bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial Localization of a Transformer Robot Based on Ultrasonic Signal Wavelet Decomposition and PHAT-β-γ Generalized Cross Correlation
Authors: Ji Hongxin , Liu Xinghua , Zhang Jianwen , Liu Liqing
Published: February 2024

Because large oil-immersed transformers are enclosed by a metal shell, the on-site localization means it is difficult to achieve the accurate location of the patrol micro-robot inside a given transformer. To address this issue, a spatial ultrasonic localization method based on wavelet decomposition and PHAT-β-γ generalized cross correlation is proposed in this paper. The method is carried out with a five-element stereo ultrasonic array for the location of a transformer patrol robot. Firstly, the localization signal is decomposed into wavelet coefficients of different scales, which would realize the adaptive decomposition of the frequency of the localization signal from low frequencies to high frequencies. Then, the wavelet coefficients are denoised and reconstructed by using the semi-soft threshold function. Second, a modified phase transform-beta-gamma (PHAT-β-γ) method is used to calculate the exact time delay between different sensors by increasing the weights of the PHAT weighting function and introducing a correlation function. Finally, by using the proposed method, the accurate localization of the transformer patrol micro-robot is achieved with a five-element stereo ultrasonic array. The simulation and test results show that inside a transformer experimental oil tank (120 cm × 100 cm × 100 cm, L × W × H), the relative error of transformer patrol micro-robot spatial localization is within 4.1%, and the maximum localization error is less than 3 cm, which meets the requirement of engineering localization.
Extraction of Coastal Levees Using U-Net Model with Visible and Topographic Images Observed by High-Resolution Satellite Sensors
Authors: Xia Hao , Tonooka Hideyuki
Published: February 2024

Coastal levees play a role in protecting coastal areas from storm surges and high waves, and they provide important input information for inundation damage simulations. However, coastal levee data with uniformity and sufficient accuracy for inundation simulations are not always well developed. Against this background, this study proposed a method to extract coastal levees by inputting high spatial resolution optical satellite image products (RGB images, digital surface models (DSMs), and slope images that can be generated from DSM images), which have high data availability at the locations and times required for simulation, into a deep learning model. The model is based on U-Net, and post-processing for noise removal was introduced to further improve its accuracy. We also proposed a method to calculate levee height using a local maximum filter by giving DSM values to the extracted levee pixels. The validation was conducted in the coastal area of Ibaraki Prefecture in Japan as a test area. The levee mask images for training were manually created by combining these data with satellite images and Google Street View, because the levee GIS data created by the Ibaraki Prefectural Government were incomplete in some parts. First, the deep learning models were compared and evaluated, and it was shown that U-Net was more accurate than Pix2Pix and BBS-Net in identifying levees. Next, three cases of input images were evaluated: (Case 1) RGB image only, (Case 2) RGB and DSM images, and (Case 3) RGB, DSM, and slope images. Case 3 was found to be the most accurate, with an average Matthews correlation coefficient of 0.674. The effectiveness of noise removal post-processing was also demonstrated. In addition, an example of the calculation of levee heights was presented and evaluated for validity. In conclusion, this method was shown to be effective in extracting coastal levees. The evaluation of generalizability and use in actual inundation simulations are future tasks.
A 90.9 dB SNDR 95.3 dB DR Audio Delta–Sigma Modulator with FIA-Assisted OTA
Authors: Huang Gongxing , Wei Cong , Wei Rongshan
Published: February 2024

This paper presents a low-power, high-gain integrator design that uses a cascode operational transconductance amplifier (OTA) with floating inverter–amplifier (FIA) assistance. Compared to a traditional cascode, the proposed integrator can achieve a gain of 80 dB, while reducing power consumption by 30%. Upon completing the analysis, the value of the FIA drive capacitor and clock scheme for the FIA-assisted OTA were obtained. To enhance the dynamic range (DR) and mitigate quantization noise, a tri-level quantizer was employed. The design of the feedback digital-to-analog converter (DAC) was simplified, as it does not use additional mismatch shaping techniques. A third-order, discrete-time delta–sigma modulator was designed and fabricated in a 0.18 μm complementary metal-oxide semiconductor (CMOS) process. It operated on a 1.8 V supply, consuming 221 µW with a 24 kHz bandwidth. The measured SNDR and DR were 90.9 dB and 95.3 dB, respectively.
Unmanned Aerial Vehicle-Based Structural Health Monitoring and Computer Vision-Aided Procedure for Seismic Safety Measures of Linear Infrastructures
Authors: Ngeljaratan Luna , Bas Elif Ecem , Moustafa Mohamed A.
Published: February 2024

Computer vision in the structural health monitoring (SHM) field has become popular, especially for processing unmanned aerial vehicle (UAV) data, but still has limitations both in experimental testing and in practical applications. Prior works have focused on UAV challenges and opportunities for the vibration-based SHM of buildings or bridges, but practical and methodological gaps exist specifically for linear infrastructure systems such as pipelines. Since they are critical for the transportation of products and the transmission of energy, a feasibility study of UAV-based SHM for linear infrastructures is essential to ensuring their service continuity through an advanced SHM system. Thus, this study proposes a single UAV for the seismic monitoring and safety assessment of linear infrastructures along with their computer vision-aided procedures. The proposed procedures were implemented in a full-scale shake-table test of a natural gas pipeline assembly. The objectives were to explore the UAV potential for the seismic vibration monitoring of linear infrastructures with the aid of several computer vision algorithms and to investigate the impact of parameter selection for each algorithm on the matching accuracy. The procedure starts by adopting the Maximally Stable Extremal Region (MSER) method to extract covariant regions that remain similar through a certain threshold of image series. The feature of interest is then detected, extracted, and matched using the Speeded-Up Robust Features (SURF) and K-nearest Neighbor (KNN) algorithms. The Maximum Sample Consensus (MSAC) algorithm is applied for model fitting by maximizing the likelihood of the solution. The output of each algorithm is examined for correctness in matching pairs and accuracy, which is a highlight of this procedure, as no studies have ever investigated these properties. The raw data are corrected and scaled to generate displacement data. Finally, a structural safety assessment was performed using several system identification models. These procedures were first validated using an aluminum bar placed on an actuator and tested in three harmonic tests, and then an implementation case study on the pipeline shake-table tests was analyzed. The validation tests show good agreement between the UAV data and reference data. The shake-table test results also generate reasonable seismic performance and assess the pipeline seismic safety, demonstrating the feasibility of the proposed procedure and the prospect of UAV-based SHM for linear infrastructure monitoring.
Enhancing Camera Calibration for Traffic Surveillance with an Integrated Approach of Genetic Algorithm and Particle Swarm Optimization
Authors: Li Shenglin , Yoon Hwan-Sik
Published: February 2024

Recent advancements in sensor technologies, coupled with signal processing and machine learning, have enabled real-time traffic control systems to effectively adapt to changing traffic conditions. Cameras, as sensors, offer a cost-effective means to determine the number, location, type, and speed of vehicles, aiding decision-making at traffic intersections. However, the effective use of cameras for traffic surveillance requires proper calibration. This paper proposes a new optimization-based method for camera calibration. In this approach, initial calibration parameters are established using the Direct Linear Transformation (DLT) method. Then, optimization algorithms are applied to further refine the calibration parameters for the correction of nonlinear lens distortions. A significant enhancement in the optimization process is achieved through the integration of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) into a combined Integrated GA and PSO (IGAPSO) technique. The effectiveness of this method is demonstrated through the calibration of eleven roadside cameras at three different intersections. The experimental results show that when compared to the baseline DLT method, the vehicle localization error is reduced by 22.30% with GA, 22.31% with PSO, and 25.51% with IGAPSO.
Time Delay Study of Ultrasonic Gas Flowmeters Based on VMD–Hilbert Spectrum and Cross-Correlation
Authors: Kong Lingcai , Zhang Liang , Guo Hulin , Zhao Ning , Xu Xinhu
Published: February 2024

The accuracy of ultrasonic flowmeter time delay measurement is directly affected by the processing method of the ultrasonic echo signal. This paper proposes a method for estimating the time delay of the ultrasonic gas flowmeter based on the Variational Mode Decomposition (VMD)–Hilbert Spectrum and Cross-Correlation (CC). The method improves the accuracy of the ultrasonic gas flowmeter by enhancing the quality of the echo signal. To denoise forward and reverse ultrasonic echo signals collected at various wind speeds, a Butterworth filter is initially used. The ultrasonic echo signals are then analyzed by Empirical Mode De-composition (EMD) and VMD analysis to obtain the Intrinsic Mode Function (IMF) containing distinct center frequencies, respectively. The Hilbert spectrum time–frequency diagram is used to evaluate the results of the VMD and EMD decompositions. It is found that the IMF decomposed by VMD has a better filtering performance and better anti-interference performance. Therefore, the IMF with a better effect is selected for signal reconstruction. The ultrasonic time delay is then calculated using the Cross-Correlation algorithm. The self-developed ultrasonic gas flowmeter was tested on the experimental platform of the gas flow standard devices using this signal processing method. The results show a maximum indication error of 0.84% within the flow range of 60–606 m3/h, with a repeatability of no more than 0.29%. These results meet the 1-level accuracy requirements as outlined in the national ultrasonic flowmeters calibration regulation JJG1030-2007.
Analyzing Pile-Up Crash Severity: Insights from Real-Time Traffic and Environmental Factors Using Ensemble Machine Learning and Shapley Additive Explanations Method
Authors: Samerei Seyed Alireza , Aghabayk Kayvan , Montella Alfonso
Published: February 2024

Pile-up (PU) crashes, which involve multiple collisions between more than two vehicles within a brief timeframe, carry substantial consequences, including fatalities and significant damages. This study aims to investigate the real-time traffic, environmental, and crash characteristics and their interactions in terms of their contributions to severe PU crashes, which have been understudied. This study investigates and interprets the effects of Total Volume/Capacity (TV/C), “Heavy Vehicles Volume/Total Volume” (HVV/TV), and average speed. For this purpose, the PU crash severity was modelled and interpreted using the crash and real-time traffic data of Iran’s freeways over a 5-year period. Among six machine learning methods, the CatBoost model demonstrated superior performance, interpreted via the SHAP method. The results indicate that avg.speed > 90 km/h, TV/C < 0.6, HVV/TV ≥ 0.1, horizontal curves, longitudinal grades, nighttime, and the involvement of heavy vehicles are associated with the risk of severe PU crashes. Additionally, several interactions are associated with severe PU crashes, including the co-occurrence of TV/C ≈ 0.1, HVV/TV ≥ 0.25, and nighttime; the interactions between TV/C ≈ 0.1 or 0.45, HVV/TV ≥ 0.25, and avg.speed > 90 km/h; horizontal curves and high average speeds; horizontal curves; and nighttime. Overall, this research provides essential insights into traffic and environmental factors driving severe PU crashes, supporting informed decision-making for policymakers.
Optimized Solid–Liquid Separation of Phenolics from Lavender Waste and Properties of the Dried Extracts
Authors: Vareltzis Patroklos , Fotiou Dimitrios , Papatheologou Vasiliki , Kyroglou Smaro , Tsachouridou Efthymia , Goula Athanasia M.
Published: February 2024

Lavender distillation produces huge quantities of solid waste yearly. This waste is usually discarded, resulting in serious environmental issues. However, it still contains residual essential oil and other bioactive compounds. This research reports on the development and comparison of optimized solid–liquid separation methods, i.e., microwave- (MAE) and ultrasound-assisted extraction (UAE) of phenolic compounds from lavender distillation waste. The optimal pretreatment conditions, such as waste moisture content and particle size, were also determined. The extracts were spray- or freeze-dried and the resulting powders were characterized for their physicochemical properties. The majority of the original phenolic compounds in lavender were found in the leachate fraction after distillation (61%), whereas 43% was found in the solid waste. Drying of the solid waste before extraction affected the process efficiency. UAE led to a higher phenolic content and greater antioxidant properties compared to MAE. Drying (spray or freeze) the extracts did not significantly affect their phenolic content, whereas the use of maltodextrin as a drying agent improved the drying process yield, especially when using the freeze-drying method. It is concluded that valorization of lavender distillation wastes can be achieved via an integrated process consisting of a green extraction method and a consequent drying process that results in a stable bioactive powder.
A Review of Solar Forecasting Techniques and the Role of Artificial Intelligence
Authors: Barhmi Khadija , Heynen Chris , Golroodbari Sara , van Sark Wilfried
Published: February 2024

Solar energy forecasting is essential for the effective integration of solar power into electricity grids and the optimal management of renewable energy resources. Distinguishing itself from the existing literature, this review study provides a nuanced contribution by centering on advancements in forecasting techniques. While preceding reviews have examined factors such as meteorological input parameters, time horizons, the preprocessing methodology, optimization, and sample size, our study uniquely delves into a diverse spectrum of time horizons, spanning ultrashort intervals (1 min to 1 h) to more extended durations (up to 24 h). This temporal diversity equips decision makers in the renewable energy sector with tools for enhanced resource allocation and refined operational planning. Our investigation highlights the prominence of Artificial Intelligence (AI) techniques, specifically focusing on Neural Networks in solar energy forecasting, and we review supervised learning, regression, ensembles, and physics-based methods. This showcases a multifaceted approach to address the intricate challenges associated with solar energy predictions. The integration of Satellite Imagery, weather predictions, and historical data further augments precision in forecasting. In assessing forecasting models, our study describes various error metrics. While the existing literature discusses the importance of metrics, our emphasis lies on the significance of standardized datasets and benchmark methods to ensure accurate evaluations and facilitate meaningful comparisons with naive forecasts. This study stands as a significant advancement in the field, fostering the development of accurate models crucial for effective renewable energy planning and emphasizing the imperative for standardization, thus addressing key gaps in the existing research landscape.
Improvements in Jump Height, Speed, and Quality of Life through an 8-Week Strength Program in Male Adolescents Soccer Players
Authors: Díaz-Hidalgo Sara , Ranchal-Sanchez Antonio , Jurado-Castro Jose
Published: February 2024

This study aimed to assess the enhancement of physical fitness and quality of life through an 8-week strength training program in male adolescent soccer players aged between 12 and 13 years. A lower body muscle group intervention was performed, with 17 players in the experimental group (EG) and 15 players in the control group (CG). The EG carried out soccer training complemented by specific strength work. Pre- and post- intervention assessments included body composition, jump height, speed with change of direction, maximum speed in 20 m, movement velocity in back-squat, perceived fatigue effort, academic performance, and quality of life. A general linear repeated measures model analysis was used considering each variable, the interaction between groups (EG, CG) and time (basal, 8-week), to analyze the differences between and within groups. The results showed a reduction in fat in the upper limbs and trunk, improvements in jump height, maximum speed of 20 m, and changes of direction, and increased quality of life (p < 0.05) in the EG. It was concluded that a strength program could improve some components of physical performance in male adolescent soccer players.
ISAK-Based Anthropometric Standards for Elite Male and Female Soccer Players
Authors: Petri Cristian , Campa Francesco , Holway Francis , Pengue Luca , Arrones Luis Suarez
Published: February 2024

This study aimed to provide reference values for anthropometric characteristics of elite male and female soccer players, considering a group of individuals from the general population as controls. The anthropometric profiles of 357 elite soccer players [184 males (age 24.3 ± 4.3 y) and 173 females (age 25.2 ± 5.1 y)] participating in the first Italian league (Serie A) and 363 subjects from the general population [188 males (age 24.2 ± 4.8 y) and 175 females (age 25.0 ± 5.1 y)] were measured according to the guidelines of the International Society for the Advancement of Kinanthropometry (ISAK). Reference percentiles for stature, body mass, circumferences, eight skinfolds (biceps, triceps, subscapular, suprailiac, supraspinal, abdominal, front thigh, and calf), breadths, and somatotype were calculated and stratified by player position and sex. No difference (p > 0.05) was found in age between the two groups. Soccer players showed lower values for the sum of the eight ISAK skinfolds than individuals from the general population of the same sex. This suggests lower adipose tissue, as indicated by a lower endomorphic component. The somatotype was endomorphic mesomorph and mesomorphic endomorph for the male and female individuals from the general population, respectively. The male soccer players were ectomorphic mesomorphs, while the females were balanced mesomorphs, defining a sport-specific morphology. This study provides sex- and role-specific anthropometric standards for elite soccer players. Raw anthropometric reference values may be useful for evaluating body composition without using any predictive equations or assumptions.
New Vessel Extraction Method by Using Skew Normal Distribution for MRA Images
Authors: Bahrami Tohid , Khamnei Hossein Jabbari , Lakestani Mehrdad , Kibria B. M. Golam
Published: February 2024

Vascular-related diseases pose significant public health challenges and are a leading cause of mortality and disability. Understanding the complex structure of the vascular system and its processes is crucial for addressing these issues. Recent advancements in medical imaging technology have enabled the generation of high-resolution 3D images of vascular structures, leading to a diverse array of methods for vascular extraction. While previous research has often assumed a normal distribution of image data, this paper introduces a novel vessel extraction method that utilizes the skew normal distribution for more accurate probability distribution modeling. The proposed method begins with a preprocessing step to enhance vessel structures and reduce noise in Magnetic Resonance Angiography (MRA) images. The skew normal distribution, known for its ability to model skewed data, is then employed to characterize the intensity distribution of vessels. By estimating the parameters of the skew normal distribution using the Expectation-Maximization (EM) algorithm, the method effectively separates vessel pixels from the background and non-vessel regions. To extract vessels, a thresholding technique is applied based on the estimated skew normal distribution parameters. This segmentation process enables accurate vessel extraction, particularly in detecting thin vessels and enhancing the delineation of vascular edges with low contrast. Experimental evaluations on a diverse set of MRA images demonstrate the superior performance of the proposed method compared to previous approaches in terms of accuracy and computational efficiency. The presented vessel extraction method holds promise for improving the diagnosis and treatment of vascular-related diseases. By leveraging the skew normal distribution, it provides accurate and efficient vessel segmentation, contributing to the advancement of vascular imaging in the field of medical image analysis.
Deep Learning-Based Carbon Emission Forecasting and Peak Carbon Pathways in China’s Logistics Industry
Authors: Chen Ting , Wang Maochun
Published: February 2024

As a major energy-consuming industry, energy conservation and emission reduction in the logistics industry are critical to China’s timely achievement of its dual-carbon goals of “carbon peaking” by 2030 and “carbon neutrality” by 2060. Based on deep learning, Random Forest (RF) was used to screen out the key factors affecting carbon emissions in the logistics industry, and the Whale Algorithm-optimized Radial Basis Function Neural Network (WOA-RBF) was proposed. The Monte Carlo simulation predicted the future evolution trends of each key factor under the three scenarios of baseline scenario (BAU), policy regulation scenario (PR), and technological breakthrough scenario (TB) and accurately predicted the carbon emission trends of the logistics industry from 2023 to 2035 by using the most probable future values of each influencing factor as inputs to the WOA-RBF prediction model. The results of the study demonstrate that fixed asset investment (LFI), population (P), total energy consumption (E), energy consumption per unit of value added of the logistics industry (EIL), share of oil consumption (OR), and share of railway freight turnover (RTR) are the key factors influencing the logistics industry’s carbon emissions. Monte Carlo simulations can effectively reflect the uncertainty of future changes in these key factors. In comparison to the BAU and PR scenarios, the TB scenario, with the combined incentives of national policy regulation and technology innovation, is the most likely for the logistics industry to meet the “Peak Carbon” goal baseline scenario.
Trace Metal Contamination in Community Garden Soils across the United States
Authors: Malone Maeve , Shakya Kabindra M.
Published: February 2024

Community gardens are often seen as a means for producing sustainable food resources in urban communities. However, the presence of trace metals and metalloids such as lead, arsenic, and cadmium in urban soils poses a health risk to gardeners who participate in urban community gardens. They are exposed to these contaminates through multiple exposure pathways such as inhalation and ingestion directly through soil or through crops grown in the soil. Hot spots of soil contamination are higher in areas of cities with greater minority populations and lower incomes. This paper reviews the state of heavy metal contamination in community garden soils across the United States. This paper outlines the major sources of heavy metals in urban soils, exposure pathways, the ways to reduce heavy metal levels in garden soils, the means to slow down the uptake of heavy metals, and limit the exposure of these contaminates. The application of biochar and compost, implementing raised beds, and maintaining a natural pH are all examples of ways to mitigate heavy metal contaminants.
Environmental Management of Ecuador’s Business Sector in the Fight against Climate Change
Authors: Aizaga Miguel , Ramírez Marcelo , Colmenárez Mujica María Carmen , Toasa Renato M.
Published: February 2024

The private sector is part of the United Nations Global Compact, which promotes the voluntary participation of organizations to implement environmental care strategies. The purpose of this article is to examine the performance of Ecuadorian companies in regard to environmental management, especially in the fight against climate change, considering the economic sectors (manufacturing, mining, commerce, construction and services). Figures from the National Institute of Statistics and the Census of Ecuador (2020) are used, including descriptive statistics and cross-tabulations with Cramer’s V index. The results show that approximately 5% of companies had the ISO 14001:2015 certification. In the seven actions against climate change considered, the proportion of companies that did not consider them to be current expenses predominated. Cramer’s V index, for associating the economic sector and the environmental spend, revealed that certain economic sectors (manufacturing and mining) are contributing significantly to environmental management spending in the areas of air, soil, wastewater and waste treatment, while no economic sector dominates the others in areas such as radiation treatment, the use of mineral or energy resources and water resources.
Societal Involvement in Household Waste Sorting Behavior in the Context of the Circular Economy: A Case Study of Poland
Authors: Rogowska Justyna , Piątkowska Kamila , Głowacz Zuzanna
Published: February 2024

Population growth and the increasing demand for raw materials with the expanding amount of waste in the environment have resulted in the need to change the production–consumption model based on a one-way flow of materials (from raw materials through products to waste). An alternative to the linear model of production and consumption is the circular economy model (CE), which assumes more efficient use of resources, waste recovery (including municipal waste), and the reuse of materials. One of the important elements of this system is recycling, which will not efficiently function without public participation in the waste sorting system. The aim of the survey study was to examine the motivation, knowledge, and behavior of Polish respondents regarding the sorting of household waste and related problems. The survey results showed that almost 90% of respondents declared waste sorting, mostly because of the threat to the environment (34%) and the desire to contribute to the recycling process (34%), despite respondents’ problems with assigning certain types of waste to appropriate containers. This indicates the need for further education in this area, which should be conducted primarily online—the main sources of information about waste sorting, according to the respondents, are social media (33%) and websites (22%). The research results can help in designing educational campaigns both at the national (Ministry of the Environment and non-governmental organizations) and regional (municipal) levels, as these results indicate in which areas citizens have the most problems with waste separation.
New Coal Char-Based Building Products: Manufacturing, Engineering Performance, and Techno-Economic Analysis for the USA Market
Authors: Pandey Suraj Prasad , Yu Hua , Lau Chooikim , Ng Kam
Published: February 2024

Common building products, i.e., thin brick and stone veneer, add the look of brick walls or the enduring charm of natural stones into buildings and houses without imposing a substantial increase in structural load. This study investigates the mechanical strength, durability, and economic feasibility of producing innovative char-based thin bricks and stone veneers. The char-based thin brick vacuum treated with hydrophobic liquid exhibits water absorption rates within the 4–7% range, displays durability against 50 freeze–thaw (F-T) cycles, and maintains a saturation coefficient below 0.6. In contrast, commercial thin bricks have water absorption of 9–12%. Treated char-based stone veneer has water absorption of 5.3% and an average compressive strength of 19.2 MPa, maintains its structural integrity throughout 50 F-T cycles, and exhibits a negligible linear shrinkage of approximately 0.01%. In contrast, commercial stone veneers have water absorption of 10–16%. These engineering properties meet the criteria as per ASTM standards C1088 and C1670 for thin brick and stone veneer, respectively. A techno-economic study was preliminarily conducted to examine the potential cost efficiency and cash flow in manufacturing these char-based building products. The manufacturing cost of USD 25.83 is lower than the average market price of 64.65 USD/sq. m. for thin bricks. The manufacturing cost of USD 32.65 is lower than the average market price of 129.17 USD/sq. m. for stone veneers. These comparisons present a compelling economic advantage for their commercialization. This comprehensive study has demonstrated the advantages of sustainable char-based stone veneers and thin bricks regarding engineering performance and economic benefits.
Swarm Division-Based Aircraft Velocity Obstacle Optimization Considering Low-Carbon Emissions
Authors: Zhong Qingwei , Yu Yingxue , Zhang Yongxiang , Guo Jingwei , He Zian
Published: February 2024

In the pursuit of sustainable aviation, this paper presents an innovative approach that adopts a swarm division strategy to enhance and refine the velocity obstacle (VO) method, guided by a low-carbon principle. A dynamic elliptical protection zone model forms the core of this innovative approach. Specifically, this dynamic elliptical protection zone is created based on the difference in aircraft velocity, and a swarm division strategy is introduced in this process. Initially, aircraft that share the same route and type, and have similar velocities and distances, are grouped into swarms. Then, the characteristics of the swarms, such as mass points, velocities, and protection zones, are recorded. Second, the collision cone (CC) between swarms is established, and planar geometrical analysis is used to determine the optimal relief velocity and heading of aircraft on the low-carbon objective while ensuring a safe interval between aircraft in the swarm during the relief period. Additionally, a swarm control algorithm is utilized to adjust the velocity of the aircraft by a small margin. Finally, simulation experiments are conducted using Python, revealing that the swarm relief efficiency of the enhanced VO method sees a notable increase of over 33%. Concurrently, the need for adjustments decreases by an average of 32.78%, while fuel savings reach as high as 70.18%. The strategy is real-time and operational, significantly reduces the air traffic controller (ATC) workload, improves flight efficiency and safety, and contributes positively to the reduction in carbon emissions, which is beneficial for the environment.
Ultimate Load-Bearing Capacity and Sustainable Performance of Pile Foundations of Yanji Suspension Bridge in Fault Zone Based on Refined Geological Model
Authors: Ren Meng , Cheng Jiaqi , Zhang Shengbin , Pang Yutao , Zhu Weiyuan
Published: February 2024

Pile foundation is the most important foundation type of long-span bridges, of which the ultimate load-bearing capacity affects the safety and sustainable performance of bridges. When constructing large-span bridges, the bridge site may be close to the adjacent fault zones, which seriously affects the safety and long-term performance of pile foundations, causing the failure and unsustainability of long-span bridges in their life-cycle service life. At present, there are no engineering design rules or methods for assessing the load-bearing capacity of the pile foundation near the fault zones. To study the influence of the fault zone on the loading-bearing capacity and sustainable performance of pile foundations, triaxial compression tests were carried out on the mylonite at the Yanji suspension bridge site near the Xiangfan–Guangji fault zone in Hubei Province. The mechanical properties of mylonite were reflected by the Mohr–Coulomb yield criterion, and a topographic and geological modeling method based on the multi-platform was established. Then, the ABAQUS finite element software was used to study the deformation, stress, failure modes, and sustainable performance of the pile foundation under different bridge load levels, analyze the safety of the pile foundation in the fracture zone, and summarize the ultimate bearing characteristics of the pile foundation. The results show that the whole pile and surrounding rock are basically elastic under the pressure of the designed load, the plastic zone of the pile foundation is mainly concentrated at the pile bottom, and the shear stress concentration zone of the pile is mainly manifested in the joint of the cap and pile and the interface between soft and hard rock. When the load is increased to 4 times the designed load, the stress concentration area of the pile body gradually shifts upward from the pile bottom, and the surrounding rock at the bottom forms an “X-shaped” shear failure zone. After 100 years of operation, the maximum compressive stress of piles reaches 28.6 MPa, which is 120% higher than that at the beginning of the bridge construction, indicating that the sustainable performance of the piles can withstand the effect of the fault zone over the designed service years.
Occurrence, Source Apportionment, and Ecological Risk of Typical Pharmaceuticals in Surface Waters of Beijing, China
Authors: Huangfu Yonghao , Li Qingshan , Yang Weiwei , Bu Qingwei , Yang Lei , Tang Jianfeng , Gan Jie
Published: February 2024

Various studies have shown that the heavy use of pharmaceuticals poses serious ecological risks, especially in metropolitan areas with intensive human activities. In this study, the spatial distribution, sources, and ecological risks of 29 pharmaceuticals in 82 surface waters collected from the North Canal Basin in Beijing were studied. The results showed that the pharmaceutical concentrations ranged from not detected to 193 ng/L, with ampicillin being undetected while ofloxacin had a 100% detection frequency, which indicates the widespread occurrence of pharmaceutical pollution in the North Canal Basin. In comparison with other freshwater study areas, concentrations of pharmaceuticals in the North Canal Basin were generally at moderate levels. It was found that pharmaceutical concentrations were always higher in rivers that directly received wastewater effluents. Source analysis was conducted using the positive matrix factorization model. Combining the spatial pollution patterns of pharmaceuticals, it has been found that wastewater effluents contributed the most to the loads of pharmaceuticals in the studied basin, while in suburban areas, a possible contribution of untreated wastewater was demonstrated. Risk assessment indicated that approximately 55% of the pharmaceuticals posed low-to-high ecological risks, and combining the results of risk analyses, it is advised that controlling WWTP effluent is probably the most cost-effective measure in treating pharmaceutical pollution.
Training and Active Case Detection to Prevent Leprosy: Effect on Knowledge, Attitude and Skills of Health Workers on Early Diagnosis of Leprosy in a Leprosy Hotspot District in Ethiopia
Authors: Mamo Ephrem , Tsehay Dareskedar , Hassen Seid , Getahun Solomon , Mengiste Addis , Tadesse Beletshachew , Tadesse Tesfaye , Legesse Mengestu , Bobosha Kidist
Published: February 2024

Background: Despite all of the efforts, leprosy continues to affect hundreds of thousands of people every year, including children, showing the ongoing transmission of the disease within the population. The transmission of leprosy can be interrupted through an integrated approach that includes active case-finding, contact tracing and capacity building of health workers. Methods: A cross-sectional study design was used to assess the knowledge, attitudes and skills of health workers in the screening and diagnosis of leprosy. One hundred and eighty-one and eighty-eight health care workers participated in the pre-and post-assessment surveys, respectively. Data were collected through interviews and an observational checklist. Frequency tables and graphs were used to describe the study variables, and statistical significance between pre- and post-assessment surveys was declared at p-value < 0.5. Result: The percentages of healthcare workers with good knowledge, positive attitudes and skills were 61.2%, 55.6% and 51.7% in the pre-assessment survey and 77.3%, 56.3% and 75.0%, respectively, in the post-assessment survey. There was a significant improvement in the knowledge and skill scores of participants in the post-assessment survey (p < 0.01). During the campaign, 3780 index contacts were screened; 570 (15.1%) were diagnosed with skin diseases, and 17 new leprosy cases were diagnosed (case detection rate of 45 per 10,000 contacts). Conclusion: Training improved the knowledge and skills of healthcare workers, and a large number of skin diseases were detected through mass screening and active case findings. Providing training for frontline healthcare workers contributed to the detection of more cases and facilitated early detection of leprosy cases.
Viroporins Manipulate Cellular Powerhouses and Modulate Innate Immunity
Authors: Cedillo-Barrón Leticia , García-Cordero Julio , Visoso-Carvajal Giovani , León-Juárez Moisés
Published: February 2024

Viruses have a wide repertoire of molecular strategies that focus on their replication or the facilitation of different stages of the viral cycle. One of these strategies is mediated by the activity of viroporins, which are multifunctional viral proteins that, upon oligomerization, exhibit ion channel properties with mild ion selectivity. Viroporins facilitate multiple processes, such as the regulation of immune response and inflammasome activation through the induction of pore formation in various cell organelle membranes to facilitate the escape of ions and the alteration of intracellular homeostasis. Viroporins target diverse membranes (such as the cellular membrane), endoplasmic reticulum, and mitochondria. Cumulative data regarding the importance of mitochondria function in multiple processes, such as cellular metabolism, energy production, calcium homeostasis, apoptosis, and mitophagy, have been reported. The direct or indirect interaction of viroporins with mitochondria and how this interaction affects the functioning of mitochondrial cells in the innate immunity of host cells against viruses remains unclear. A better understanding of the viroporin–mitochondria interactions will provide insights into their role in affecting host immune signaling through the mitochondria. Thus, in this review, we mainly focus on descriptions of viroporins and studies that have provided insights into the role of viroporins in hijacked mitochondria.
Sero and Carriage Epidemiology of Pertussis in Urban and Rural Regions in Vietnam
Authors: Toizumi Michiko , Le Lien Thuy , Nguyen Hien Anh Thi , Le Thao Thi Thu , Kitamura Noriko , Bui Liem Xuan , Ho Nen Minh , Do Hung Thai , Kamachi Kazunari , Otsuka Nao , Bui Minh Xuan , Dang Duc Anh , Yoshida Lay-Myint
Published: February 2024

The underestimation of the pertussis burden prompted our study to investigate the prevalence of recent pertussis infection, its associated factors, and antibody titer changes in the same individuals in Vietnam. Two cross-sectional surveys were conducted in Nha Trang in 2017 and Quang Ngai in 2019, representing high- and low-vaccine-coverage areas, respectively. Serum anti-pertussis toxin immunoglobulin-G (anti-PT IgG) ≥ 62.5 IU/mL by ELISA indicated infection in the previous 12 months. In Nha Trang, the participants of the 2017 survey were followed up in 2019. Logistic regression was used to determine the odds ratios for the characteristics associated with anti-PT IgG ≥ 62.5. The age-stratified prevalence in patients aged >2 years ranged from 2.1% (age 26–35) to 9.6% (3–5) in Nha Trang (2017) and from 7.2% (age 26–35) to 11.4% (6–15) in Quang Ngai. The prevalence tended to be higher in Quang Ngai across all age groups. Cough, recent antibiotic use, and smoking in Nha Trang were positively associated with an anti-PT IgG of ≥62.5, and having been diagnosed with pertussis and persistent cough with paroxysms/whoop in Quang Ngai were positively associated with an anti-PT IgG of ≥62.5. No nasopharyngeal swabs were positive for Bordetella pertussis using real-time PCR. The geometric mean of the IgG titer ratio from 2019 to 2017 was 1.45 in the paired samples. This study emphasizes Bordetella pertussis circulation across all age groups in both low- and high-vaccine-coverage settings in Vietnam, underscoring the need for continuous and standardized surveillance for a comprehensive understanding of its epidemiology.
Development of a Highly Efficient CRISPR/Cas9-Mediated Herpesvirus of Turkey-Based Vaccine against Novel Variant Infectious Bursal Disease Virus
Authors: Zhang Jun-Feng , Park Jong-Yeol , Kim Sang-Won , Choi Yu-Ri , Cha Se-Yeoun , Jang Hyung-Kwan , Wei Bai , Kang Min
Published: February 2024

Infectious bursal disease (IBD), caused by IBD virus (IBDV), is an extremely contagious immunosuppressive disease that causes major losses for the poultry industry worldwide. Recently, the novel variant IBDV (G2d) has been highly prevalent in Korea, but the current vaccines against this very virulent IBDV have limited efficacy against this novel variant. To develop a vaccine against this variant IBDV, a recombinant virus designated rHVT-VP2 was constructed by inserting the IBDV (G2d) VP2 gene into herpesvirus of turkeys (HVT) using CRISPR/Cas9 gene-editing technology. The PCR and sequencing results obtained showed that the recombinant virus rHVT-VP2 was successfully constructed. Vaccination with rHVT-VP2 generated IBDV-specific antibodies in specific pathogen-free chickens starting from 2 weeks post-immunization. Seven days after the challenge, the autopsy results showed that the bursa atrophy rates of the rHVT-VP2, HVT, vaccine A, and positive control groups were 0%, 100%, 60%, and 100%, respectively, and the BBIX values were 1.07 ± 0.22, 0.27 ± 0.05, 0.64 ± 0.33, and 0.32 ± 0.06, respectively. These results indicate that rHVT-VP2 can provide 100% protection against a challenge with the IBDV (G2d), whereas vaccine A only provides partial protection. In conclusion, vaccination with the recombinant virus rHVT-VP2 can provide chickens with effective protection against variant IBDV (G2d).
Vaccine Based on Recombinant Fusion Protein Combining Hepatitis B Virus PreS with SARS-CoV-2 Wild-Type- and Omicron-Derived Receptor Binding Domain Strongly Induces Omicron-Neutralizing Antibodies in a Murine Model
Authors: Gattinger Pia , Kratzer Bernhard , Sehgal Al Nasar Ahmed , Ohradanova-Repic Anna , Gebetsberger Laura , Tajti Gabor , Focke-Tejkl Margarete , Schaar Mirjam , Fuhrmann Verena , Petrowitsch Lukas , Keller Walter , Högler Sandra , Stockinger Hannes , Pickl Winfried F. , Valenta Rudolf
Published: February 2024

Background: COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a recurrent endemic disease affecting the whole world. Since November 2021, Omicron and its subvariants have dominated in the spread of the disease. In order to prevent severe courses of disease, vaccines are needed to boost and maintain antibody levels capable of neutralizing Omicron. Recently, we produced and characterized a SARS-CoV-2 vaccine based on a recombinant fusion protein consisting of hepatitis B virus (HBV)-derived PreS and two SARS-CoV-2 wild-type RBDs. Objectives: To develop a PreS-RBD vaccine which induces high levels of Omicron-specific neutralizing antibodies. Methods: We designed, produced, characterized and compared strain-specific (wild-type: W-PreS-W; Omicron: O-PreS-O), bivalent (mix of W-PreS-W and O-PreS-O) and chimeric (i.e., W-PreS-O) SARS-CoV-2 protein subunit vaccines. Immunogens were characterized in vitro using protein chemical methods, mass spectrometry, and circular dichroism in combination with thermal denaturation and immunological methods. In addition, BALB/c mice were immunized with aluminum–hydroxide-adsorbed proteins and aluminum hydroxide alone (i.e., placebo) to study the specific antibody and cytokine responses, safety and Omicron neutralization. Results: Defined and pure immunogens could be produced in significant quantities as secreted and folded proteins in mammalian cells. The antibodies induced after vaccination with different doses of strain-specific, bivalent and chimeric PreS-RBD fusion proteins reacted with wild-type and Omicron RBD in a dose-dependent manner and resulted in a mixed Th1/Th2 immune response. Interestingly, the RBD-specific IgG levels induced with the different vaccines were comparable, but the W-PreS-O-induced virus neutralization titers against Omicron (median VNT50: 5000) were seven- and twofold higher than the W-PreS-W- and O-PreS-O-specific ones, respectively, and they were six-fold higher than those of the bivalent vaccine. Conclusion: Among the tested immunogens, the chimeric PreS-RBD subunit vaccine, W-PreS-O, induced the highest neutralizing antibody titers against Omicron. Thus, W-PreS-O seems to be a highly promising COVID-19 vaccine candidate for further preclinical and clinical evaluation.
Potential Cost-Effectiveness of Maternal Influenza Immunisation in Low-Income Countries: An Explorative Modelling Study and Value of Information Analysis to Guide Future Clinical Research
Authors: Wang Yingying , Giles Michelle L. , Carvalho Natalie
Published: February 2024

Maternal influenza immunisation (MII) is recommended for protecting pregnant women and infants under six months of age from severe disease related to influenza. However, few low-income countries have introduced this vaccine. Existing cost-effectiveness studies do not consider potential vaccine non-specific effects (NSE) observed in some settings, such as reductions in preterm birth. A decision tree model was built to examine the potential cost-effectiveness of MII in a hypothetical low-income country compared to no vaccination, considering possible values for NSE on preterm birth in addition to vaccine-specific effects on influenza. We synthesized epidemiological and cost data from low-income countries. All costs were adjusted to 2021 United States dollars (USD). We considered cost-effectiveness thresholds that reflect opportunity costs (USD 188 per disability-adjusted life year averted; range: USD 28–538). Results suggest that even a small (5%) NSE on preterm birth may make MII a cost-effective strategy in these settings. A value of information analysis indicated that acquiring more information on the presence and possible size of NSE of MII could greatly reduce the uncertainty in decision-making on MII. Further clinical research investigating NSE in low-income countries may be of high value to optimise immunisation policy.