Search Results (713)

Conventional methods for train positioning and integrity monitoring are limited by their dependence on trackside infrastructure. This reliance on fixed equipment has prompted the investigation of global navigation satellite systems (GNSSs) as a more efficient alternative. The track-constrained algorithm based on the ‘train head (TH) and train tail (TT)’ double-difference (DD) baseline model (Single DD algorithm) has been applied for positioning and train length monitoring. It has been observed that the coefficient matrix can cause the inflation of the odometer corrections when the difference in track slope at both ends of the train is small. This inflation problem reduces the train positioning accuracy. A dual DD baseline fusion algorithm (Dual DD algorithm) with minimized sensitivity on the difference in track slope is thereby introduced. Furthermore, to validate the status of reference stations, a cross-checking function is utilized. The simulation results demonstrate that with a noise setting of 0.0067 m in carrier phase measurement, the Dual DD algorithm enhances the accuracy of train location estimation by up to 10 times compared to the Single DD algorithm. Meanwhile, the simulation result of train length difference validates the feasibility of the cross-checking function. Full article

Global warming caused by the increase in the atmospheric CO₂ content has become a focal environmental issue of common concern to the international community. As a key resource support for achieving the “dual carbon” goals in Western China, Sichuan Province requires a deep analysis of its carbon sources, carbon sinks, and its characteristics in terms of atmospheric environmental capacity, which is of great significance for formulating effective regional sustainable development strategies and responding to global climate change. In view of the unique geographical and climatic conditions in Sichuan Province and the current situation of a low and uneven distribution of atmospheric environmental capacity, this paper uses three forms of multi-source satellite data, OCO-2, OCO-3, and GOSAT, combined with other auxiliary data, to generate a daily XCO₂ concentration dataset with a spatial resolution of a 1km grid in Sichuan Province from 2015 to 2022. Based on the Optuna optimization method with 10-fold cross-validation, the optimal hyperparameter configuration of the four base learners of Stacking, random forest, gradient boosting decision tree, extreme gradient boosting, and the K nearest neighbor algorithm is searched for; finally, the logistic regression algorithm is used as the second-layer meta-learner to effectively improve the prediction accuracy and generalization ability of the Stacking ensemble learning model. According to the comparison of the performance of each model by cross-validation and TCCON site verification, the Stacking model significantly improved in accuracy, with an R², RMSE, and MAE of 0.983, 0.87 ppm and 0.19 ppm, respectively, which is better than those of traditional models such as RF, KNN, XGBoost, and GBRT. The accuracy verification of the atmospheric XCO₂ data estimated by the model based on the observation data of the two TCCON stations in Xianghe and Hefei showed that the correlation coefficients were 0.96 and 0.98, and the MAEs were 0.657 ppm and 0.639 ppm, respectively, further verifying the high accuracy and reliability of the model. At the same time, the fusion of multi-source satellite data significantly improved the spatial coverage of XCO₂ concentration data in Sichuan Province, effectively filling the gap in single satellite observation data. Based on the reconstructed XCO₂ dataset of Sichuan Province, the study revealed that there are significant regional and seasonal differences in the XCO₂ concentrations in the region, showing seasonal variation characteristics of being higher in spring and winter and lower in summer and autumn; in terms of the spatial distribution, the overall spatial distribution characteristics are high in the east and low in the west. This study helps to deepen our understanding of the carbon cycle and climate change, and can provide a scientific basis and risk assessment methods for policy formulation, effect evaluation, and international cooperation. Full article

Several studies conducted worldwide have reported on the effectiveness of consistent condom use with lubricants in preventing HIV transmission and acquisition; however, men who have sex with men (MSM) in Ghana continue to be disproportionately affected by the HIV burden. They are stigmatized, discriminated against, and criminalized, leading to social isolation, reduced access to health care, and inadequate targeted interventions. The dissemination of HIV prevention tools such as condoms and lubricants is also mainly focused on the general population, and this approach overlooks the specific needs and vulnerabilities of MSM. This study aimed to determine the prevalence and associated factors of consistent condom use with lubricants among MSM in Ghana. We analyzed cross-sectional data from the Ghana Men’s Study II dataset involving 4095 MSM aged 18 years and above. De-identified data were imported into STATA (College Station, TX, USA, software version 17) for data analysis. Descriptive analysis was performed to describe relevant characteristics of the study population. Multivariable logistic regression analysis was performed for significant variables in bivariate analysis to determine the associated factors of consistent condom use with lubricants. All the statistical analyses were performed at a 95% confidence interval, with significant differences at p < 0.05. The prevalence of consistent condom use with lubricants during penetrative anal sex was highest with male partners (44.9%), followed by female partners (40.0%), and all sexual partners (38.9%), respectively. In multivariable logistic regression analysis, having a senior high school education (AOR: 1.76; 95% CI: 0.88–3.12, p = 0.039), tertiary education or higher (AOR: 2.24; 95% CI: 0.86–3.23, p = 0.041), being an insertive sex partner (AOR: 1.26; 95% CI: 1.02–1.56, p = 0.029), being a sex worker (AOR: 1.41; 95% CI: 1.00–1.98, p = 0.048), buying sex from other males (AOR: 1.32; 95% CI: 1.03–1.70, p = 0.027), being a light drinker (AOR: 0.54; 95% CI: 0.42–0.68, p < 0.001), being a moderate drinker (AOR: 0.48; 95% CI: 0.30–0.78, p = 0.003), and possessing good HIV knowledge (AOR: 1.79; 95% CI: 1.46–2.20, p < 0.001) had higher odds of consistent condom use with lubricants. Being Islamic (AOR: 0.65; 95% CI: 0.49–0.87, p = 0.004), having a low income (AOR: 0.57; 95% CI: 0.42–0.77, p < 0.001), and easy access (AOR: 0.52; 95% CI: 0.37–0.72, p < 0.001) to condoms were positively associated with consistent condom use. This study found a low prevalence of consistent condom use with lubricants among the MSM population in Ghana. The study also found a range of socio-demographic, behavioral, and structural factors associated with consistent condom use with lubricants. This calls for very specific and unique public health interventions, such as developing a predictive model to identify and mitigate barriers to consistent condom use with lubricants. Full article

Air quality significantly impacts the environment and human living conditions, with direct and indirect effects on the economy. Precise and prompt detection of air pollutants is crucial for mitigating risks and implementing strategies to control pollution within acceptable thresholds. One of the common pollutants is nitrogen dioxide (NO₂), high concentrations of which are detrimental to the human respiratory system and may lead to serious lung diseases. Unfortunately, reliable NO₂ detection requires sophisticated and expensive apparatus. Although cheap sensors are now widespread, they lack accuracy and stability and are highly sensitive to environmental conditions. The purpose of this study is to propose a novel approach to precise calibration of the low-cost NO₂ sensors. It is illustrated using a custom-developed autonomous platform for cost-efficient NO₂ monitoring. The platform utilizes various sensors alongside electronic circuitry, control and communication units, and drivers. The calibration strategy leverages comprehensive data from multiple reference stations, employing neural network (NN) and kriging interpolation metamodels. These models are built using diverse environmental parameters (temperature, pressure, humidity) and cross-referenced data gathered by surplus NO₂ sensors. Instead of providing direct outputs of the calibrated sensor, our approach relies on predicting affine correction coefficients, which increase the flexibility of the correction process. Additionally, a calibration stage incorporating global correlation enhancement is developed and applied. Demonstrative experiments extensively validate this approach, affirming the platform and calibration methodology’s practicality for reliable and cost-effective NO₂ monitoring, especially keeping in mind that the predictive power of the enhanced sensor (correlation coefficient nearing 0.9 against reference data, RMSE < 3.5 µg/m³) is close to that of expensive reference equipment. Full article

Cross-domain authentication of drones has played an important role in emergency rescue, collaborative missions, and so on. However, the existing cross-domain authentication protocols for drones may cause privacy leakages and stolen-verifier attacks due to the storage of drone information by ground stations, and drones and ground stations are susceptible to capture attacks, which may suffer from impersonation attacks. To address these problems, we propose a lightweight cross-domain authentication protocol based on physical unclonable function (PUF). In the proposed protocol, the control center is not involved in the authentication process, preventing bottleneck problems when multiple drones authenticate simultaneously. Ground stations do not store drone information, effectively safeguarding against privacy leakage and stolen-verifier attacks. PUF is utilized to protect drones from capture attacks. We conduct both informal security analysis and formal security proof to demonstrate the protocol’s security. In terms of performance, compared with relevant schemes, our protocol shows remarkable efficiency improvements. Computationally, it is 5–92% more efficient. Regarding communication overhead, it is 9–68% lower than relevant schemes. For storage, it is 22–48% lower than relevant schemes. We simulated the proposed protocol using a Raspberry Pi 4B, which emulates the computational capabilities of actual UAV and ground stations. During the simulation, a large number of authentication requests were generated. We monitored key performance indicators such as authentication success rate, response time, and resource utilization. To test its security, we simulated common attacks like replay, forgery, and impersonation. The protocol’s timestamps effectively identified and rejected replayed messages. Meanwhile, the PUF mechanism and unique signature scheme foiled our attempts to forge authentication messages. These simulation results, combined with theoretical security proofs, confirm the protocol’s practical viability and security in real-world-like scenarios. Full article

With the rapid expansion of the aviation industry, pier-style departure lounges have become increasingly prevalent in modern airport terminals. Unlike traditional long enclosures—such as corridors, tunnels, and subway stations—airport terminal piers feature unique geometries, volumes, and interior finishes which complicate sound propagation. To address the paucity of objective acoustic data in these expansive environments, this study performed in situ measurements of impulse responses and sound pressure levels in two piers with distinct shapes and volumes within the same terminal. Key acoustic parameters, including the A-weighted equivalent continuous sound pressure level (L_Aeq), early decay time (EDT), reverberation time (T₃₀), definition (D₅₀), and speech transmission index (STI), were analyzed. The results reveal that EDT and T₃₀ increase significantly with distance from the sound source, while D₅₀ and STI decrease correspondingly. Specifically, compared to Pier B, which has a smaller cross-sectional area and a single-sided layout, Pier A, characterized by a larger cross-sectional area and a double-sided layout, exhibits a faster sound attenuation when the receiver is positioned closer to the source and a longer reverberation time when the receiver is farther from the source. Notably, STI does not differ significantly between the two piers. These findings enhance the understanding of acoustic behavior in large-span, elongated airport piers and provide valuable guidance for optimizing the acoustic environment of departure lounges to improve passenger comfort. Full article

The emergence of GaN-based micro-LEDs has revolutionized display technologies due to their superior brightness, energy efficiency, and thermal stability compared to traditional counterparts. However, the development of red-emitting micro-LEDs on silicon substrates (GaN-on-Si) faces significant challenges, among them including hydrogen-induced deactivation of p-GaN caused by hydrogen species generated from SiH₄ decomposition during SiO₂ passivation layer growth, which degrades device performance. This study systematically investigates the use of high-density metal-oxide dielectric passivation layers deposited by atomic layer deposition (ALD), specifically Al₂O₃ and HfO₂, to mitigate these effects and enhance device reliability. The passivation layers effectively suppress hydrogen diffusion and preserve p-GaN activation, ensuring improved ohmic contact formation and reduced forward voltage, which is measured by the probe station. The properties of the epitaxial layer and the cross-section morphology of the dielectric layer were characterized by photoluminescence (PL) and scanning electron microscopy (SEM), respectively. Experimental results reveal that Al₂O₃ exhibits superior thermal stability and lower current leakage under high-temperature annealing, while HfO₂ achieves higher light-output power (LOP) and efficiency under increased current densities. Electroluminescence (EL) measurements confirm that the passivation strategy maintains the intrinsic optical properties of the epitaxial wafer with minimal impact on Wp and FWHM across varying process conditions. The findings demonstrate the efficacy of metal-oxide dielectric passivation in addressing critical challenges in InGaN red micro-LED on silicon substrate fabrication, contributing to accelerating scalable and efficient next-generation display technologies. Full article

Planning in forestry should be based on accurate and reliable data. UAVs equipped with RGB cameras can enable fast and relatively cheap surveys, but their accuracy depends on many factors. Therefore, it is necessary to determine when UAVs can be used and when this type of survey gives data that does not reflect the true ground situation. This research analyzed the usability of a UAV, equipped with a RGB camera, for recording normal cross-sections and side ditch depths of the forest road in a lowland forest. The research was conducted in two time periods: during winter and spring, i.e., outside and during the vegetation season. DTMs of the area researched were created based on aerial photographs taken with the UAV, Z values of terrain points were read, and the depths of side ditches were calculated based on read Z values. The water depth in the side ditches and the vegetation height on the entire road body width were recorded to determine the influence of these two variables on the UAV survey error. Terrain points were recorded with the total station, which was the reference measurement method. An analysis of the obtained (read) DTM Z values revealed RMSE values of 10.09 cm for winter (outside vegetation) and 36.41 cm for spring (vegetation) UAV survey. The side ditch, calculated based on the DTM of the winter and spring periods of UAV recording, were statistically significantly different from the side ditch depths measured using the total station. Correcting the obtained data with water depth and vegetation height lowered the differences in Z values, as well as the ditch depths visible from ${RMSE}_Z$ (7.70 cm) for the winter UAV survey, with no statistically significant difference in side ditch depths. In the case of the correction of spring recording data, ${RMSE}_Z$ was smaller (23.41 cm) than before correction (36.41 cm), and the depth of the side ditches was still statistically significantly different. The authors conclude that water and ground vegetation can significantly affect UAV survey accuracy. In the winter period, side ditch depth measurement is possible in areas where water is not present. If water is present, manual measurement of water height and correction of obtained UAV data can improve data accuracy. On the other hand, spring or vegetation period UAV surveys are highly affected by ground vegetation height and the authors do not recommend surveys in that period. Full article

To address the challenges of cross-city travel for different types of electric vehicles (EV) and to tackle the issue of rapid charging in regions with weak power grids, this paper presents a strategic approach for locating and sizing highway charging stations tailored to such grid limitations. Initially, considering the initial EV state of charge, a path-demand-based model for EV charging station location–allocation is proposed to optimize station numbers and enhance vehicle flow, which indicates the passing rate of vehicles. Subsequently, a capacity configuration model is formulated, integrating wind, photovoltaic, storage, and diesel generators to manage the stations’ load. This model introduces a new objective function, the annual comprehensive cost, encompassing installation, operation, maintenance, wind and solar curtailment, and diesel generation costs. Simulation examples on north-western cross-city highways validate the efficacy of this approach, showing that the proposed wind–solar storage fast-charging station site selection and capacity optimization model can effectively cater to diverse electric vehicle charging demands. Moreover, it achieves a 90% self-consistency rate during operation across various typical daily scenarios, ensuring a secure and economically viable operational performance. Full article

High-precision, robust, and rapid three-dimensional (3D) passive positioning of the radiation source is critical for modern reconnaissance systems. While synthetic aperture technology has advanced 2D passive positioning performance, existing methods fail to achieve full 3D positioning with sufficient accuracy and computational efficiency. This is because of the inherent limitations of the single-station platform in resolving elevation-angle ambiguity. To address this gap, we propose a Cross-Track Interferometric Synthetic Aperture (CISA) 3D passive positioning algorithm. The algorithm innovatively realizes robust elevation-angle measurement by recursively deriving the long baseline unambiguous phase difference step-by-step from a virtual short baseline. The 3D positioning is achieved by combining passive synthetic aperture and interferometric angle measurement. Furthermore, we establish the incoherence model of synthetic aperture passive positioning for the first time and propose a compensation method based on static acquisition data to improve the practicability of CISA. Simulation and experimental results demonstrate that the proposed CISA algorithm achieves a positioning accuracy of 4.73‰R, improves computational efficiency by 1–2 orders of magnitude compared to conventional methods, and exhibits superior robustness to noise. The research can provide a reference for the method research and engineering realization of synthetic aperture 3D passive positioning. Full article

Fishways can effectively validate the effectiveness and rationality of their construction, optimize operational modes, and achieve intelligent scientific management through fish species detection. Traditional fish species detection methods for fishways are unsuitable due to inefficiency and disruption of the fish ecological environment. Therefore, combining cameras with target detection technology provides a better solution. However, challenges include the limited computational power of onsite equipment, the complexity of model deployment, low detection accuracy, and slow detection speed, all of which are significant obstacles. This paper proposes a fish detection model for accurate and efficient fish detection. Firstly, the backbone network integrates FasterNet-Block, C2f, and an efficient multi-scale EMA attention mechanism to address attention dispersion problems during feature extraction, delivering real-time object detection across different scales. Secondly, the Neck introduces a novel architecture to enhance feature fusion by integrating the RepBlock and BiFusion modules. Finally, the performance of the fish detection model is demonstrated based on the Fish26 dataset, in which the detection accuracy, computational cost, and parameter count are significantly optimized by 1.7%, 23.4%, and 24%, respectively, compared to the state-of-the-art model. At the same time, we installed detection devices in a specific fishway and deployed the proposed method within these devices. We collected data on four fish species passing through the fishway to create a dataset and train the model. The results of the practical application demonstrated superior fish detection capabilities, with rapid detection ability achieved while minimizing resource usage. This validated the effectiveness of the proposed method for equipment deployment in real-world engineering environments. This marks a shift from traditional manual detection to intelligent fish species detection in fishways, promoting water resource utilization and the protection of fish ecological environments. Full article

This article introduces a high-precision vertical pendulum tiltmeter with rapid deployment capability to improve the observation efficiency, practicality, and reliability of geophysical site tilt observation instruments. The system consists of a pendulum body, a triangular platform, a locking pendulum motor, a sealed cover, a ratio measurement bridge, a high-precision ADC, and an embedded data acquisition unit. The sensing unit adopts a vertical pendulum system suspended by a cross spring and a differential capacitance bridge measurement circuit, which can simultaneously measure two orthogonal directions of ground tilt. The pendulum is installed on a short baseline triangular platform, sealed as a whole with the platform, and equipped with a locking pendulum motor. When the pendulum is locked and packaged, it can withstand a 2 m free fall impact, with high reliability and easy use. It can be quickly deployed without the need for professional technicians. This article analyzes its various performance and technical indicators based on its application in the rapid deployment of the Zeketai seismic station in Xinjiang. It is of great significance for emergency response, mobile observation, base detection, anomaly verification, and other applications of ground tilt. Full article

Among urban public transport systems, light rail, mass transit, and tram systems offer sustainable travel options. However, many of these systems, particularly in developed countries, fail to meet user needs and the expectations of transport authorities. Increasing the demand for urban rail systems as an alternative to private cars is essential for achieving net zero targets and Sustainable Development Goals. This study investigates the factors influencing urban rail demand using qualitative data analysis, with a focus on thematic analysis. A systematic review of 53 studies from the UK, Europe, and worldwide, including journal articles and transport research reports, was conducted and coded using NVivo Version 15 software. Six main categories emerged: land use and accessibility, service quality, user benefits, governance, sustainability aspects, and user-focused elements. These categories, along with their themes and sub-themes, were analysed using cross-tabulations to compare attributes across domains. The key findings indicate that accessibility and intermodal connectivity are crucial for encouraging urban rail use, while ticketing, station facilities, walkability, travel costs, ventilation, and security also moderately influence user preferences. This study provides essential guidelines for policymakers and transport providers to improve urban rail systems and informed the development of a questionnaire to explore the interrelationships of these factors, discussed in a forthcoming paper. Full article

The impact generated by landslide-induced surge waves in large reservoirs poses significant threats to the safety of coastal residents and their property. It is essential to further elucidate the characteristics of these surge waves and enhance the capabilities of surge wave prediction and emergency warning systems. This research takes the Wangjiashan landslide in the Baihetan Hydropower Station reservoir area as a prototype, constructing a three-dimensional landslide model at a 1:150 scale. Through experiments designed under varying water levels and slope friction coefficients, the spatiotemporal evolution patterns of the landslide-induced surge waves along the riverbank were analyzed. The research results indicate that through the use of the zero-crossing method, fundamental characteristics of landslide-induced surge waves such as the maximum wave height, maximum period, significant wave height, and significant wave period could be obtained. Based on the statistical analysis of significant wave heights, the surge waves were categorized into three levels—small waves, moderate waves, and large waves—accounting for 15.79%, 78.95%, and 5.26% of the total waves, respectively. The height of surge waves decreases with an increase in the slope friction coefficient and river channel water depth. Additionally, the interaction between the landslide’s entry velocity into the water and the water level determines the effectiveness of wave propagation. This research provides crucial data support and theoretical foundations for the prediction and emergency warning of landslide-induced surge waves, offering significant implications for the prevention and mitigation of reservoir and landslide disasters. Full article

The Haidian District was, historically, rich in water resources. However, with urban development, the groundwater levels have declined, and most rivers have lost their ecological baseflows. To restore the aquatic ecosystems, the district has implemented a cyclic water network and advanced water replenishment projects. Nonetheless, the existing replenishment strategies face challenges, such as an insufficient scientific basis, lack of data, and high energy consumption. There is an urgent need to develop a scientifically robust ecological water replenishment system and optimize pump station scheduling to enhance water resource management efficiency. This study addresses the ecological water replenishment needs of seasonal rivers by integrating the Literature method, Rainfall-Runoff method, and R2cross method to develop a comprehensive approach for calculating the ecological flow and water depth. The proposed method simultaneously meets the ecological functionality and landscape requirements of seasonal rivers. Additionally, the SWMM model is employed to design intelligent pump station scheduling rules, optimizing the replenishment efficiency and energy consumption. Through field measurements and data collection, the ecological water demands of the river channels in different areas are assessed. Using a hydrodynamic model, the dynamic variations in the ecological flow and water depth are simulated. For the Cuihu, Daoxianghu, and Yongfeng areas, this study reveals that the current replenishment volume is insufficient to meet the landscape and ecological needs of the rivers. Most rivers require a 20–30% increase in water levels, with the Dazhai qu needing a substantial rise from 0.17 m to 0.3 m, representing an increase of 76%. Additionally, the results demonstrate that intelligent pump station scheduling can significantly reduce operating costs and energy consumption by dynamically adjusting the replenishment timing and flow rates. This approach optimizes the intervals between equipment activation and deactivation, thereby balancing ecological and energy-saving goals. This research not only provides technical support for the precise calculation of ecological replenishment volumes and the intelligent management of pump stations, but also offers scientific references for water resource management in similar regions. The findings will enhance the ecological functions and landscape quality of the rivers in the Haidian District while promoting refined and intelligent regional water resource management. Moreover, this study presents innovative solutions and theoretical foundations for water resource regulation under the backdrop of climate change. Full article