particular focus on measuring strains that are often overlooked in publications addressing similar topics. Additionally, it focuses on comparing DIC strain measurements with strain gauge data on rotating components, addressing a critical gap in existing literature, as strain measurement in rotating structures remains underexplored in current research. Full article

A Multimode Propulsion System (MPS) is an innovative spacecraft thruster concept that integrates two or more propulsion modes sharing the same type of propellant. A spacecraft equipped with an MPS can potentially combine the advantages of continuous-thrust electric propulsion and medium-to-high-thrust chemical propulsion within a single vehicle, while reducing the overall mass compared to traditional configurations where each propulsion system uses a different propellant. This feature makes the MPS concept particularly attractive for small spacecraft, such as the well-known CubeSats, which have now reached a high level of technological maturity and are employed not only in geocentric environments but also in interplanetary missions as support elements for conventional deep-space vehicles. Within the MPS framework, a Monopropellant-Electrospray Multimode Propulsion System (MEMPS) represents a specific type of micropropulsion technology that enables a single miniaturized propulsion unit to operate in either catalytic-chemical or electrospray-electric mode. This paper investigates the flight performance of a MEMPS-equipped CubeSat in a classical circle-to-circle orbit-raising (or lowering) maneuver within a two-dimensional mission scenario. Specifically, the study derives the optimal guidance law that allows the CubeSat to follow a transfer trajectory optimized either for minimum flight time or minimum propellant consumption, starting from a parking orbit of assigned radius and targeting a final circular orbit. Numerical simulations indicate that a heliocentric orbit raising, increasing the initial solar distance by $20\%$, can be achieved with a flight time of approximately 11 months and a propellant consumption slightly below 6 kg. The proposed method is applied to a heliocentric case study, although the procedure can be readily extended to geocentric transfer missions, which represent a more common application scenario for current CubeSat-based scientific missions. Full article