Article
Biophysics
Jun-Hee Park, Ga-Yeon Lee, Zhiquan Song, Ji-Hong Bong, Young Wook Chang, Sungbo Cho, Min-Jung Kang, Jae-Chul Pyun
Summary: Vertically paired electrodes (VPEs) with multiple electrode pairs were developed to enhance capacitive measurements. The sensitivity was improved by optimizing the electrode gap and number of electrode pairs. A conductive polymer layer was used for electrode fabrication, and the sensitivity enhancement was verified through modeling and experiments. The VPEs were successfully applied for SARS-CoV-2 nucleoprotein detection.
BIOSENSORS & BIOELECTRONICS
(2022)
Article
Chemistry, Analytical
Shaoyu Kang, Mohamed Sharafeldin, Sophie C. Patrick, Xuanxiao Chen, Jason J. Davis
Summary: We present a simple method for quantifying target proteins by monitoring the redox capacitance of a conductive polymer interface. This method allows real-time analysis of both association and dissociation regimes and can detect target proteins at picomolar levels within 15 seconds. This proof-of-principle methodology is expected to be widely applicable in quantifying other clinically relevant targets.
ANALYTICAL CHEMISTRY
(2023)
Article
Engineering, Chemical
Niklas Koeller, Lukas Mankertz, Selina Finger, Christian J. Linnartz, Matthias Wessling
Summary: This study presents a methodology to scale up Flow-electrode Capacitive Deionization (FCDI) technology from lab-scale to pilot-scale systems. By increasing membrane area and using a stacking approach, the FCDI modules were successfully scaled up and achieved a salt transfer rate comparable to lab-scale systems. This provides a foundation for future assessments of energy demand and economics.
Review
Engineering, Chemical
Jie Ma, Chunxiao Zhai, Fei Yu
Summary: Flow-electrode capacitive deionization (FCDI) technology overcomes the limitations of traditional CDI technology by combining flow electrodes and ion exchange membranes. Extensive research over the past decade has led to positive progress in FCDI technology, including charge transport theory, material development, and engineering applications, showing promising potential.
Article
Chemistry, Multidisciplinary
Lanfang Wang, Ruifang Ding, Yanqing Hao, Yujia Li, Wenjiao Liu, Wenbo Lu, Xiaohong Xu
Summary: A novel light-driven non-enzymatic glucose sensor based on AuNi nanodendrites has been successfully developed. The nanodendritic structure provides a large surface area and excellent electron transfer for glucose oxidation. Under visible light illumination, this hierarchical hybrid structure exhibits remarkable photoelectrocatalytic activity.
NEW JOURNAL OF CHEMISTRY
(2023)
Article
Engineering, Environmental
Hahnsoll Rhee, Rhokyun Kwak
Summary: Exposure of a conducting porous material to an electric field in electrolytes induces an electric dipole, resulting in capacitive charging of cations and anions at opposite poles. A novel desalination method using this induced-charge capacitive deionization (IC-CDI) is investigated, and a microscale IC-CDI platform is devised to study ion transport dynamics and desalination performances compared to conventional CDI.
Article
Chemistry, Analytical
Sarah T. R. Brandao, Adriano dos Santos, Paulo R. Bueno, Eduardo M. Cilli
Summary: Redox-active moieties assembled on metallic interfaces follow quantum mechanical rules, with the quantum capacitance of the interface playing a key role in electron transfer dynamics. Modifying these interfaces with biological receptors has advantages for miniaturized electroanalytical devices, and using peptide-based redox-active moieties has shown promising results. In this work, different ferrocene-tagged peptide structures were used to form self-assembled monolayers on gold for electroanalytical assays, with the Gly-peptide structure showing the best performance for sensing the NS1 DENV biomarker. The study highlights the importance of surface chemistry in sensing interfaces and the advantages of using peptides as biosensor components.
ANALYTICAL CHEMISTRY
(2023)
Article
Engineering, Electrical & Electronic
Xin He, Zhihao Liu, Gengzhe Shen, Xiang He, Jionghong Liang, Yu Zhong, Tianlong Liang, Jie He, Yue Xin, Chi Zhang, Dongdong Ye, Guofa Cai
Summary: The pressure sensor developed based on MXene/Ag NWs composite electrodes and micro-structured dielectric layer shows high sensitivity, fast response, wide detection range, and long-term stability. It is capable of detecting various human activities and has promising application prospects in wearable and flexible electronic devices.
NPJ FLEXIBLE ELECTRONICS
(2021)
Article
Engineering, Electrical & Electronic
Charn Loong Ng, Mamun Bin Ibne Reaz, Maria Liz Crespo, Andres Cicuttin, Mohd Ibrahim Bin Shapiai, Sawal Hamid Bin Md Ali, Noorfazila Binti Kamal, Muhammad Enamul Hoque Chowdhury
Summary: Musculoskeletal diseases have a negative impact on personal health and the global economy. Wearable sensing technology, specifically the capacitive EMG biomedical sensor introduced in this research, can improve the efficiency of public healthcare strategies to combat these diseases. The sensor's flexibility, miniaturization, and durability make it suitable for standalone adhesive use or integration into wearable applications.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Review
Engineering, Chemical
Fei Yu, Zhengqu Yang, Yujuan Cheng, Siyang Xing, Yayi Wang, Jie Ma
Summary: This review summarizes the advantages of flow-electrode capacitive deionization (FCDI), focusing on the progress of FCDI research in terms of cell structure design, operating mode, flow phase component, and environmental applications. Possible challenges of current FCDI technology are presented, along with outlining the future direction of FCDI.
SEPARATION AND PURIFICATION TECHNOLOGY
(2022)
Article
Electrochemistry
Anis Allagui, Hachemi Benaoum
Summary: Porous electrodes made of hierarchically nanostructured materials are widely used in electrochemical energy technologies. Modeling the macroscopic transport and relaxation in these electrodes is important, but challenging due to their complex microscopic structure. Discharge response of these electrodes does not follow the traditional exponential decay observed in flat electrodes, instead requiring differential equations with non-integer derivatives.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2022)
Review
Engineering, Chemical
Ming Gao, Zhiqian Yang, Wencui Liang, Tianqi Ao, Wenqing Chen
Summary: In recent years, the development of advanced freestanding pseudocapacitive electrode materials with controlled topography, structural complexity, and improved desalination performance has attracted significant interest. This paper presents a comprehensive review of recent advancements in the rational design of freestanding electrodes for hybrid capacitive deionization (CDI) to enhance their desalination capacity, stability, and selectivity. The review summarizes advanced electrode materials and discusses various synthetic strategies to improve CDI performance. It also categorizes electrode materials into different structures and discusses the applicability of CDI in various industrial processes.
SEPARATION AND PURIFICATION TECHNOLOGY
(2023)
Review
Chemistry, Multidisciplinary
Sushil Kumar, Najat Maher Aldaqqa, Emad Alhseinat, Dinesh Shetty
Summary: In recent years, capacitive deionization (CDI) has emerged as a promising desalination technique for converting sea and wastewater into potable water due to its energy efficiency and eco-friendly nature. However, its low salt removal capacity and parasitic reactions have limited its effectiveness. To address these issues, the development of porous carbon nanomaterials as electrode materials and the proposal of membrane capacitive deionization (mCDI) have been explored. This review discusses fabrication techniques and experimental parameters used to evaluate the desalination performance of different materials, providing an overview of improvements made for CDI and mCDI desalination purposes.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2023)
Article
Nanoscience & Nanotechnology
Qinghao Wu, Dawei Liang, Shanfu Lu, Jin Zhang, Haining Wang, Yan Xiang, Doron Aurbach
Summary: The study demonstrates a simple and cost-effective method for fabricating high-CE electrodes for desalination through applying a thin layer of inorganic ion-exchange material on activated carbon electrodes.
ACS APPLIED MATERIALS & INTERFACES
(2021)
Article
Chemistry, Analytical
Andreia S. P. Sousa, Andreia Noites, Rui Vilarinho, Rubim Santos
Summary: This study observed the evolution of electrode-skin interface impedance of surface EMG electrodes over time. The results showed a decrease in impedance values from minute 5 to minute 15, followed by stabilization till minute 50. These findings have important implications for the methods and data analysis of EMG studies.
Article
Chemistry, Analytical
Md Shafayet Hossain, Muhammad E. H. Chowdhury, Mamun Bin Ibne Reaz, Sawal Hamid Md Ali, Ahmad Ashrif A. Bakar, Serkan Kiranyaz, Amith Khandakar, Mohammed Alhatou, Rumana Habib, Muhammad Maqsud Hossain
Article
Mathematical & Computational Biology
Fahmida Haque, Mamun B. I. Reaz, Muhammad E. H. Chowdhury, Serkan Kiranyaz, Sawal H. M. Ali, Mohammed Alhatou, Rumana Habib, Ahmad A. A. Bakar, Norhana Arsad, Geetika Srivastava
Summary: This study explored the use of machine learning models in the diagnosis of diabetic sensorimotor polyneuropathy (DSPN). The results showed that the ensemble classifier and random forest model performed well in diagnosing DSPN using nerve conduction studies data, and can enhance the management of DSPN patients.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2022)
Article
Chemistry, Analytical
Amith Khandakar, Sakib Mahmud, Muhammad E. H. Chowdhury, Mamun Bin Ibne Reaz, Serkan Kiranyaz, Zaid Bin Mahbub, Sawal Hamid Md Ali, Ahmad Ashrif A. Bakar, Mohamed Arselene Ayari, Mohammed Alhatou, Mohammed Abdul-Moniem, Md Ahasan Atick Faisal
Summary: An intelligent insole system is designed to monitor individuals' foot pressure and temperature in real-time. It utilizes off-the-shelf sensors to detect plantar pressure and temperature, and data can be wirelessly transmitted to a centralized device for storage. The research aims to create an affordable, practical, and portable foot monitoring system for continuous at-home monitoring of foot problems and early detection of diabetic foot complications.
Review
Computer Science, Artificial Intelligence
Kh Shahriya Zaman, Mamun Bin Ibne Reaz, Sawal Hamid Md Ali, Ahmad Ashrif A. Bakar, Muhammad Enamul Hoque Chowdhury
Summary: Recent advancements in deep learning applications have prompted researchers to reconsider hardware architecture to meet the demands of fast and efficient application-specific computations. The emergence of specialized DL processors has reduced reliance on cloud servers, improved privacy, reduced latency, and alleviated bandwidth congestion. As researchers explore various application-specific hardware architectures, new technologies and design considerations are being developed to enhance the performance and efficiency of DL tasks.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Health Care Sciences & Services
Nakib Hayat Chowdhury, Mamun Bin Ibne Reaz, Sawal Hamid Md Ali, Shamim Ahmad, Maria Liz Crespo, Andres Cicuttin, Fahmida Haque, Ahmad Ashrif A. Bakar, Mohammad Arif Sobhan Bhuiyan
Summary: This study aimed to develop a prediction model and nomogram for detecting CKD in T1DM patients early using routine checkup data. By utilizing multiple feature ranking algorithms and logistic regression analysis, a predictive model for CKD in T1DM patients was successfully developed and showed excellent performance.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Article
Engineering, Electrical & Electronic
Amith Khandakar, Muhammad E. H. Chowdhury, Mamun Bin Ibne Reaz, Serkan Kiranyaz, Anwarul Hasan, Tawsifur Rahman, Sawal Hamid Md. Ali, Mohd Ibrahim bin Shapiai Abd Razak, Ahmad Ashrif A. Bakar, Kanchon Kanti Podder, Moajjem Hossain Chowdhury, Md. Ahasan Atick Faisal, Rayaz A. Malik
Summary: Diabetic sensorimotor polyneuropathy (DSPN) can result in pain, diabetic foot ulceration (DFU), amputation, and death. This study proposes a robust machine-learning approach called DSPNet to identify patients with severe DSPN using standing foot temperature maps. The study achieved an F1 score of 90.3% and outperformed current deep-learning network methods, indicating the effectiveness of temperature maps in detecting high-risk DFU patients and identifying severe DSPN patients. Such sensors can be easily incorporated into smart insoles.
IEEE SENSORS JOURNAL
(2023)
Article
Medicine, General & Internal
Fahmida Haque, Mamun B. I. Reaz, Muhammad E. H. Chowdhury, Mohd Ibrahim bin Shapiai, Rayaz S. A. Malik, Mohammed Alhatou, Syoji Kobashi, Iffat Ara, Sawal H. M. Ali, Ahmad A. A. Bakar, Mohammad Arif Sobhan Bhuiyan
Summary: Diabetic sensorimotor polyneuropathy (DSPN) is a serious complication of diabetes that can lead to foot ulceration and amputation. The Michigan neuropathy screening instrument (MNSI) is commonly used for screening DSPN but lacks a measure of severity. In this study, a DSPN severity grading system based on machine learning algorithms was developed using longitudinal data from the EDIC trial. The system utilizes the top seven MNSI features, including vibration perception, filament test, previous neuropathy, callus, deformities, and fissure, to detect DSPN severity. The developed nomogram showed high accuracy in predicting DSPN and can be used to determine prognosis in patients with DSPN.
Article
Biotechnology & Applied Microbiology
Moajjem Hossain Chowdhury, Md Nazmul Islam Shuzan, Muhammad E. H. Chowdhury, Mamun Bin Ibne Reaz, Sakib Mahmud, Nasser Al Emadi, Mohamed Arselene Ayari, Sawal Hamid Md Ali, Ahmad Ashrif A. Bakar, Syed Mahfuzur Rahman, Amith Khandakar
Summary: This paper proposes a deep-learning-based solution to estimate RR directly from the PPG signal, providing a new method for monitoring respiratory ailments. The lightweight model outperforms other deep neural networks and shows promising results on different datasets. It can be deployed to mobile devices for real-time monitoring.
BIOENGINEERING-BASEL
(2022)
Article
Biotechnology & Applied Microbiology
Md Shafayet Hossain, Sakib Mahmud, Amith Khandakar, Nasser Al-Emadi, Farhana Ahmed Chowdhury, Zaid Bin Mahbub, Mamun Bin Ibne Reaz, Muhammad E. H. Chowdhury
Summary: This paper proposes a novel one-dimensional convolutional neural network (1D-CNN) called MultiResUNet3+ to remove physiological artifacts from electroencephalogram (EEG) signals. A publicly available dataset is used to train, validate, and test the proposed model along with four other 1D-CNN models. The results show that MultiResUNet3+ achieves the highest reduction in EOG and EMG artifacts compared to the other models.
BIOENGINEERING-BASEL
(2023)
Review
Medicine, General & Internal
Khandaker Reajul Islam, Johayra Prithula, Jaya Kumar, Toh Leong Tan, Mamun Bin Ibne Reaz, Md. Shaheenur Islam Sumon, Muhammad E. H. Chowdhury
Summary: This systematic review examines the application of machine learning and deep learning in predicting sepsis using electronic health records. The study highlights the importance of these methods in early sepsis detection and improving patient outcomes.
JOURNAL OF CLINICAL MEDICINE
(2023)
Article
Engineering, Electrical & Electronic
Charn Loong Ng, Mamun Bin Ibne Reaz, Maria Liz Crespo, Andres Cicuttin, Mohd Ibrahim Bin Shapiai, Sawal Hamid Bin Md Ali, Noorfazila Binti Kamal, Muhammad Enamul Hoque Chowdhury
Summary: Musculoskeletal diseases have a negative impact on personal health and the global economy. Wearable sensing technology, specifically the capacitive EMG biomedical sensor introduced in this research, can improve the efficiency of public healthcare strategies to combat these diseases. The sensor's flexibility, miniaturization, and durability make it suitable for standalone adhesive use or integration into wearable applications.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Md. Johirul Islam, Shamim Ahmad, Fahmida Haque, Mamun Bin Ibne Reaz, Mohammad Arif Sobhan Bhuiyan, Md. Rezaul Islam
Summary: Surface electromyography (EMG) is a promising signal for hand movement recognition. However, subject-dependent EMG pattern recognition limits its use for different subjects. This study proposes a subject invariant EMG pattern recognition method by extracting subject invariant features and using spectral regression discriminant analysis (SRDA) for dimensionality reduction. The proposed method achieves high F1 scores and outperforms subject independent and subject-dependent methods, while being simple, classifier independent, and time complexity free.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Chemistry, Analytical
Fahmida Haque, Mamun Bin Ibne Reaz, Muhammad Enamul Hoque Chowdhury, Maymouna Ezeddin, Serkan Kiranyaz, Mohammed Alhatou, Sawal Hamid Md Ali, Ahmad Ashrif A. Bakar, Geetika Srivastava
Summary: This study proposes the use of machine learning techniques to identify DN and DFU patients using EMG and GRF data. The KNN algorithm performed well in identifying DN and DFU, achieving high accuracy when optimized.
Article
Computer Science, Information Systems
Md Johirul Islam, Shamim Ahmad, Fahmida Haque, Mamun Bin Ibne Reaz, Mohammad A. S. Bhuiyan, Md Rezaul Islam
Summary: This study proposes a feature selection method for improving electromyogram pattern recognition in prosthetic hands. The selected features achieve significant improvements in accuracy and F1 score, and the method achieves forearm orientation and muscle force invariant performance in training the classifier.
Article
Computer Science, Information Systems
Md Shafayet Hossain, Mamun Bin Ibne Reaz, Muhammad E. H. Chowdhury, Sawal H. M. Ali, Ahmad Ashrif A. Bakar, Serkan Kiranyaz, Amith Khandakar, Mohammed Alhatou, Rumana Habib
Summary: Physiological signal measurement and processing are gaining popularity in ambulatory settings. This paper proposes three novel multiresolution analysis techniques for motion artifact correction from EEG and fNIRS signals. The results show that these methods outperform existing techniques in denoising performance.
Article
Engineering, Multidisciplinary
Sicheng Jiao, Shixiang Wang, Minge Gao, Min Xu
Summary: This paper presents a non-contact method of thickness measurement for thin-walled rotary shell parts based on a chromatic confocal sensor. The method involves using a flip method to obtain surface profiles from both sides of the workpiece, measuring the decentration and tilt errors of the workpiece using a centering system, establishing a unified reference coordinate system, reconstructing the external and internal surface profiles, and calculating the thickness. Experimental results show that the method can accurately measure the thickness of a sapphire spherical shell workpiece and is consistent with measurements of other materials.
Article
Engineering, Multidisciplinary
Rajeev Kumar, Sajal Agarwal, Sarika Pal, Alka Verma, Yogendra Kumar Prajapati
Summary: This study evaluated the performance of a CaF2-Ag-MXene-based surface plasmon resonance (SPR) sensor at different wavelengths. The results showed that the sensor achieved the maximum sensitivity at a wavelength of 532 nm, and higher sensitivities were obtained at shorter wavelengths at the expense of detection accuracy.
Article
Engineering, Multidisciplinary
Attilio Di Nisio, Gregorio Andria, Francesco Adamo, Daniel Lotano, Filippo Attivissimo
Summary: Capacitive sensing is a widely used technique for a variety of applications, including avionics. However, current industry standard Capacitive Level Sensors (CLSs) used in helicopters perform poorly in terms of sensitivity and dynamic characteristics. In this study, novel geometries were explored and three prototypes were built and tested. Experimental validation showed that the new design featuring a helicoidal slit along the external electrode of the cylindrical probe improved sensitivity, response time, and linearity.
Article
Engineering, Multidisciplinary
Kai Yang, Huiqin Wang, Ke Wang, Fengchen Chen
Summary: This paper proposes an effective measurement method for dynamic compaction construction based on time series model, which enables real-time monitoring and measurement of anomalies and important construction parameters through simulating motion state transformation and running time estimation.
Article
Engineering, Multidisciplinary
Hui Fu, Qinghua Song, Jixiang Gong, Liping Jiang, Zhanqiang Liu, Qiang Luan, Hongsheng Wang
Summary: An automatic detection and pixel-level quantification model based on joint Mask R-CNN and TransUNet is developed to accurately evaluate microcrack damage on the grinding surfaces of engineering ceramics. The model is effectively trained on actual micrograph image dataset using a joint training strategy. The proposed model achieves reliable automatic detection and fine segmentation of microcracks, and a skeleton-based quantification model is also proposed to provide comprehensive and precise measurements of microcrack size.
Review
Engineering, Multidisciplinary
Sang Yeob Kim, Da Yun Kwon, Arum Jang, Young K. Ju, Jong-Sub Lee, Seungkwan Hong
Summary: This paper reviews the categorization and applications of UAV sensors in forensic engineering, with a focus on geotechnical, structural, and water infrastructure fields. It discusses the advantages and disadvantages of sensors with different wavelengths and addresses the challenges of current UAV technology and recommendations for further research in forensic engineering.
Article
Engineering, Multidisciplinary
Anton Nunez-Seoane, Joaquin Martinez-Sanchez, Erik Rua, Pedro Arias
Summary: This article compares the use of Mobile Laser Scanners (MLS) and Aerial Laser Scanners (ALS) for digitizing the road environment and detecting road slopes. The study found that ALS data and its corresponding algorithm achieved better detection and delimitation results compared to MLS. Measuring the road from a terrestrial perspective negatively impacted the detection process, while an aerial perspective allowed for scanning of the entire slope structure.
Article
Engineering, Multidisciplinary
Nur Luqman Saleh, Aduwati Sali, Raja Syamsul Azmir Raja Abdullah, Sharifah M. Syed Ahmad, Jiun Terng Liew, Fazirulhisyam Hashim, Fairuz Abdullah, Nur Emileen Abdul Rashid
Summary: This study introduces an enhanced signal processing scheme for detecting mouth-click signals used by blind individuals. By utilizing additional band-pass filtering and other steps, the detection accuracy is improved. Experimental results using artificial signal data showed a 100% success rate in detecting obstacles. The emerging concepts in this research are expected to benefit radar and sonar system applications.
Article
Engineering, Multidisciplinary
Jiqiang Tang, Shengjie Qiu, Lu Zhang, Jinji Sun, Xinxiu Zhou
Summary: This paper studies the magnetic noise level of a compact high-performance magnetically shielded room (MSR) under different operational conditions and establishes a quantitative model for magnetic noise calculation. Verification experiments show the effectiveness of the proposed method.
Review
Engineering, Multidisciplinary
Krzysztof Bartnik, Marcin Koba, Mateusz Smietana
Summary: The demand for miniaturized sensors in the biomedical industry is increasing, and optical fiber sensors (OFSs) are gaining popularity due to their small size, flexibility, and biocompatibility. This study reviews various OFS designs tested in vivo and identifies future perspectives and challenges for OFS technology development from a user perspective.
Article
Engineering, Multidisciplinary
Yue Wang, Lei Zhou, Zihao Li, Jun Wang, Xuangou Wu, Xiangjun Wang, Lei Hu
Summary: This paper presents a 3-D reconstruction method for dynamic stereo vision of metal surface based on line structured light, overcoming the limitation of the measurement range of static stereo vision. The proposed method uses joint calibration and global optimization to accurately reconstruct the 3-D coordinates of the line structured light fringe, improving the reconstruction accuracy.
Article
Engineering, Multidisciplinary
Jaafar Alsalaet
Summary: Order tracking analysis is an effective tool for machinery fault diagnosis and operational modal analysis. This study presents a new formulation for the data equation of the second-generation Vold-Kalman filter, using separated cosine and sine kernels to minimize error and provide smoother envelopes. The proposed method achieves high accuracy even with small weighting factors.
Article
Engineering, Multidisciplinary
Tonglei Cao, Kechen Song, Likun Xu, Hu Feng, Yunhui Yan, Jingbo Guo
Summary: This study constructs a high-resolution dataset for surface defects in ceramic tiles and addresses the scale and quantity differences in defect distribution. An improved approach is proposed by introducing a content-aware feature recombination method and a dynamic attention mechanism. Experimental results demonstrate the superior accuracy and efficiency of the proposed method.
Article
Engineering, Multidisciplinary
Qinghong Fu, Yunxi Lou, Jianghui Deng, Xin Qiu, Xianhua Chen
Summary: Measurement and quantitative characterization of aging-induced gradient properties is crucial for accurate analysis and design of asphalt pavement. This research proposes the composite specimen method to obtain asphalt binders at different depths within the mixture and uses dynamic shear rheometer tests to measure aging-induced gradient properties and reveal internal mechanisms. G* master curves are constructed to investigate gradient aging effects in a wide range. The study finds that the composite specimen method can effectively restore the boundary conditions and that it is feasible to study gradient aging characteristics within the asphalt mixture. The study also observes variations in G* and delta values and the depth range of gradient aging effects for different aging levels.
Article
Engineering, Multidisciplinary
Min Li, Kai Wei, Tianhe Xu, Yali Shi, Dixing Wang
Summary: Due to the limitations of ground monitoring stations in China for the BDS, the accuracy of BDS Medium Earth Orbit (MEO) satellite orbits can be influenced. To overcome this, low Earth orbit (LEO) satellites can be used as additional monitoring stations. In this study, data from two LEO satellites were collected to improve the precise orbit determination of the BDS. By comparing the results with GPS and BDS-2/3 solutions, it was found that including the LEO satellites significantly improved the accuracy of GPS and BDS-2/3 orbits.
