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1,006 results on '"Chen, Weibin"'

221. Multi-objective optimization of a new special-shaped tube for heating deicing fluid

Author

Yunpeng Li, Yue Xianqu, Qi Nie, Zhang Yue, Chen Weibin, and Wu Mengli

Subjects
Physics, Computer simulation, Turbulence, Mathematical analysis, 02 engineering and technology, 021001 nanoscience & nanotechnology, Condensed Matter Physics, 01 natural sciences, Multi-objective optimization, Nusselt number, Deicing fluid, 010406 physical chemistry, 0104 chemical sciences, Base (group theory), Sensitivity (control systems), Physical and Theoretical Chemistry, 0210 nano-technology, Dimensionless quantity
Abstract

The ground deicing heating system is an important equipment to ensure flight safety of civil aircraft in winter. As the main element, the heating tube directly affects the working efficiency of the system. The deicing fluid is high viscosity mixture. To improve heating efficiency of deicing fluid, a new special-shaped tube is proposed, which is named double-spiral trapezoidal grooved tube. The upper base width (m), groove depth (h) and base angle (θ) are the important structural parameters of the new tube. The optimal Latin hypercube design is applied to carry out the experiment design of m, h and θ. Nusselt number (Nu), flow resistance coefficient (f) and performance evaluation criteria (PEC) are selected as the optimization objectives. Then, the response surface approximation model is established to conduct sensitivity analysis. Based on the model, NCGA and NSGA-II algorithms are, respectively, introduced to perform the multi-objective optimization. The results show that NSGA-II is better than NCGA. When $$m \in \left[ {0.17, \, 0.33} \right]$$ , $$h \in [1.06, \, 1.08]$$ and $$\theta \in \left[ {84.06, \, 84.75} \right]$$ , the best range of optimization objectives is $$Nu \in \left[ {86.04, \, 87.81} \right]$$ , $$f \in \left[ {0.70, \, 0.73} \right]$$ and $${\text{PEC}} \in \left[ {1.60, \, 1.62} \right]$$ . With the growth of turbulence intensity, PEC > 1, and Nu increases by 4–27%. As a result, the heating efficiency of the new tube is superior to the original tube.

Published
2019

233. Distinct storage mechanisms of soil organic carbon in coniferous forest and evergreen broadleaf forest in tropical China

Author

Su, Fanglong, Xu, Shan, Sayer, Emma, Chen, Weibin, Du, Yue, Lu, Xiankai, Su, Fanglong, Xu, Shan, Sayer, Emma, Chen, Weibin, Du, Yue, and Lu, Xiankai

Abstract

The impact of human activities on soil carbon (C) storage in tropical forests has aroused wide concern during the past decades, because these ecosystems play a key role in ameliorating global climate change. However, there remain uncertainties about how land-use history alters soil organic carbon (SOC) stability and storage in different forests. In this study, we measured the C content and mass distributions of soil aggregates, density fractions, mineral-bound C and microbial biomass C in the organic horizon, 0-10 cm and 10-20 cm soil layers in coniferous forest and evergreen broadleaf forest at Dinghushan Biosphere Reserve in tropical China. The broadleaf forest had larger SOC stocks than the coniferous forest, but the proportion of SOC stored in different density fractions at 0-10 cm soils was similar between forest types, while a greater proportion of SOC was stored in microaggregates in the coniferous forest. Most of the SOC was held as light fraction C in the organic horizon in the coniferous forest, whereas the concentrations of mineral-bound C were higher in the broadleaf forest. These findings indicate clear differences in the protection of SOC between broadleaf and coniferous forests growing on the same soil type. We propose that historic conversion of broadleaf forest to coniferous forest has reduced soil C sequestration capacity by altering the diversity and quality of plant inputs to the soil, which in turn affected macroaggregate formation, soil chemical properties and microbial biomass. Our results thus demonstrate that changes in forest tree species composition could have long-lasting effects on soil structure and carbon storage, providing crucial evidence for policy decisions on forest carbon sink management.

Published
2021

235. Development of a Graphene-Based Wireless Displacement Transducer

Author

Hong, Chengyu, Yang, Qiang, Chen, Weibin, Yuan, Shu, Zhao, Xin, and Ding, Xianbo

Abstract

Graphene-based sensors have drawn significant attention in the field of monitoring due to their excellent mechanical and electrical properties. In this study, an innovative graphene wireless displacement transducer was developed. This displacement transducer consists of two components: a processing unit characterized by the features of low cost, low latency, and low power consumption, and a sensing unit composed of a graphene-based displacement sensor with the advantages of simplification, a large measurement range, and high durability. The structural design of the graphene-based displacement sensor was realized using 3-D printing technology. A series of calibration experiments were carried out to evaluate the measurement performance of the displacement transducer. Measurement results of calibration experiments indicate that the measurement sensitivity and static error were 29.6 $\text{k}\Omega $ /mm and 7.62%, respectively. The maximum measurement range was 0–90 mm. The obtained maximum resistance difference of the graphene sensor is less than 4.5% under the cyclic test, indicating that the sensor has excellent stability. The displacement transducer is expected to apply for structural health monitoring of infrastructures such as crack monitoring and relative movement measurement.

Published
2023
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236. Adaptive Power Sharing and Switching Frequency Control for Power Loss Optimization in WBG/Si Hybrid Half-Bridge Converters

Author

Zhang, Chao, Yuan, Xufeng, Wang, Jun, Chen, Weibin, Hu, Bo, and Shen, Zheng John

Abstract

The optimization of switching frequencies and the power-sharing ratio between the silicon (Si) phase and wide-bandgap (WBG) phase are critically important for the efficiency improvement and safe operation of the WBG/Si hybrid half-bridge (HHB)-based power converters. In this article, a novel adaptive power sharing and switching frequency control for power loss optimization in WBG/Si HHB is proposed. It is based on intelligence particle swarm optimization (PSO), especially suitable for applications with time-varying operation current. The PSO approach only evaluates the fitness values to seek the best optimal parameters without requiring an accurate power loss model and additional hardware components. Therefore, the proposed method can be easily implemented and adapted to various working conditions. A 3-kW prototype of the Si/SiC HHB-based single-phase inverter is built to validate the proposed approach. In comparison with the fixed frequency and power-sharing ratio, the proposed method achieves an 18% maximum total power loss reduction while maintaining the same power quality performance.

Published
2023
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237. Multimodal Self-Paced Locality-Preserving Learning for Diagnosis of Alzheimer’s Disease

Author

Hao, Xiaoke, Wang, Ruxue, Guo, Yingchun, Xiao, Yunjia, Yu, Ming, Wang, Meiling, Chen, Weibin, and Zhang, Daoqiang

Abstract

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease that severely impairs human thinking and memory. The accurate diagnosis of AD and its prodromal stages, such as mild cognitive impairment (MCI), is very important for timely treatment or possible interventions of AD. Recent studies have shown that multiple neuroimaging and biological measures contain supplementary information for diagnosis and prognosis. Most existing methods are proposed to simply integrate the multimodal data and train the model using all samples once, which do not fully explore the structural information across the different modalities and ignore the significance of sample learning in the training process. In this article, we propose a multimodal self-paced locality-preserving learning (MSLPL) framework to preserve the inherent structural relationships of the original data and realize the sample selection process from “simple” to “complex.” Specifically, the model can project the neuroimaging and genetic data into the label space and learn dimensionality reduction manners with preserving locality structure. Meanwhile, the contributions of each sample are adaptively evaluated by weighting optimization so that the impact of noises can be reduced during model training by self-paced learning (SPL). Finally, a multikernel support vector machine (MK-SVM) is used to fuse the features selected from different modalities for the final prediction. We evaluate MSLPL on 913 subjects from the AD neuroimaging initiative (ADNI) database with imaging and genetic data. The experimental results demonstrate that the proposed method can achieve better classification performances compared with the start-of-the-art multimodality-based methods.

Published
2023
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238. Multi-verse Optimizer with Rosenbrock and Diffusion Mechanisms for Multilevel Threshold Image Segmentation from COVID-19 Chest X-Ray Images

Author

Han, Yan, Chen, Weibin, Heidari, Ali Asghar, and Chen, Huiling

Abstract

Coronavirus Disease 2019 (COVID-19) is the most severe epidemic that is prevalent all over the world. How quickly and accurately identifying COVID-19 is of great significance to controlling the spread speed of the epidemic. Moreover, it is essential to accurately and rapidly identify COVID-19 lesions by analyzing Chest X-ray images. As we all know, image segmentation is a critical stage in image processing and analysis. To achieve better image segmentation results, this paper proposes to improve the multi-verse optimizer algorithm using the Rosenbrock method and diffusion mechanism named RDMVO. Then utilizes RDMVO to calculate the maximum Kapur’s entropy for multilevel threshold image segmentation. This image segmentation scheme is called RDMVO-MIS. We ran two sets of experiments to test the performance of RDMVO and RDMVO-MIS. First, RDMVO was compared with other excellent peers on IEEE CEC2017 to test the performance of RDMVO on benchmark functions. Second, the image segmentation experiment was carried out using RDMVO-MIS, and some meta-heuristic algorithms were selected as comparisons. The test image dataset includes Berkeley images and COVID-19 Chest X-ray images. The experimental results verify that RDMVO is highly competitive in benchmark functions and image segmentation experiments compared with other meta-heuristic algorithms.

Published
2023
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239. Analysis of oligosaccharides derived from heparin by ion-pair reversed-phase chromatography/mass spectrometry

Author

Doneanu, Catalin E., Chen, Weibin, and Gebler, John C.

Subjects
Oligosaccharides -- Properties, Heparin -- Properties, Chromatography -- Methods, Mass spectrometry -- Methods, Chemistry, Analytic -- Methods, Chemistry
Abstract

Current chromatographic and mass spectrometric techniques have limitations for analyzing heparin and heparin oligomers due to their high polarity, structural diversity, and sulfate lability. A rapid method for the analysis of heparin oligosaccharides was developed using ion-pair reversed-phase ultraperformance liquid chromatography coupled with electrospray quadruple time-of-flight mass spectrometry (IPRP-UPLC ESI Q-TOF MS). The method utilizes an optimized buffer system containing a linear pentylamine and a unique additive, 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP), to achieve highly efficient separation together with enhanced mass response of heparin oligosaccharides. Analyses of a heparin oligosaccharide test mixture, dp6 through dp22, reveal that the chromatographic conditions enable baseline resolution of isomeric heparin oligosaccharides (dp6) and produce intact molecular ions with no sulfate losses during mass spectrometric analysis. In addition, the described conditions are amenable to the detection of heparin oligosaccharides in positive ion mode, yield stronger positive ion signals for corresponding oligosaccharides compared to the negative ion mode, and allow identification of structural isomers by an MS/MS approach. Because sensitive detection of oligosaccharides is also achieved with ultraviolet (UV) detection, the method utilizes a dual detection scheme (UV and MS in series) along with IPRP UPLC to simultaneously obtain quantification (UV) and characterization (MS) data for heparin oligosaccharides. The broad potential of this new method is further demonstrated for the analysis of a low-molecular-weight heparin (LMWH) preparation from porcine heparin. This approach will be of particular utility for profiling the molecular entities of heparin materials, as well as for structural variability comparison for samples from various sources.

Published
2009

242. Copper-based theranostic nanocatalysts for synergetic photothermal-chemodynamic therapy.

Author

Zuo, Wenbao, Fan, Zhongxiong, Chen, Luping, Liu, Jinxue, Wan, Zheng, Xiao, Zhimei, Chen, Weibin, Wu, Liang, Chen, Dengyue, and Zhu, Xuan

Subjects
METASTATIC breast cancer, CARBONIC anhydrase inhibitors, ACOUSTIC imaging, CARBONIC anhydrase, HABER-Weiss reaction
Abstract

Chemodynamic therapy (CDT) has aroused extensive attention as a potent therapeutic modality. However, its practical application is severely restricted by the strong acidity requirement for Fenton reaction and upregulated antioxidant defense within metastatic breast cancer. Herein, a copper-based single-site nanocatalyst functionalized with carbonic anhydrase inhibitor (CAI) was constructed for magnetic resonance/photoacoustic imaging (MRI/PA)-guided synergetic photothermal therapy (PTT) and CDT. Once reaching tumor sites, the nanocatalyst can be recognized by tumor cell membranes-overexpressed carbonic anhydrase IX (CA IX). Subsequently, the single-site CuII can be reduced to CuI by the tumor-overexpressed glutathione (GSH), which simultaneously impaired the tumor antioxidant defense system and triggered CAI release for inducing intracellular H+ accumulation. Further, the decreased intracellular pH can accelerate the nanocatalyst biodegradation to release more CuII and CAI to participate in next-cycle GSH-depletion and cytoplasm acidification, respectively, thereby continuously supplying CuI and H+ for self-cyclically amplified CDT. Upon laser irradiation, the nanocatalyst can generate local heat, which not only permits PTT but also enhances the nanocatalyst-mediated CDT. Moreover, the suppression of CA IX can hinder the tumor extracellular matrix degradation to prevent tumor metastasis. Overall, this work highlighted the great application prospect in enhancing CDT via tumor acidic/redox microenvironment remodeling, and provides an insightful paradigm for inhibiting breast cancer metastasis. The practical application of chemodynamic therapy (CDT) is severely restricted by the strong acidity requirement for Fenton reaction and upregulated antioxidant defense within cancer. Herein, we developed a carbonic anhydrase inhibitor (CAI)-functionalized Cu-based nanocatalyst. Once reaching tumor sites, the CuII can be reduced to CuI by the tumor-overexpressed glutathione (GSH), which simultaneously impaired the tumor antioxidant system and triggered CAI release for inducing intracellular H+ accumulation. Further, the decreased intracellular pH can accelerate the nanocatalyst biodegradation to release more CuII and CAI to participate in next-cycle GSH-depletion and cytoplasm acidification, respectively, thus continuously supplying CuI and H+ for self-cyclically amplified CDT. Upon laser irradiation, the nanocatalyst not only permits PTT but also enhances the CDT. [Display omitted] [ABSTRACT FROM AUTHOR]

Published
2022
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243. Mechanistic and Experimental Study of the Cu x O@C Nanocomposite Derived from Cu 3 (BTC) 2 for SO 2 Removal.

Author

Duan, Rudi, Chen, Weibin, Chen, Ziwei, Gu, Jialiang, Dong, Zhaoqi, He, Beini, Liu, Lili, and Wang, Xidong

Subjects
*CHARGE transfer, *NANOCOMPOSITE materials, *FLUE gas desulfurization, *COPPER oxide
Abstract

A tunable and efficient strategy was adopted to synthesize highly porous nano-structured CuO−carbonized composites (CuxO@C) using Cu3(BTC)2 as a sacrificial template. The as-synthesized CuO nanocomposites exhibited hollow octahedral structures, a large surface area (89.837 m2 g−1) and a high proportion of Cu2O active sites distributed on a carbon frame. Based on DFT calculations, both the Cu atoms on the surface (CuS) and oxygen vacancy (OV) exhibited strong chemical reactivity. On the perfect CuO (111), the CuS transferred charge to O atoms on the surface and SO2 molecules. A strong adsorption energy (−1.41 eV) indicated the existence of the chemisorption process. On the oxygen-deficient CuO (111), the O2 preferably adsorbed on OV and then formed SO3 by bonding with SO2, followed by the cleavage of the O−O bond. Furthermore, the CuO nanocomposites exhibited an excellent ratio of S/Cu in SO2 removal experiments compared with CuO nanoparticles produced by coprecipitation. [ABSTRACT FROM AUTHOR]

Published
2022
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249. New Peak Detection Performance Metrics from the MAM Consortium Interlaboratory Study

Author

Mouchahoir, Trina, primary, Schiel, John E., additional, Rogers, Rich, additional, Heckert, Alan, additional, Place, Benjamin J., additional, Ammerman, Aaron, additional, Li, Xiaoxiao, additional, Robinson, Tom, additional, Schmidt, Brian, additional, Chumsae, Chris M., additional, Li, Xinbi, additional, Manuilov, Anton V., additional, Yan, Bo, additional, Staples, Gregory O., additional, Ren, Da, additional, Veach, Alexander J., additional, Wang, Dongdong, additional, Yared, Wael, additional, Sosic, Zoran, additional, Wang, Yan, additional, Zang, Li, additional, Leone, Anthony M., additional, Liu, Peiran, additional, Ludwig, Richard, additional, Tao, Li, additional, Wu, Wei, additional, Cansizoglu, Ahmet, additional, Hanneman, Andrew, additional, Adams, Greg W., additional, Perdivara, Irina, additional, Walker, Hunter, additional, Wilson, Margo, additional, Brandenburg, Arnd, additional, DeGraan-Weber, Nick, additional, Gotta, Stefano, additional, Shambaugh, Joe, additional, Alvarez, Melissa, additional, Yu, X. Christopher, additional, Cao, Li, additional, Shao, Chun, additional, Mahan, Andrew, additional, Nanda, Hirsh, additional, Nields, Kristen, additional, Nightlinger, Nancy, additional, Barysz, Helena Maria, additional, Jahn, Michael, additional, Niu, Ben, additional, Wang, Jihong, additional, Leo, Gabriella, additional, Sepe, Nunzio, additional, Liu, Yan-Hui, additional, Patel, Bhumit A., additional, Richardson, Douglas, additional, Wang, Yi, additional, Tizabi, Daniela, additional, Borisov, Oleg V., additional, Lu, Yali, additional, Maynard, Ernest L., additional, Gruhler, Albrecht, additional, Haselmann, Kim F., additional, Krogh, Thomas N., additional, Sönksen, Carsten P., additional, Letarte, Simon, additional, Shen, Sean, additional, Boggio, Kristin, additional, Johnson, Keith, additional, Ni, Wenqin, additional, Patel, Himakshi, additional, Ripley, David, additional, Rouse, Jason C., additional, Zhang, Ying, additional, Daniels, Carly, additional, Dawdy, Andrew, additional, Friese, Olga, additional, Powers, Thomas W., additional, Sperry, Justin B., additional, Woods, Josh, additional, Carlson, Eric, additional, Sen, K. Ilker, additional, Skilton, St John, additional, Busch, Michelle, additional, Lund, Anders, additional, Stapels, Martha, additional, Guo, Xu, additional, Heidelberger, Sibylle, additional, Kaluarachchi, Harini, additional, McCarthy, Sean, additional, Kim, John, additional, Zhen, Jing, additional, Zhou, Ying, additional, Rogstad, Sarah, additional, Wang, Xiaoshi, additional, Fang, Jing, additional, Chen, Weibin, additional, Yu, Ying Qing, additional, Hoogerheide, John G., additional, Scott, Rebecca, additional, and Yuan, Hua, additional

Published
2021
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