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823 results on '"Xu, Jianrong"'

4. Research on Crack Control Method of Girder End Anchorage Zone Based on Nonlinear Finite Element Analysis

Author

Wang, Tongyi, Gu, Jinjian, Xu, Jianrong, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Guo, Wei, editor, Qian, Kai, editor, Tang, Honggang, editor, and Gong, Lei, editor

Published
2024
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5. Research on the application of knowledge graph in intelligent operation and maintenance for optical transport network

Author

YANG Ganggang, SHAO Zhugui, SHANG Fengliang, XU Jianrong, and LIU Cui

Subjects
knowledge graph, optical transport network, intelligent operation and maintenance, Telecommunication, TK5101-6720, Technology
Abstract

In order to solve the problems of high cost, low efficiency, and weak intelligence in the traditional operation and maintenance mode of optical transport networks, the research status and challenges of knowledge graph technology in the telecom industry were analyzed. Firstly, an intelligent operation and maintenance system architecture for optical transport networks based on knowledge graphs were proposed. Key technologies such as network state perception, knowledge graph construction, and open search capabilities were emphatically studied. Secondly, the application of intelligent cutover in a city branch of China Telecom was taken as an example, the application effect was analyzed, and the test showed that the cutover efficiency was improved by about 3 times. Finally, the development trend of intelligent operation and maintenance of optical transmission networks based on knowledge graphs was discussed.

Published
2024
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6. HiGNN: Hierarchical Informative Graph Neural Networks for Molecular Property Prediction Equipped with Feature-Wise Attention

Author

Zhu, Weimin, Zhang, Yi, Zhao, DuanCheng, Xu, Jianrong, and Wang, Ling

Subjects
Computer Science - Machine Learning, Quantitative Biology - Quantitative Methods
Abstract

Elucidating and accurately predicting the druggability and bioactivities of molecules plays a pivotal role in drug design and discovery and remains an open challenge. Recently, graph neural networks (GNN) have made remarkable advancements in graph-based molecular property prediction. However, current graph-based deep learning methods neglect the hierarchical information of molecules and the relationships between feature channels. In this study, we propose a well-designed hierarchical informative graph neural networks framework (termed HiGNN) for predicting molecular property by utilizing a co-representation learning of molecular graphs and chemically synthesizable BRICS fragments. Furthermore, a plug-and-play feature-wise attention block is first designed in HiGNN architecture to adaptively recalibrate atomic features after the message passing phase. Extensive experiments demonstrate that HiGNN achieves state-of-the-art predictive performance on many challenging drug discovery-associated benchmark datasets. In addition, we devise a molecule-fragment similarity mechanism to comprehensively investigate the interpretability of HiGNN model at the subgraph level, indicating that HiGNN as a powerful deep learning tool can help chemists and pharmacists identify the key components of molecules for designing better molecules with desired properties or functions. The source code is publicly available at https://github.com/idruglab/hignn.

Published
2022

17. PFGDF: Pruning Filter via Gaussian Distribution Feature for Deep Neural Networks Acceleration

Author

Xu, Jianrong, Diao, Boyu, Cui, Bifeng, Yang, Kang, Li, Chao, and Xu, Yongjun

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Deep learning has achieved impressive results in many areas, but the deployment of edge intelligent devices is still very slow. To solve this problem, we propose a novel compression and acceleration method based on data distribution characteristics for deep neural networks, namely Pruning Filter via Gaussian Distribution Feature (PFGDF). Compared with previous advanced pruning methods, PFGDF compresses the model by filters with insignificance in distribution, regardless of the contribution and sensitivity information of the convolution filter. PFGDF is significantly different from weight sparsification pruning because it does not require the special accelerated library to process the sparse weight matrix and introduces no more extra parameters. The pruning process of PFGDF is automated. Furthermore, the model compressed by PFGDF can restore the same performance as the uncompressed model. We evaluate PFGDF through extensive experiments, on CIFAR-10, PFGDF compresses the convolution filter on VGG-16 by 66.62% with more than 90% parameter reduced, while the inference time is accelerated by 83.73% on Huawei MATE 10.

Published
2020

18. Implementation of Global Hearts Hypertension Control Programs in 32 Low- and Middle-Income Countries: JACC International

Author

Pathni, Anupam, Osi, Kufor, Dessie, Girma, Zhang, Xiulei, Cazabon, Danielle, Banigbe, Bolanle, Farrell, Margaret, Erojikwe, Okeoma, Swahoo, Swagata, Krishna, Ashish, Yusuf, Abdikaid Ahmed, Kebede, Henok Gebreyohannes, Berhanu, Molla Gedefaw, Bezabih, Tilahun, Tegegn, Teshome Ayalew, Demissie, Workneh, Burka, Daniel, Tasmin, Misu, Ogbeide, Bolatito, Cheadle, Timothy, Odu, Joseph, Beyene, Meron Hailu, Borkhataria, Cecile, Elliott, Kate, Jaffe, Marc, Garg, Renu, Frieden, Thomas R., Khan, Taskeen, Slama, Slim, Mikkelson, Bente, Lai, Truong Duc, Santos, Rauell John, Aquino, Tyrone, Calla, Dofel Joseph, Kunwar, Abhishek, Durgad, Kiran, Bunluesin, Sushera, Dewan, Mary, Obagha, C.E., Msyamboza, Kelias, Das, Bidisha, Kishore, Navneet, Puthussery, Yannick Poulose, Sambandam, Gopinath Thirugnana, Immanuel, A Branch, Chandrakant Joshi, Chakshu, Bhardawaj, Rupali, Wankhede, Amol, Khedkar, Suhas Namdevrao, Bhardawaj, Vishwajit Washudeorao, Kumar Reddy, Thokala Sravan, Chavan, Tejpalsinh Anandrao, Chittimella, Raghavendra Patel, Bhandari, Subhasis, Shah, Urvin Kumar, Chandram, Deenadayalan, Wassey, Mohammed Abdul, Kadia, Abhinav, Sarode, Lalit Dinkar, Chauhan, Lalita, Ponna, Satyendra Nath, Babu, Suresh, Gupta, Piyush, Reddy, Thej Kiran, Sekhon, Hanspreet, Jeelani, Asif, Nath, Gunjan, Wankhede, Virendra, Jayaprasad, Niniya, Mohanty, Trishna, Kumar, Praveen, Khanna, Abhishek, Singh, Shweta, Bhat, Ashish, Thakkar, Jatin, Anitha Sreekumar, Aiswarya Lakshmi, Lakshmanasamy, Ravivarman, Rafique, Mohamed Essa, Dar, Sunil Kumar, Chintala, Sreedhar, Jagadeesh, Bharath, Patruni, Manoj, Raimule, Madhur, Prabhu Valawalkar, Shahanara S., Ordunez, Pedro, Giraldo, Gloria, Martinez, Ramon, Rosende, Andres, Rodriguez, Yenny, Lombardi, Cintia, Gamarra, Angelo, Rodriguez, Libardo, Parra, Natalia, Rodriguez, Gonzalo, Villalta, Noelia, Escobar, Maria C., Villacres, Nilda, Sorto, Carlos, Baca, Edith, Batista, Vhania, Perez, Vivian, Victoria, Jorge, Abaakouk, Zohra, Malcolm, Taraleen, Kostova, Deliana, Richter, Patricia, Whelton, Paul K., Lackland, Daniel, Weber, Michael, Pineiro, Daniel, Wood, David, Pinto, Fausto, Mwangi, Jeremiah, Perel, Pablo, Codato, Elisa, Eiselé, Jean-Luc, Kaur, Prabhdeep, Parashuraman, Ganeshkumar, Sharma, Meenakshi, Shivashankar, Roopa, Bangar, Sampada Dipak, Chakma, Tapas, Pragya, Pragati, Malik, Abdul, Awal, Khondker Abdul, Malik, Fazilatunnesa, Choudhury, Sohel Reza, Bhuiyan, Mahfuzur Rahman, Jubayer, Shamim, Al Mamun, Mohammad Abdullah, Ishraquzzaman, Mir, Abrar, Ahmed Khairul, Akhter, Jubaida, Sultana, Sarmin, Parvej, Aslam, Sayem Khandoker Ehsanul Amin, Noor Nabi, Islam, Md Shahinul, Dey Parag, Deb Dulal, Amin, Ruhul, Luna, Mahfuja, Ibn Karim, Md Abbas, Mahajabin, Progga, Khan, Iqbal Ahmed, Hossain, Sazzad, Ullah, Riasat Razi, Nahid, Muhtamim Fuwad, Zhang, Xinhua, Huang, Hongxia, Wang, Hao, Guan, Tingrui, Zhao, Haiying, Ojji, Dike, Shedul, Gabriel Lamkur, Shedul, Grace, Orji, Anthony, Asuku, Regina, Alo-Joseph, Confidence, Akor, Charity, Egenti, Nonye, Nwankwo, Ada, Omitiran, Kasarachi, Okoli, Rosemary, Ripiye, Nanna, Akor, Blessing, Cai, Jun, Wang, Lu, Wang, Wenjie, Fan, Luyun, Xu, Jianrong (Jenny), Tang, Shanshan, Wu, Guoli, Smith, Barbara, Kenyon, Thomas, Mandal, Sudarsan, Swarnakar, Sunny, Wickramasinghe, S.C., Herath, Amila Bandarra, Ratnayake, I.U., Samarasinghe, Kosala, Kumarasiri, K.H.N., Vensentini, Natalia, Mendieta, Daniel Palacios, Rivera, Marcela, Gonzalez, Yamile Valdez, Cevallos, Lucia, Villatoro, Matías Humberto, Gloria Hernandez, Laura Elena, Arenas, Elsa, Fernández, Daniel, De Oleo, Daniel Mola, Cyr, Shana, Mitchell, Roxanne, Hossain, AHM Enayet, Amin, Mohammad Robed, Alim, Abdul, Milon, Sarowar Uddin, Alex-Okoh, M.O., Odoh-Bako, D.O., Malau, M.T., Oshundele, B.R., Akinkoye, O.K., Abraham, E.A., Eze, S.V., Elemuwa, Chris, Lamorde, Suleiman, Oguntayo, E.A., Rajab, Ashiru, Ibrahim, Auwalu, Soyinka, Festus, Caluag, Maria Elizabeth, Uy, Maria Rosario, Adriano Subaan, Regional Director, Gayomali, Aimee Marie, Lapascua, John Richard, Taffese, Hiwot Solomon, Bac, Truong Dinh, Bao, Tran Quoc, Guo, Xiaolei, Xu, Chunxiao, Zhang, Bingyin, Thi Tho, Nguyen Thi, Van, Ngo Hai, Danh, Phan Cong, Tinh, Ho Huu, Hau, Tran Phuc, Appel, Lawrence J., Matsushita, Kunihiro, Andersen, Katye, Ayensu-Asiedu, Christabelle, Byiringiro, Samuel, Brady, Tammy, Charleston, Jeanne, Chen, Mengkun, Commodore–Mensah, Yvonne, Dalcin, Arlene, Dennison-Himmelfarb, Cheryl, Ding, Ning, Doyle, Christopher K., Edward, Anbrasi, de Souza Elias, Sabrina, Foti, Kathryn, Greer, Raquel, Henry, Megan, Hu, Xiao, Ishigami, Junichi, Kou, Minghao, Lord, Katherine, Lu, Yifei, Marklund, Matti, Amezcua, Pablo Martinez, Mattingly, Joey, McArthur, Kristin, Miller, Edgar R., III, Neupane, Dinesh, Ogungbe, Bunmi, Pariyo, George, Pathak, Priya, Pilla, Scott, Rao, Krishna, Resnick, Carol, Riekert, Kristin, Sakulsaengprapha, Tangkwa, Scheiber, Simona, Shilkofski, Nicole, Tamplin, Steve, Tang, Olive, Zhao, Di, Campbell, Norman, Ogedegbe, Olugbenga, Di Pette, Donald, Brettler, Jeffrey, Connell, Kenneth, Kishore, Sandeep P., Huffman, Mark, Hutchinson, Brian, Abdalla, Marwa, Moran, Andrew E., and Gupta, Reena

Published
2023
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19. Glial cell line-derived neurotrophic factor (GDNF) mediates hepatic stellate cell activation via ALK5/Smad signalling

Author

Tao, Le, Ma, Wenting, Wu, Liu, Xu, Mingyi, Yang, Yanqin, Zhang, Wei, Sha, Wenjun, Li, Hongshan, Xu, Jianrong, Feng, Rilu, Xue, Dongying, Zhang, Jie, Dooley, Steven, Seki, Ekihiro, Liu, Ping, and Liu, Cheng

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Nutrition and Dietetics, Liver Disease, Digestive Diseases, Chronic Liver Disease and Cirrhosis, Aetiology, 2.1 Biological and endogenous factors, Oral and gastrointestinal, Adult, Animals, Biopsy, Cell Line, Disease Models, Animal, Female, Follow-Up Studies, Gene Expression Regulation, Glial Cell Line-Derived Neurotrophic Factor, Hepatic Stellate Cells, Humans, Liver Cirrhosis, Male, Mice, RNA, Receptor, Transforming Growth Factor-beta Type I, Retrospective Studies, Signal Transduction, Smad Proteins, Up-Regulation, chronic liver disease, hepatic fibrosis, hepatic stellate cell, Paediatrics and Reproductive Medicine, Gastroenterology & Hepatology, Clinical sciences, Nutrition and dietetics
Abstract

ObjectiveAlthough glial cell line-derived neurotrophic factor (GDNF) is a member of the transforming growth factor-β superfamily, its function in liver fibrosis has rarely been studied. Here, we investigated the role of GDNF in hepatic stellate cell (HSC) activation and liver fibrosis in humans and mice.DesignGDNF expression was examined in liver biopsies and sera from patients with liver fibrosis. The functional role of GDNF in liver fibrosis was examined in mice with adenoviral delivery of the GDNF gene, GDNF sgRNA CRISPR/Cas9 and the administration of GDNF-blocking antibodies. GDNF was examined on HSC activation using human and mouse primary HSCs. The binding of activin receptor-like kinase 5 (ALK5) to GDNF was determined using surface plasmon resonance (SPR), molecular docking, mutagenesis and co-immunoprecipitation.ResultsGDNF mRNA and protein levels are significantly upregulated in patients with stage F4 fibrosis. Serum GDNF content correlates positively with α-smooth muscle actin (α-SMA) and Col1A1 mRNA in human fibrotic livers. Mice with overexpressed GDNF display aggravated liver fibrosis, while mice with silenced GDNF expression or signalling inhibition by GDNF-blocking antibodies have reduced fibrosis and HSC activation. GDNF is confined mainly to HSCs and contributes to HSC activation through ALK5 at His39 and Asp76 and through downstream signalling via Smad2/3, but not through GDNF family receptor alpha-1 (GFRα1). GDNF, ALK5 and α-SMA colocalise in human and mouse HSCs, as demonstrated by confocal microscopy.ConclusionsGDNF promotes HSC activation and liver fibrosis through ALK5/Smad signalling. Inhibition of GDNF could be a novel therapeutic strategy to combat liver fibrosis.

Published
2019

21. Capsaicin receptor TRPV1 maintains quiescence of hepatic stellate cells in the liver via recruitment of SARM1

Author

Tao, Le, Yang, Guangyue, Sun, Tiantian, Jie Tao, Zhu, Chan, Yu, Huimin, Cheng, Yalan, Yang, Zongguo, Xu, Mingyi, Jiang, Yuefeng, Zhang, Wei, Wang, Zhiyi, Ma, Wenting, Wu, Liu, Xue, Dongying, Wang, Dongxue, Yang, Wentao, Zhao, Yongjuan, Horsefield, Shane, Kobe, Bostjan, Zhang, Zhe, Tang, Zongxiang, Li, Qigen, Zhai, Qiwei, Dooley, Steven, Seki, Ekihiro, Liu, Ping, Xu, Jianrong, Chen, Hongzhuan, and Liu, Cheng

Published
2023
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23. Numerical Simulation of Water Impoundment at a High Arch Dam Site

Author

Detournay, Christine, Meng, Guotao, Hou, Jing, Xu, Jianrong, Cheng, Zhao, Peterson, Ryan, Cundall, Peter, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, and Wahab, Magd Abdel, editor

Published
2022
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35. Inversion Method for Material Parameters of Concrete Dams Using Intelligent Algorithm-Based Displacement Separation.

Author

Xu, Jianrong, Gao, Lingang, Li, Tongchun, Guo, Jinhua, Qi, Huijun, Peng, Yu, and Wang, Jianxin

Abstract

Integrating long-term observational data analysis with numerical simulations of dam operations provides an effective approach to dam safety evaluation. However, analytical results are often subject to errors due to challenges in accurately surveying and modeling the foundation, as well as temporal changes in foundation properties. This paper proposes a concrete dam displacement separation model that distinguishes between deformation caused by foundation restraint and that induced by external loads. By combining this model with intelligent optimization techniques and long-term observational data, we can identify the actual mechanical parameters of the dam and conduct structural health assessments. The proposed model accommodates multiple degrees of freedom and is applicable to both two- and three-dimensional dam modeling. Consequently, it is well-suited for parameter identification and health diagnosis of concrete gravity and arch dams with extensive observational data. The efficacy of this diagnostic model has been validated through computational case studies and practical engineering applications. [ABSTRACT FROM AUTHOR]

Published
2024
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37. The Activation of Muscarinic Acetylcholine Receptors Protects against Neuroinflammation in a Mouse Model through Attenuating Microglial Inflammation.

Author

Wang, Kaichun, Xie, Yuanyuan, Chen, Xixiang, Ouyang, Xiaoyan, Zhao, Lanxue, Chen, Hongzhuan, and Xu, Jianrong

Subjects
CENTRAL nervous system, DISEASE progression, INFLAMMATION, SPINAL cord, NEUROINFLAMMATION, MUSCARINIC receptors
Abstract

Neuroinflammation is a critical factor that contributes to neurological impairment and is closely associated with the onset and progression of neurodegenerative diseases. In the central nervous system (CNS), microglia play a pivotal role in the regulation of inflammation through various signaling pathways. Therefore, mitigating microglial inflammation is considered a promising strategy for restraining neuroinflammation. Muscarinic acetylcholine receptors (mAChRs) are widely expressed in the CNS and exhibit clear neuroprotective effects in various disease models. However, whether the activation of mAChRs can harness benefits in neuroinflammation remains largely unexplored. In this study, the anti-inflammatory effects of mAChRs were found in a neuroinflammation mouse model. The expression of various cytokines and chemokines was regulated in the brains and spinal cords after the administration of mAChR agonists. Microglia were the primary target cells through which mAChRs exerted their anti-inflammatory effects. The results showed that the activation of mAChRs decreased the pro-inflammatory phenotypes of microglia, including the expression of inflammatory cytokines, morphological characteristics, and distribution density. Such anti-inflammatory modulation further exerted neuroprotection, which was found to be even more significant by the direct activation of neuronal mAChRs. This study elucidates the dual mechanisms through which mAChRs exert neuroprotective effects in central inflammatory responses, providing evidence for their application in inflammation-related neurological disorders. [ABSTRACT FROM AUTHOR]

Published
2024
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39. Quantitative susceptibility mapping (QSM) as a means to monitor cerebral hematoma treatment

Author

Zhang, Yuyao, Wei, Hongjiang, Sun, Yawen, Cronin, Matthew J, He, Naying, Xu, Jianrong, Zhou, Yan, and Liu, Chunlei

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Stroke, Neurosciences, Biomedical Imaging, Clinical Research, Brain Disorders, Adolescent, Adult, Aged, Aged, 80 and over, Cerebral Hemorrhage, Female, Hematoma, Humans, Image Interpretation, Computer-Assisted, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Observer Variation, Prospective Studies, Regression Analysis, Reproducibility of Results, Severity of Illness Index, Young Adult, computed tomography, hematoma volume, intracerebral hemorrhage, magnetic resonance imaging, quantitative susceptibility mapping, Physical Sciences, Engineering, Medical and Health Sciences, Nuclear Medicine & Medical Imaging, Clinical sciences
Abstract

BACKGROUND:Quantitative susceptibility mapping (QSM) offers a consistent hemorrhage volume measurement independent of imaging parameters. PURPOSE:To investigate the magnetic susceptibility of intracerebral hemorrhage (ICH) as a quantitative measurement for monitoring treatment in hematoma patients. STUDY TYPE:Prospective. POPULATION:Twenty-six patients with acute ICH were recruited and enrolled in treatment including surgery or medication (mannitol) for 1 week. FIELD STRENGTH/SEQUENCE:A 3D gradient echo sequence at 3.0T. ASSESSMENT:The hematoma volumes on computed tomography (CT) and QSM were calculated and used for correlation analysis. Magnetic susceptibility changes from pre- to posttreatment were calculated and compared to the National Institutes of Health stroke scale (NIHSS) measure of neurological deficit for each patient. STATISTICAL TESTS:Mean susceptibility values were calculated over each region of interest (ROI). A one-sample t-test was used to assess the changes of total volumes and mean magnetic susceptibility of ICH identified between pre- and posttreatment images (P < 0.05 was considered significant) and the Bland-Altman analysis with 95% limits of agreement (average difference, ±1.96 SD of the difference). Regression of volume measurements on QSM vs. CT and fitted linear regression of mean susceptibility vs. CT signal intensity for hematoma regions were conducted in all patients. RESULTS:Good correlation was found between hemorrhage volumes calculated from CT and QSM (CT volume = 0.94*QSM volume, r = 0.98). Comparison of QSM pre- and posttreatment showed that the mean ICH volume was reduced by a statistically insignificant amount from 5.74 cm3 to 5.45 cm3 (P = 0.21), while mean magnetic susceptibility was reduced significantly from 0.48 ppm to 0.38 ppm (P = 0.004). A significant positive association was found between changes in magnetic susceptibility values and NIHSS following hematoma treatment (P < 0.01). DATA CONCLUSIONS:QSM in hematoma assessment, as compared with CT, offers a comparably accurate volume measurement; however, susceptibility measurements may enable improved monitoring of ICH treatment compared to volume measurements alone. LEVEL OF EVIDENCE:2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:907-915.

Published
2018

48. Preparation of binary eutectic sugar alcohol particles and their application as cooling materials in traditional cigarettes.

Author

LI Kai, LIU Wen, XU Jianrong, HUANG Chaozhang, WANG Daoquan, and WANG Duo

Subjects
SUGAR alcohols, HEAT radiation & absorption, CHEMICAL reactions, ERYTHRITOL, XYLITOL, CIGARETTES
Abstract

In order to expand the screening range of cooling materials for traditional cigarettes, the eutectic point of xylitol and erythritol was calculated through the binary phase diagram of xylitol and erythritol. A binary eutectic sugar alcohols particles of xylitol and erythritol were prepared by melting method and applied as a cooling material in traditional cigarettes, and their heat absorption and cooling effects were evaluated. The results showed that the ratio of the amount of xylitol to erythritol at the eutectic point of binary eutectic sugar alcohol was 7.6 :2.4, which was named as X7.6E2.4 eutectic sugar alcohol particles, and the eutectic temperature was approximately 89 °C. The preparation process of the eutectic sugar alcohol particles did not undergo any chemical reaction, and their morphological characteristics were similar to those of xylitol particles, with a relatively smooth surface. When applied to medium and short length cigarettes, the mainstream smoke temperature of the cigarette was reduced by 6. 8 °C compared to blank cigarettes. Xylitol particles could effectively retain moisture from mainstream smoke. The more xylitol content was added to binary eutectic sugar alcohol particles, the less moisture was captured at the cigarette outlet. Binary eutectic sugar alcohol particles could intercept some of the tar in mainstream smoke, among which X7.6E2.4 eutectic sugar alcohol particle cigarettes capture the least amount of tar at the outlet, but binary eutectic sugar alcohol particles had no significant effect on the nicotine and CO content in mainstream smoke. The cigarette with added X7.6E2.4 eutectic sugar alcohol particles showed an improvement in the sweetness of the smoke, but the suction resistance slightly increased. In addition, the heat sensation of the smoke of cigarettes was decreased, resulting in the highest the overall sensory quality evaluation. [ABSTRACT FROM AUTHOR]

Published
2024
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