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Article ; Online: Space Target Tracking with the HRRP Characteristic-Aided Filter via Space-Based Radar

Shuyu Zheng / Libing Jiang / Qingwei Yang / Yingjian Zhao / Zhuang Wang

Remote Sensing, Vol 15, Iss 4808, p

2023 Volume 4808

Abstract: Approaching space target tracking is a typical and challenging mission in the space situational awareness (SSA) field. As the space-based radar is able to monitor the space targets of interest full-weather all-time, the space-based radar system is ... ...

Abstract	Approaching space target tracking is a typical and challenging mission in the space situational awareness (SSA) field. As the space-based radar is able to monitor the space targets of interest full-weather all-time, the space-based radar system is utilized in this paper. However, most multi-target tracking (MTT) filters in target tracking studies merely utilize the location or narrow measurements, and many potentially valuable electromagnetic scattering characteristics are missed, which leads to space target false tracking problems. The space-based radar transmits a wide-band signal, and the measured high-resolution range profile (HRRP) information is an effective characteristic for different target discrimination. Therefore, the HRRP characteristics of space targets are implemented into the update recursion of the MTT filter, which can be utilized to improve the tracking performance. Then, to predict the target HRRP sequence, the geometrical theory of diffraction (GTD) model is utilized. Additionally, a modified spatial spectrum method with a novel covariance matrix is designed to improve the scattering parameter estimation accuracy. Finally, an adapting threshold is devised for merging the Gaussian mixture (GM) components weights. The proposed threshold is on the basis of the proposed HRRP characteristic-aided probability hypothesis density (PHD) filter, and it can tackle the problem of space target discrimination. Simulation results validate the effectiveness and robustness of the proposed probability hypothesis density (HGI-PHD) filter aided by HRRP information and improved with GM weights.
Keywords	space-based radar ; space target tracking ; high-resolution range profile (HRRP) ; the geometrical theory of diffraction (GTD) model ; adapting Gaussian mixture (GM) weights ; merging threshold ; Science ; Q
Language	English
Publishing date	2023-10-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Calcium–Permeable Channels and Endothelial Dysfunction in Acute Lung Injury

Ying Hao / Zhuang Wang / Francis Frimpong / Xingjuan Chen

Current Issues in Molecular Biology, Vol 44, Iss 150, Pp 2217-

2022 Volume 2229

Abstract: The increased permeability of the lung microvascular endothelium is one critical initiation of acute lung injury (ALI). The disruption of vascular-endothelium integrity results in leakiness of the endothelial barrier and accumulation of protein-rich ... ...

Abstract	The increased permeability of the lung microvascular endothelium is one critical initiation of acute lung injury (ALI). The disruption of vascular-endothelium integrity results in leakiness of the endothelial barrier and accumulation of protein-rich fluid in the alveoli. During ALI, increased endothelial-cell (EC) permeability is always companied by high frequency and amplitude of cytosolic Ca 2+ oscillations. Mechanistically, cytosolic calcium oscillations include calcium release from internal stores and calcium entry via channels located in the cell membrane. Recently, numerous publications have shown substantial evidence that calcium-permeable channels play an important role in maintaining the integrity of the endothelium barrier function of the vessel wall in ALI. These novel endothelial signaling pathways are future targets for the treatment of lung injury. This short review focuses on the up-to-date research and provide insight into the contribution of calcium influx via ion channels to the disruption of lung microvascular endothelial-barrier function during ALI.
Keywords	calcium channels ; endothelial cells ; lung injury ; permeability ; Biology (General) ; QH301-705.5
Subject code	572
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Tool for Predicting College Student Career Decisions

Zhuang Wang / Guoxi Liang / Huiling Chen

Applied Sciences, Vol 12, Iss 4776, p

An Enhanced Support Vector Machine Framework

2022 Volume 4776

Abstract: The goal of this research is to offer an effective intelligent model for forecasting college students’ career decisions in order to give a useful reference for career decisions and policy formation by relevant departments. The suggested prediction model ... ...

Abstract	The goal of this research is to offer an effective intelligent model for forecasting college students’ career decisions in order to give a useful reference for career decisions and policy formation by relevant departments. The suggested prediction model is mainly based on a support vector machine (SVM) that has been modified using an enhanced butterfly optimization approach with a communication mechanism and Gaussian bare-bones mechanism (CBBOA). To get a better set of parameters and feature subsets, first, we added a communication mechanism to BOA to improve its global search capability and balance exploration and exploitation trends. Then, Gaussian bare-bones was added to increase the population diversity of BOA and its ability to jump out of the local optimum. The optimal SVM model (CBBOA-SVM) was then developed to predict the career decisions of college students based on the obtained parameters and feature subsets that are already optimized by CBBOA. In order to verify the effectiveness of CBBOA, we compared it with some advanced algorithms on all benchmark functions of CEC2014. Simulation results demonstrated that the performance of CBBOA is indeed more comprehensive. Meanwhile, comparisons between CBBOA-SVM and other machine learning approaches for career decision prediction were carried out, and the findings demonstrate that the provided CBBOA-SVM has better classification and more stable performance. As a result, it is plausible to conclude that the CBBOA-SVM is capable of being an effective tool for predicting college student career decisions.
Keywords	self-determination theory ; global optimization ; swarm intelligence ; college student career decisions ; support vector machine ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	006
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Predicting joint toxicity of chemicals by incorporating a weighted descriptor into a mixture model

Zhuang Wang / Fan Zhang / De-Gao Wang

Ecotoxicology and Environmental Safety, Vol 236, Iss , Pp 113472- (2022)

Cases for binary antibiotics and binary nanoparticles

2022

Abstract: A prediction method that integrated a mixture descriptor with an established mixture toxicology method was proposed for the joint toxicity of chemical pollutants. A weighted descriptor derived from the single descriptor of each component was employed to ... ...

Abstract	A prediction method that integrated a mixture descriptor with an established mixture toxicology method was proposed for the joint toxicity of chemical pollutants. A weighted descriptor derived from the single descriptor of each component was employed to calculate a mixture descriptor, which was successfully embedded into the generalized concentration addition (GCA) model named the extended GCA (XGCA) model. To develop and validate the proposed approach, binary antibiotic mixtures (ciprofloxacin and oxytetracycline) and metal-oxide (copper oxide and zinc oxide) nanoparticle mixtures were selected to study their toxicity to freshwater green algae. The results showed that concentration-response curve (CRC) derived from the XGCA model was closer to the observed CRC than those from the GCA, Concentration Addition (CA), and Independent Action (IA) models. The difference between effect concentrations predicted by the XGCA model and observed did not exceed a factor of 1.6. The XGCA model was relatively more accurate at predicting joint toxicity (in terms of effect concentrations and effect errors) than the reference models, independent of component types and mixture ratios. The XGCA model predicts the joint toxicity through molecular structural or nanostructural characters, thus modes of toxic action are not preconditions for predicting the toxicity of the mixtures. This result demonstrates the practicability of using the XGCA method in toxicity assessments of mixture pollutants with unknown modes of action.
Keywords	Combined pollution ; Mixture toxicity ; Concentration Addition ; Independent Action ; QSAR ; Environmental pollution ; TD172-193.5 ; Environmental sciences ; GE1-350
Subject code	590
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Practical Star Image Registration Algorithm Using Radial Module and Rotation Angle Features

Quan Sun / Lei Liu / Zhaodong Niu / Yabo Li / Jingyi Zhang / Zhuang Wang

Remote Sensing, Vol 15, Iss 21, p

2023 Volume 5146

Abstract: Star image registration is the most important step in the application of astronomical image differencing, stacking, and mosaicking, which requires high robustness, accuracy, and real-time capability on the part of the algorithm. At present, there are no ... ...

Abstract	Star image registration is the most important step in the application of astronomical image differencing, stacking, and mosaicking, which requires high robustness, accuracy, and real-time capability on the part of the algorithm. At present, there are no high-performance registration algorithms available in this field. In the present paper, we propose a star image registration algorithm that relies only on radial module features (RMF) and rotation angle features (RAF) while providing excellent robustness, high accuracy, and good real-time performance. The test results on a large amount of simulated and real data show that the comprehensive performance of the proposed algorithm is significantly better than the four classical baseline algorithms as judged by the presence of rotation, insufficient overlapping area, false stars, position deviation, magnitude deviation, and complex sky background, making it a more ideal star image registration algorithm than current alternatives.
Keywords	star image registration ; radial module feature ; rotation angle feature ; robustness ; real-time ; Science ; Q
Subject code	006
Language	English
Publishing date	2023-10-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Slope Stability and Effectiveness of Treatment Measures during Earthquake

Linlu Zhou / Lei Su / Zhuang Wang / Dongchun Zhu / Wei Shi / Xianzhang Ling

Sustainability, Vol 15, Iss 5309, p

2023 Volume 5309

Abstract: Slopes are prone to instability during earthquakes, which will cause geological disasters such as landslides and pose a great threat to people’s lives and property. Therefore, it is necessary to analyze the stability of slopes and the effectiveness of ... ...

Abstract	Slopes are prone to instability during earthquakes, which will cause geological disasters such as landslides and pose a great threat to people’s lives and property. Therefore, it is necessary to analyze the stability of slopes and the effectiveness of treatment measures during earthquakes. In this study, an actual slope in the creeping slide stage was selected and located in an area where earthquakes occur frequently. Once the slope experiences instability, it will produce great damage. Therefore, a finite difference program, Fast Lagrangian Analysis of Continua in Two Dimensions (FLAC2D), was employed in the numerical simulation to explore the stability of the slope before and after treatment under earthquake action. Different from previous studies, this study explores the effectiveness of various treatment measures on slope stability during earthquake. The computed results show that the stability of the slope is greatly influenced by earthquakes, and the slope displacement under seismic conditions is far larger than that under natural conditions. Three treatment measures, including excavation, anti-slide piles, and anchor cables, can significantly reduce slope displacement and the internal force on anti-slide piles, and improve the stability of a slope during an earthquake. This will provide a valuable reference for the strengthening strategies of unstable slopes. The analysis technique as well as the derived insights are of significance for slope stability and the effectiveness of treatment measures.
Keywords	earthquake ; slope stability ; treatment measures ; numerical simulation ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Refined 3D Solar Temperature Field and Effect Simulation of Ultra-High Steel Bridge Pylon

Yongjian Liu / Shi Han / Boxu Gong / Zhuang Wang / Jiang Liu / Zhenlong Shen

Applied Sciences, Vol 13, Iss 4400, p

2023 Volume 4400

Abstract: In order to accurately calculate the sunshine-induced temperature effect of an ultra-high bridge pylon, a refined numerical simulation model for the 3D bridge temperature field was established based on the proposed automatic sunshine shadow recognition ... ...

Abstract	In order to accurately calculate the sunshine-induced temperature effect of an ultra-high bridge pylon, a refined numerical simulation model for the 3D bridge temperature field was established based on the proposed automatic sunshine shadow recognition method and pylon-height-related convection modification method. A suspension bridge H-shaped pylon with a height of 280 m was taken as an example, and the temperature field and corresponding thermal stress and deformation were calculated under typical meteorological conditions in spring, summer, autumn, and winter. The results show that the maximum temperature differences between the outer surfaces of the pylon can reach 19 °C and 16 °C for north–south walls and east–west walls, respectively, and exceed the recommended value of ±5 °C in the Chinese Specification. The maximum displacements can reach 370 mm and 110 mm at the top of the bridge pylon in the longitudinal and transverse directions of the bridge, respectively. After the modification of the convective coefficient of the outer surfaces with different wind speeds at different pylon heights, the temperature gradually decreased from the top to the bottom of the pylon, with a temperature difference of 8 °C. The significant influence of the sunshine shadow was shown on the temperature field and temperature effect of the bridge pylon. By considering the shadow effect, the maximum temperature difference can reach 12 °C between adjacent sunlit and shaded areas and can reach 14 °C between two pylon columns. A significant mutation of thermal stress existed in the shaded area, and the maximum stress could be reduced by 13 MPa compared with the adjacent sunlit area. Obvious asynchronous deformation was shown between two pylon columns, and the maximum asynchronous displacement at the top of the pylon can reach 18 mm and 45 mm in the longitudinal and transverse directions, respectively.
Keywords	bridge engineering ; ultra-high steel bridge pylon ; 3D solar temperature field ; thermal effect ; refined simulation ; shadow recognition ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	600
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A pretrained proximal policy optimization algorithm with reward shaping for aircraft guidance to a moving destination in three-dimensional continuous space

Zhuang Wang / Hui Li / Zhaoxin Wu / Haolin Wu

International Journal of Advanced Robotic Systems, Vol

2021 Volume 18

Abstract: To enhance the performance of guiding an aircraft to a moving destination in a certain direction in three-dimensional continuous space, it is essential to develop an efficient intelligent algorithm. In this article, a pretrained proximal policy ... ...

Abstract	To enhance the performance of guiding an aircraft to a moving destination in a certain direction in three-dimensional continuous space, it is essential to develop an efficient intelligent algorithm. In this article, a pretrained proximal policy optimization (PPO) with reward shaping algorithm, which does not require an accurate model, is proposed to solve the guidance problem of manned aircraft and unmanned aerial vehicles. Continuous action reward function and position reward function are presented, by which the training speed is increased and the performance of the generated trajectory is improved. Using pretrained PPO, a new agent can be trained efficiently for a new task. A reinforcement learning framework is built, in which an agent can be trained to generate a reference trajectory or a series of guidance instructions. General simulation results show that the proposed method can significantly improve the training efficiency and trajectory performance. The carrier-based aircraft approach simulation is carried out to prove the application value of the proposed approach.
Keywords	Electronics ; TK7800-8360 ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	629
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	SAGE Publishing
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Machine learning-driven QSAR models for predicting the mixture toxicity of nanoparticles

Fan Zhang / Zhuang Wang / Willie J.G.M. Peijnenburg / Martina G. Vijver

Environment International, Vol 177, Iss , Pp 108025- (2023)

2023

Abstract: Research on theoretical prediction methods for the mixture toxicity of engineered nanoparticles (ENPs) faces significant challenges. The application of in silico methods based on machine learning is emerging as an effective strategy to address the ... ...

Abstract	Research on theoretical prediction methods for the mixture toxicity of engineered nanoparticles (ENPs) faces significant challenges. The application of in silico methods based on machine learning is emerging as an effective strategy to address the toxicity prediction of chemical mixtures. Herein, we combined toxicity data generated in our lab with experimental data reported in the literature to predict the combined toxicity of seven metallic ENPs for Escherichia coli at different mixing ratios (22 binary combinations). We thereafter applied two machine learning (ML) techniques, support vector machine (SVM) and neural network (NN), and compared the differences in the ability to predict the combined toxicity by means of the ML-based methods and two component-based mixture models: independent action and concentration addition. Among 72 developed quantitative structure–activity relationship (QSAR) models by the ML methods, two SVM-QSAR models and two NN-QSAR models showed good performance. Moreover, an NN-based QSAR model combined with two molecular descriptors, namely enthalpy of formation of a gaseous cation and metal oxide standard molar enthalpy of formation, showed the best predictive power for the internal dataset (R2test = 0.911, adjusted R2test = 0.733, RMSEtest = 0.091, and MAEtest = 0.067) and for the combination of internal and external datasets (R2test = 0.908, adjusted R2test = 0.871, RMSEtest = 0.255, and MAEtest = 0.181). In addition, the developed QSAR models performed better than the component-based models. The estimation of the applicability domain of the selected QSAR models showed that all the binary mixtures in training and test sets were in the applicability domain. This study approach could provide a methodological and theoretical basis for the ecological risk assessment of mixtures of ENPs.
Keywords	Nanotoxicity ; Advanced nanomaterials ; Support vector machine ; Neural network ; Mixture toxicity ; Environmental sciences ; GE1-350
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Combined Toxicity of TiO 2 Nanospherical Particles and TiO 2 Nanotubes to Two Microalgae with Different Morphology

Zhuang Wang / Shiguang Jin / Fan Zhang / Degao Wang

Nanomaterials, Vol 10, Iss 2559, p

2020 Volume 2559

Abstract: The joint activity of multiple engineered nanoparticles (ENPs) has attracted much attention in recent years. Many previous studies have focused on the combined toxicity of different ENPs with nanostructures of the same dimension. However, the mixture ... ...

Abstract	The joint activity of multiple engineered nanoparticles (ENPs) has attracted much attention in recent years. Many previous studies have focused on the combined toxicity of different ENPs with nanostructures of the same dimension. However, the mixture toxicity of multiple ENPs with different dimensions is much less understood. Herein, we investigated the toxicity of the binary mixture of TiO 2 nanospherical particles (NPs) and TiO 2 nanotubes (NTs) to two freshwater algae with different morphology, namely, Scenedesmus obliquus and Chlorella pyrenoidosa . The physicochemical properties, dispersion stability, and the generation of reactive oxygen species (ROS) were determined in the single and binary systems. Classical approaches to assessing mixture toxicity were applied to evaluate and predict the toxicity of the binary mixtures. The results show that the combined toxicity of TiO 2 NPs and NTs to S. obliquus was between the single toxicity of TiO 2 NTs and NPs, while the combined toxicity to C. pyrenoidosa was higher than their single toxicity. Moreover, the toxicity of the binary mixtures to C. pyrenoidosa was higher than that to S. obliquus. A toxic unit assessment showed that the effects of TiO 2 NPs and NTs were additive to the algae. The combined toxicity to S. obliquus and C. pyrenoidosa can be effectively predicted by the concentration addition model and the independent action model, respectively. The mechanism of the toxicity caused by the binary mixtures of TiO 2 NPs and NTs may be associated with the dispersion stability of the nanoparticles in aquatic media and the ROS-induced oxidative stress effects. Our results may offer a new insight into evaluating and predicting the combined toxicological effects of ENPs with different dimensions and of probing the mechanisms involved in their joint toxicity.
Keywords	TiO 2 nanoparticles ; TiO 2 nanotubes ; nanotoxicity ; freshwater algae ; oxidative damage ; Chemistry ; QD1-999
Subject code	590
Language	English
Publishing date	2020-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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