30,907 results on '"SUN Yu"'
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2. Environmental Nonprofit Organizations and Public Opinion on Global Warming
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Sun Yu
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environmental nonprofit organizations ,public opinion ,global warming ,the mere exposure effect ,Social pathology. Social and public welfare. Criminology ,HV1-9960 - Abstract
Environmental nonprofit organizations (ENPOs) play a critical role in climate governance. Though ENPOs dedicate significant efforts to advocacy and providing public services, their interaction with public opinion on global warming has not been fully explored. Through multilevel regression analysis on county-level data in the U.S., this article examines the relationship between the presence of ENPOs and public perceptions of global warming, taking into account variations among ENPOs. The findings indicate that: (1) the overall presence of ENPOs is slightly, but not significantly, positively correlated with public perceptions of global warming, with advocacy-oriented ENPOs showing a more robust and statistically significant correlation; (2) there is an inverted-U relationship between the presence of ENPOs and public opinion on global warming, with advocacy-oriented ENPOs reaching tipping points earlier than service-oriented ENPOs; and (3) the partisanship of liberal counties influences this association. This study suggests a potential role for nonprofits in policymaking by interacting with public opinion.
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- 2024
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3. Research on path planning of material transmission platform based on A* and dynamic window method
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TANG Wei, TAN Xiao, SUN Yu, YAN Jiapeng, and YAN Guangrui
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path planning ,A* algorithm ,dynamic window method ,Bezier curve ,material transmission ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Due to the problems of traditional material transfer equipment such as single working mode and inflexible adjustment of transfer path, intelligent material transfer system has gradually become a research hotspot in the field of logistics transmission. A path planning algorithm based on A* and dynamic window method was proposed for the modular material transmission platform, in order to improve its obstacle avoidance ability during the transfer process by flexibly adjusting the material transfer path. In the global path planning, the smoothness and static obstacle avoidance of the transmission path were realized by improving the A* weight function and integrating the Bezier curve and matrix interference theory. And by introducing the dynamic window method and extracting the global path key points as transition points for local path guidance of the transmission target, dynamic obstacle avoidance was realized when the path falling into local optimization was avoided. The research results showed that the path planning algorithm based on A* and dynamic window method could reduce the total global path length by 4.6% and the total path turning angle by 42.3%, while the dynamic obstacles could be effectively avoided in the local planning, which verified the rationality of the path planning algorithm.
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- 2023
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4. Changes in HIV prevalence and intervention service utilization among MSM under sentinel monitoring in Taizhou of Zhejiang Province
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CHEN Xiaoxiao, SUN Yu, WANG Shanling, WANG Tingting, XIE Yali, SHEN Weiwei, LIU Xing, and LIN Haijiang
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men who have sex with men ,sentinel surveillance ,aids ,hiv intervention service ,epidemic of covid-19 ,Medicine - Abstract
ObjectiveTo analyze the changes in HIV, syphilis and hepatitis C prevalence among men who have sex with men (MSM) in Taizhou City, Zhejiang Province from 2017 to 2022, and the utilization of HIV intervention services and its influencing factors.MethodsMSM participants were recruited from HIV sentinel surveillance in Taizhou through snowball sampling method. Participants’ socio-demographic characteristics, sexual behavior characteristics, knowledge of HIV and utilization of HIV intervention services were collected and statistically described by questionnaire survey. Blood samples from MSM sentinel population were also collected for HIV, syphilis, and HCV antibody testing. Multivariate logistic regression analysis was used to analyze the influencing factors for utilizing HIV intervention services among MSM.ResultsA total of 2 499 MSM were included in the analysis from 2017 to 2022, with HIV prevalence of 5.8%, syphilis prevalence of 4.0%, and HCV prevalence of 0.6%. The infection rate, proportion of homosexual anal sex and heterosexual sex showed a decreasing trend, while the proportion of condom use during homosexual anal sex, condom publicity and distribution, AIDS consultation and testing, acceptance of peer education, and online temporary homosexual sex showed an increasing trend. All these differences were statistically significant. Multivariate logistic regression analysis showed that COVID-19 epidemic (aOR=1.66, 95%CI:1.04‒2.64) and HIV knowledge awareness (aOR=2.57, 95%CI:1.22‒5.40) were positively correlated with increased acceptance of condom publicity and distribution, and utilization of AIDS counseling and testing. Those who sought male sexual partners through offline route (aOR=3.44, 95%CI: 1.16‒10.21), and had a history of sexually transmitted diseases within one year (aOR=5.47, 95%CI: 1.04‒28.76) were positively correlated with community-based methadone maintenance therapy, clean needle provision and exchange services, while COVID-19 epidemic (aOR=0.35, 95%CI: 0.14‒0.88) was negatively correlated with the utilization of these services. COVID-19 epidemic (aOR=2.11, 95%CI: 1.54‒2.89), HIV knowledge awareness (aOR=2.09, 95%CI: 1.08‒4.02), offline search for male sexual partners (aOR=1.47, 95%CI: 1.03‒2.11), and awareness of HIV infection of sexual partners (aOR=2.09, 95%CI: 1.62‒2.69) were positively correlated with the increased use of peer education service, while married or cohabited (aOR=0.73, 95%CI: 0.55‒0.98) and VCT (aOR=0.61, 95%CI: 0.46‒0.82) were negatively correlated with utilization of peer education service.ConclusionHIV infection rate of sentinel MSM population in Taizhou decreases, while the utilization of HIV intervention services increases in general. Targeted measures should be developed according to the changes in sexual behavior and HIV intervention services among MSM populations in Taizhou to improve the HIV intervention services for the MSM population.
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- 2023
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5. A monocular image depth estimation method based on weighted fusion and point‐wise convolution
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Chen Lei, Liang Zhengyou, and Sun Yu
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computer vision ,convolutional neural nets ,estimation theory ,image processing ,indoor environment ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Computer software ,QA76.75-76.765 - Abstract
Abstract The existing monocular depth estimation methods based on deep learning have difficulty in estimating the depth near the edges of the objects in an image when the depth distance between these objects changes abruptly and decline in accuracy when an image has more noises. Furthermore, these methods consume more hardware resources because they have huge network parameters. To solve these problems, this paper proposes a depth estimation method based on weighted fusion and point‐wise convolution. The authors design a maximum‐average adaptive pooling weighted fusion module (MAWF) that fuses global features and local features and a continuous point‐wise convolution module for processing the fused features derived from the (MAWF) module. The two modules work closely together for three times to perform weighted fusion and point‐wise convolution of features of multi‐scale from the encoder output, which can better decode the depth information of a scene. Experimental results show that our method achieves state‐of‐the‐art performance on the KITTI dataset with δ1 up to 0.996 and the root mean square error metric down to 8% and has demonstrated the strong generalisation and robustness.
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- 2023
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6. Necrotizing Enterocolitis and Neurodevelopmental Impairments: Microbiome, Gut, and Brain Entanglements
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Cuilee Sha, Zhaosheng Jin, Stella Y. Ku, Ann S. Kogosov, Sun Yu, Sergio D. Bergese, and Helen Hsieh
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gut–microbiota–brain ,microbiome ,nutrition ,development ,necrotizing enterocolitis (NEC) ,inflammatory bowel disease ,Microbiology ,QR1-502 - Abstract
There is significant communication and interdependence among the gut, the microbiome, and the brain during development. Diseases, such as necrotizing enterocolitis (NEC), highlight how injury to the immature gastrointestinal tract leads to long-term neurological consequences, due to vulnerabilities of the brain in the early stages of life. A better understanding of the developing gut–microbiota–brain axis is needed to both prevent and treat the devastating consequences of these disease processes. The gut–microbiota–brain axis is a bidirectional communication pathway that includes metabolic, nervous, endocrine, and immune components. In this review, we discuss gut development, microbiome colonization and maturation, and the interactions that influence neurodevelopment in the context of NEC. We describe the components of the gut–brain axis and how the microbiome is an integral member of this relationship. Finally, we explore how derangements within the microbiome and gut–microbiota–brain axis affect the normal development and function of the other systems and long-term neurodevelopmental consequences for patients.
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- 2024
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7. Ferroptosis: A potential target of macrophages in plaque vulnerability
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Li Yu, Ma Ji-Qing, Wang Chao-Chen, Zhou Jian, Sun Yu-Dong, Wei Xiao-Long, and Zhao Zhi-Qing
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atherosclerosis ,ferroptosis ,macrophage ,plaque vulnerability ,Biology (General) ,QH301-705.5 - Abstract
Plaque vulnerability has been the subject of several recent studies aimed at reducing the risk of stroke and carotid artery stenosis. Atherosclerotic plaque development is a complex process involving inflammation mediated by macrophages. Plaques become more vulnerable when the equilibrium between macrophage recruitment and clearance is disturbed. Lipoperoxides, which are affected by iron levels in cells, are responsible for the cell death seen in ferroptosis. Ferroptosis results from lipoperoxide-induced mitochondrial membrane toxicity. Atherosclerosis in ApoE(−/−) mice is reduced when ferroptosis is inhibited and iron intake is limited. Single-cell sequencing revealed that a ferroptosis-related gene was substantially expressed in atherosclerosis-modeled macrophages. Since ferroptosis can be regulated, it offers hope as a non-invasive method of treating carotid plaque. In this study, we discuss the role of ferroptosis in atherosclerotic plaque vulnerability, including its mechanism, regulation, and potential future research directions.
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- 2023
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8. Circular RNA hsa_circ_0007444 inhibits ovarian cancer progression through miR-23a-3p/DICER1 axis
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Zhang Min, Sun Yu, Xu Hanzi, Shi Yaqian, Shen Rong, Teng Fang, Xu Juan, and Jia Xuemei
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ovarian cancer ,hsa_circ_0007444 ,miR-23a-3p ,DICER1 ,progression ,Biochemistry ,QD415-436 ,Genetics ,QH426-470 - Abstract
Ovarian cancer is the second leading cause of death in women with gynecological malignancy in China. Circular RNAs are a class of noncoding regulatory RNAs reported to be involved in cancer development and progression. Previous studies, including our own, have indicated that hsa_circ_0007444 is downregulated in ovarian cancer tissues. This study aims to elucidate the function and mechanism of hsa_circ_0007444 in ovarian cancer progression. The expression of hsa_circ_0007444 is determined by quantitative real-time PCR (qRT-PCR). Cell proliferation, invasion, migration and apoptosis are examined by cell counting-kit 8 (CCK-8), transwell and flow cytometry assays. Tumor growth and metastasis are assessed in vivo using Balb/c nude mouse xenograft model and tail vein injection model. And the mechanism of action of hsa_circ_0007444 is analysed by RNA-binding protein immunoprecipitation (RIP), luciferase reporter and rescue assays. hsa_circ_0007444 is downregulated in ovarian cancer tissues and cell lines compared with that in normal ovarian tissues and normal epithelial cell line. Gain- and loss-of-function results indicate that hsa_circ_0007444 inhibits cell proliferation, invasion, migration and increases cell apoptosis of ovarian cancer cells in vitro, and inhibits tumor growth and lung metastasis in vivo. Mechanistically, hsa_circ_0007444 can interact with AGO2 and sponge miR-23a-3p, thereby upregulating DICER1 expression, which is an important tumor suppressor in ovarian cancer. And miR-23a-3p mimics can rescue the inhibitory effect of hsa_circ_0007444 on ovarian cancer cell proliferation, invasion and migration. Therefore, hsa_circ_0007444 can inhibit ovarian cancer progression through the hsa_circ_0007444/miR-23a-3p/DICER1 axis.
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- 2023
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9. Development of a Dual-Probe Competitive Enzyme-Linked Immunosorbent Assay Based on Magnetic Nanoparticles for the Detection of Fumonisin B
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SUN Yu, MENG Xianmei, LIN Chao, LI Bing, ZHANG Liang
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magnetic nanoparticle-fumonisin b1 probe ,monoclonal antibody-horseradish peroxidase probe ,fumonisin ,dual-probe assay ,Food processing and manufacture ,TP368-456 - Abstract
In this study, a dual-probe competitive enzyme-linked immunosorbent assay (ELISA) based on magnetic nanoparticles for the simultaneous detection of fumonisin B1 (FB1), FB2 and FB3 in maize samples was established. A magnetic capture probe (MNPs-FB1) was synthesized by the active ester method, and a monoclonal antibody-horseradish peroxidase (McAb-HRP) probe was prepared by a modified sodium periodate method. The reaction conditions of the assay were optimized. The linear ranges for FB1 and the total amount of FB1, FB2 and FB3 (FBs) were 0.07–1.98 and 0.10–9.86 ng/mL, respectively. The average recoveries of FBs from spiked maize samples ranged from 86.2% to 105.1%. The correlation coefficient between the results of the developed assay and those of liquid chromatography-tandem mass spectrometry (LC-MS/MS) was 0.996 6. These results suggest that this assay is characterized by rapidity, high accuracy and good repeatability and provides a new method for the detection of FBs in maize samples.
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- 2023
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10. Study on an Improved Algorithm for Helical Gear Meshing Stiffness and Its Influencing Factors
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Liu Ziqian, Sun Yu, Zhou Chaodong, Jiang Yanjun, Feng Nan, and Zhao Linyan
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Tooth root transition curve ,Potential energy method ,Helical gear ,Meshing stiffness ,Contact ratio ,Mechanical engineering and machinery ,TJ1-1570 - Abstract
Based on the potential energy method, an algorithm for modifying the meshing stiffness of helical gears is proposed. This method considers the real machining of the tooth root transition curve, which is a trajectory line formed by the tip angle of the tooth when the tool rolls into motion, and the starting point of the involute is the intersection of the tooth root transition curve and the involute. When calculating the stiffness, the tooth root transition curve equation from the root of the tooth to the starting point of the involute is used for the calculation, and the involute equation from the starting point of the involute to the top of the tooth is used in the calculation. The meshing stiffness calculated by this method is closer to the reality. Compared with the finite element method, the accuracy of the modified algorithm is verified and the calculation accuracy of the helical gear meshing stiffness is improved. Based on this method, the influence of involute shape, meshing position and contact ratio on the meshing stiffness and transmission error of helical gears is analyzed. The research results show that when the pressure angle increases, the radius of curvature of involute will increase. Thus the transverse stiffness of gears is improved. At the same time, the transverse contact ratio will firstly increase and then decrease. Under the influence of transverse stiffness and transverse contact ratio, the variation trend of average meshing stiffness is the same as that of transverse contact ratio; when the meshing position is closer to the node, the meshing stiffness will increase; an increased total contact ratio will make the average stiffness increase, and the transmission error (TE) decrease as a whole. However, when the contact ratio is close to the odd multiple of 0.5, the TE peak-to-peak value will reach a maximum value.
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- 2023
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11. Perioperative utility of amisulpride and dopamine receptor antagonist antiemetics-a narrative review
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Murad Elias, Alexa Gombert, Sulaimaan Siddiqui, Sun Yu, Zhaosheng Jin, and Sergio Bergese
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amisulpride ,antiemetics ,dopamine receptor antagonist ,haloperidol ,droperidol ,post-operative nausea and vomiting ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Despite advances in antiemetics and protocolized postoperative nausea vomiting (PONV) management, it remains one of the most common postoperative adverse events. In patients who developed PONV despite antiemetic prophylaxis, giving a rescue treatment from the same class of medication is known to be of limited efficacy. Given the widespread use of 5-HT3 antagonists as PONV prophylaxis, another class of effective intravenous rescue antiemetic is in dire need, especially when prophylaxis fails, and rescue medication is utilized. Dopamine antagonists were widely used for the treatment of PONV but have fallen out of favor due to some of their side effect profiles. Amisulpride was first designed as an antipsychotic medication but was found to have antiemetic properties. Here we will review the historical perspective on the use of dopamine receptor antagonist antiemetics, as well as the evidence on the efficacy and safety of amisulpride.
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- 2023
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12. Optical Performance Monitoring Technology of IMDD System based on Deep Neural Network
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LIU Jun, LI Bo-zhong, CHENG Fang, LI Zi-fan, GUO Ying, SUN Yu-xiao, DENG Cun-xue, ZHANG Ru-yi, and WANG Ying-xu
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DNN ,OSNR ,optical performance monitoring ,IMDD ,Applied optics. Photonics ,TA1501-1820 - Abstract
In advanced high-speed fiber optic communication systems, due to the introduction of dense wavelength division multiplexing technology, the signal spectral interval is getting narrower and narrower, and the traditional out-of-band Optical Signal-to-Noise Ratio (OSNR) monitoring technology is no longer accurate. Therefore, further study is required in the low-cost in-band OSNR monitoring scheme. A Deep Neural Network (DNN) link OSNR monitoring scheme for Intensity-Modulation and Direct Detection (IMDD) system is proposed. We used a 5-layer DNN trained from 550 000 datasets to successfully estimate the OSNR of the 2 GBaud On-Off Key (OOK) signal in the range of 5 to 15 dB, and the Mean Absolute Error (MAE) is less than 0.8 dB.
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- 2023
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13. DEEP-SEA LANDING VEHICLE SHAPE DRAG ANALYSIS AND BOW MODELED LINE OPTIMIZATION DESIGN (MT)
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ZHANG ZiYao, ZHOU Yue, SUN Yu, LAN YanJun, and GUO Wei
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Deep-sea landing vehicle ,Drag ,Optimal design ,Bow modeled line ,Computational Fluid Dynamics(CFD) ,Mechanical engineering and machinery ,TJ1-1570 ,Materials of engineering and construction. Mechanics of materials ,TA401-492 - Abstract
Based on the computational fluid dynamics, a numerical model of deep-sea landing vehicle was established to meet the requirements of deep-sea landing vehicle for large scale and long period submarine operation. The key design variables were determined by parametric analysis of the control point of the landing vehicle bow modeled line, which was carried out in the Isight software through the combination with SolidWorks and Fluent. The optimal latin Hypercube method is used to select sample points for the direct navigation resistance calculation, an approximate model of design variable-resistance was established based on the radial basis function neural network, and the optimal design of landing vehicle bow modeled line was carried out by using the adaptive simulated annealing algorithm. The optimized resistance is reduced by 14.24%, and the hydrodynamic performance is improved. This work provides a basis for the optimization design of the deep-sea landing vehicle and can also provide a reference for the numerical analysis of other submersible vehicles.
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- 2023
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14. Research progress in additive friction stir deposition
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CHEN Gang, WU Kai, SUN Yu, JIA Hepeng, ZHU Zhixiong, and HU Fengfeng
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additive friction stir deposition ,microstructure evolution ,material flow characteristics ,mechanical properties change ,Materials of engineering and construction. Mechanics of materials ,TA401-492 - Abstract
The additive friction stir deposition (AFSD) technology is a new solid-state additive manufacturing technology. The metal bars, powders, and wires are used as feedstock. During the additive process, the friction heat generated by the friction between feedstock and the plate and the plastic deformation heat generated by the severe deformation of feedstock form a viscoplastic deposition layer. The deposition layer is stacked layer by layer to form three-dimensional parts. Because of its solid phase characteristics, it has many advantages over fused-based metal additive technologies and has become a research hotspot in the field of additive manufacturing. In this paper, the latest research progress of AFSD technology at home and abroad was reviewed from four aspects of equipment development, microstructure evolution, material flow characteristics and mechanical properties change. The feasibility of the application of this technology in engineering practice was analyzed and the application prospect in the field of metal coating reinforcement for material repair parts of additive manufacturing was forecasted. Finally, it was pointed out that the heat generation mechanism, material flow characteristics, auxiliary optimization process, and intelligent equipment development are the future research directions.
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- 2023
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15. Knowledge graph analysis of current situation and trend in Chinese medicine sterilization
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LIAO Xin, WANG Shi, CAI Yuan, LI Penghui, SUN Yu, XU Xinyuan, and PENG Yanmei
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traditional chinese medicine ,sterilization ,citespace ,vosviewer ,knowledge map ,Nuclear and particle physics. Atomic energy. Radioactivity ,QC770-798 ,Medical physics. Medical radiology. Nuclear medicine ,R895-920 - Abstract
Traditional Chinese medicine (TCM) is applied in various forms, such as decoction pieces, raw powder, extract, and patent Chinese medicine, etc. Controlling exogenous microbial contamination, ensuring the safety and effectiveness of traditional Chinese medicine, and selecting the appropriate sterilization technology are the key factors regarding its use. In this study, the literature on sterilization of TCM published from 2001 to 2021 was retrieved from CNKI, Wanfang, VIP, and Web of Science. Subsequently, visualization analysis software named VOSviewer and CiteSpace were used to analyze the application status and trend in TCM sterilization methods in the past 20 years. After screening was performed, 322 studies were included. The journal that published the highest number of studies on TCM sterilization was Electromechanical Information. The author's cooperative network analysis found that the Chinese medicine sterilization field mainly formed the China Institute for Food and Drug Control and Guangzhou Institute for Drug Control and other core research teams. Keywords in the literature show that the research on TCM sterilization of traditional Chinese medicine mainly focuses on irradiation, microwave, preparation process, active ingredients, drying, fingerprint, etc. The advantages and disadvantages of different sterilization technologies and their suitable scopes, combined with the future development trend in TCM sterilization, were comprehensively discussed for in-depth analysis, to provide a reference for researchers in selecting appropriate sterilization methods. To further promote the scientific development of TCM sterilization, the authors propose that TCM sterilization should be closely combined with technology, equipment, and policy in the future to facilitate rapid modernization of TCM.
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- 2022
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16. Application of refined nursing management in complete denture prosthodontics for elderly patients with low and flat alveolar ridge (精细化护理在牙槽嵴低平老年患者全口义齿修复中的作用)
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TANG Youjia (汤有佳), YAN Tong (晏桐), CAI Wen (蔡文), SUN Yu (孙雨), and LU Jinxin (卢金鑫)
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denture prosthodontics ,refined nursing management ,alveolar ridge ,comfort ,义齿修复 ,精细化护理 ,牙槽嵴 ,舒适度 ,Nursing ,RT1-120 - Abstract
Objective To investigate the effect of refined nursing management in complete denture prosthodontics for elderly patients with low and flat alveolar ridge. Methods The clinical data of 44 elderly patients with low and flat alveolar ridge requiring complete denture prosthodontics were retrospectively analyzed. All patients received the refined nursing management after admission. The condition of denture restoration was evaluated. Results The dental restoration was not ideal in 17 patients wearing complete denture for the first time. The Satisfaction with return visit was 95. 45%(42/44) and 100. 00%(44/44) at 1 month and 3 months after discharge, respectively. Conclusion The effect of adopting refined nursing management for elderly patients with low alveolar ridge is very remarkable, with high satisfaction with nursing service mode and attitude, which has clinical promotion value. (目的 探讨精细化护理在牙槽嵴低平老年患者全口义齿修复中的应用效果。方法 回顾性分析44例牙槽嵴低平需要进行全口义齿修复的老年患者的临床资料, 患者入院后均开展精细化护理干预, 观察患者义齿修复情况。结果 44例患者中, 修复效果不佳者仅17例, 均为全口义齿初戴的患者。患者1、3个月复诊满意度分别为95. 45%(42/44)和100. 00%(44/44)。结论 精细化护理的应用有助于提高牙槽嵴低平老年患者全口义齿修复效果, 提升患者护理满意度。)
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- 2022
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17. Hepatitis C virus co-infection and influencing factors among newly reported HIV concordant couples in Dehong Prefecture of Yunnan Province from 2016 to 2019
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LI Yanling, SUN Yu, CAO Yanfen, WANG Jibao, WANG Yikui, DUAN Xing, YANG Jin, XIANG Lifen, GAO Jie, YANG Yuecheng, YE Runhua, HE Na, DING Yingying, and DUAN Song
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hiv ,hiv concordant couple ,hepatitis c virus ,co-infection ,influencing factor ,Medicine - Abstract
ObjectiveTo determine the characteristics and influencing factors of hepatitis C virus (HCV) co-infection among HIV concordant couples in Dehong Prefecture.MethodsUsing the data of newly reported HIV concordant couples in Dehong Prefecture from 2016 to 2019, we collected the demographic characteristics, exposure history, and HCV infection to determine the characteristics of HCV co-infection among HIV concordant couples.ResultsAmong the 160 HIV concordant couples included in the study, 46 (28.8%) males and 14 (8.8%) females were co-infected with HCV. The prevalence of HIV-HCV co-infection was higher among the male spouses who were diagnosed less than 40, Jingpo ethnic, Burmese, illiteracy, farmers, and intravenous drug users. In contrast, the prevalence of HIV-HCV co-infection was higher among the female spouses who were diagnosed less than 40, Jingpo ethnic, and Burmese. Logistic regression analysis among male spouses showed that the Jingpo ethnic and intravenous drug users had higher risk of HCV co-infection.ConclusionHIV concordant couples in Dehong Prefecture have high prevalence of HIV-HCV co-infection. Effective intervention strategies should be developed based on ethnic-specific factors and exposure characteristics among male and female spouses of HIV concordant couples.
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- 2022
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18. Artesunate, as an Hsp90 inhibitor, inhibits the proliferation of Burkitt’s lymphoma cells by inhibiting AKT and ERK
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Li Yuan-Ce, Zhang Qi, Zhang Hong-Yang, Wang Yan-Wen, Sun Yu-Mei, Yang Bi-Juan, and Yin Jun-Lin
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artesunate ,Hsp90 ,client protein ,lymphoma ,PLGA-PEG ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Introduction: Artesunate, a derivative of artemisinin, has anti-malarial effects, and in recent years has also been reported to have anti-tumor activity. However, its anti-tumor mechanisms are not well understood.Methods: In this study, we focused on the targeting of Hsp90 by artesunate to inhibit tumor cell proliferation, which we examined using immunoprecipitation, a proliferation assay, flow cytometry, western blotting, a tumor xenograft animal model, and immunohistochemistry. Furthermore, to examine the tumor-suppressive effects of artesunatein nude mice, we used artesunate-loaded PLGA-PEG nanoparticles.Results: The binding of artesunate to Hsp90 was found to reduce the expression of its client proteins AKT, ERK, p-AKT, p-ERK, and EGFR, thereby blocking the cell cycle at the G0/G1 → S stage in lymphoma cells and inducing apoptosis. In addition, the results of tumor xenograft experiments revealed that artesunate reduced the expression of AKT and ERK proteins in tumor tissues, inhibited tumor proliferation, and reduced tumor size and weight. Furthermore, nanoparticle encapsulation was demonstrated to enhance the anti-cancer activity of artesunate.Discussion: We thus established that artesunate inhibits the proliferation of lymphoma cells by targeting the Hsp90 protein, and we accordingly believe that this compound has potential for development as a novelanti-tumor drug.
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- 2023
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19. Physalis pubescens L. branch and leaf extracts inhibit lymphoma proliferation by inducing apoptosis and cell cycle arrest
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Li Yuan-Ce, Pang Yu-Yan, Zhang Qi, Zhang Hong-Yang, Wang Yan-Wen, Sun Yu-Mei, Zeng Guang-Zhi, and Yin Jun-Lin
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Physalis pubescens L. ,lymphoma ,physalin ,cell cycle ,apoptosis ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Physalis pubescens L. is an annual or perennial plant in the family Solanaceae It is used in traditional medicine for treating sore throats, coughs, urinary discomfort, and astringent pain, and externally for pemphigus and eczema in northern China. The proliferation inhibitory activity and mechanisms of the ethyl acetate extract (PHY-EA) from the leaves of Physalis pubescens were investigated. High performance liquid chromatography was used to identify the chemical composition of PHY-EA; sulforhodamine B was used to detect the proliferation inhibitory effect of PHY-EA on MCF-7, CA-46, Hela, HepG2, B16, and other tumor cells; flow cytometry was used to detect the effect of PHY-EA on the lymphoma cell cycle and apoptosis; Western blot was used to detect the expression of the cycle- and apoptosis-related proteins. The expression of Ki-67 and cleaved caspase 3 was detected by immunohistochemistry. The results showed that PHY-EA contained physalin B, physalin O, and physalin L. PHY-EA blocked the cell cycle of G2/M→G0/G1 in lymphoma cells and induced apoptosis in tumor cells. Mouse transplantation tumor experiments showed that PHY-EA had a significant inhibitory effect on mouse transplantation tumors, and the tumor volume and weight were significantly reduced. In conclusion, PHY-EA has a good antiproliferative effect on Burkkit lymphoma, indicating its potential medicinal value.
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- 2023
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20. Visualization and analysis based on Cite Space domestic feedback information recommendation application research
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Zheng Huizhen, Sun Yu, and Luo Xueyi
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Social Sciences - Abstract
This study used Cite Space to analyse the domestic literature on feedback recommendation applications between 2003 and 2023. It is found that domestic scholars have conducted in-depth research in the areas of recommender systems, collaborative filtering, and implicit feedback, focusing on hotspots such as deep learning, matrix decomposition, and user feedback. Although the existing research focuses on improving the efficiency of information access and user satisfaction, the in-depth research on multi-source feedback integration methods still faces challenges. Future research can leverage new technologies such as deep learning to mine more user behaviour data and achieve more accurate personalized recommendations.
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- 2024
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21. Anthocyanin-assisted Agrobacterium infiltration for the rapid evaluation of genome editing efficiencies across multiple plant species
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Xing Sinian, Sun Yu, Li Boshu, Li Hongchao, Zhao Kevin T., Chen Kunling, and Gao Caixia
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genome editing ,Agrobacterium infiltration ,anthocyanin ,transient transformation ,geminivirus replicon ,strawberry ,tomato ,Science ,Engineering (General). Civil engineering (General) ,TA1-2040 - Abstract
CRISPR-based genome editing technologies continue to drive major advances in life sciences. A major challenge for realizing widespread use of genome editing in plants and agriculture is establishing methods that enable the rapid, comprehensive, and precise evaluation of editing technologies using transient methods. Here we report a new and rapid genome editing evaluation method using Agrobacterium infiltration techniques to enable broad-spectrum, simplistic, and precise assessments of genome editing efficiencies. We employed an anthocyanin marker to facilitate visual screenings of genome-edited cells for use in adult strawberry fruits as well as tomato fruits, cotton leaves, and sugar beet leaves. Using this method, we demonstrate the ability to quickly measure genome editing efficiencies mediated by SpCas9, LbCas12a, A3A-PBE, ABE8e, and PPE. This new method will allow researchers to rapidly and easily evaluate genome editing tools across a broad spectrum of plant species, further expediting the development of genome-edited agricultural crops.
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- 2023
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22. Study on related risk factors of pain in de novo Parkinson's disease patients
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GUO Zhi⁃ying, LIU Wei⁃guo, SUN Yu, ZHENG Hui⁃fen, YANG Yu⁃xuan, and ZHAO Ming⁃ming
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parkinson disease ,pain ,risk factors ,logistic models ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Objective To explore the risk factors of pain in de novo Parkinson's disease (PD) patients. Methods A total of 129 de novo PD patients collected from The Affiliated Brain Hospital of Nanjing Medical University from October 2018 to September 2021 were included. According to the Item ⁃17 of the Unified Parkinson's Disease Rating Scale Ⅱ (UPDRSⅡ⁃17th), patients were classified as PD patients without pain (UPDRSⅡ⁃17th was 0, n = 88) and PD patients with pain (UPDRSⅡ⁃17th ≥ 2, n = 41). Mini⁃ Mental State Examination (MMSE) and corrected Montreal Cognitive Assessment (corrected MoCA) were used to assess cognitive function. Meanwhile, Hamilton Depression Rating Scale ⁃24 Items (HAMD ⁃24) was used to assess the depression status and the UPDRSⅢ was used to assess the motor function. The modified version of Hoehn ⁃Yahr staging was used to assess disease severity. The related risk factors of pain in PD patients were analyzed by univariate and multivariate forward Logistic regression. Results The in of pain in PD patients was 31.78% (41/129). Compared with PD without pain group, PD with pain group had lower scores in MMSE (Z = ﹣2.389, P = 0.017) and corrected MoCA (Z = ﹣2.166, P = 0.030), but higher scores in HAMD-24 (Z = ﹣4.024, P = 0.000), UPDRS Ⅲ (Z = ﹣3.639, P = 0.000)and Hoehn-Yahr staging grading (Z = ﹣2.232, P = 0.026). Further analysis of the differences between 2 groups in 7 domains of HAMD-24 showed PD with pain group had higher scores of the anxiety/somatization (Z = ﹣3.707, P = 0.000), mental disorder (Z = ﹣2.519, P = 0.012), retardation symptom (Z = ﹣2.048, P = 0.041), sleep disturbances (Z = ﹣3.484, P = 0.000) and despair symptom (Z = ﹣3.069, P = 0.002) than PD without pain group. Logistic regression analysis showed long duration (OR = 1.354, 95%CI: 1.013-1.809; P = 0.041), high HAMD-24 score (OR = 1.095, 95%CI: 1.033-1.162; P = 0.002) and high UPDRS Ⅲ score (OR = 1.040, 95%CI: 1.001- 1.082; P = 0.046) were risk factors of pain in PD patients. Conclusions Pain in PD has a high incidence in de novo PD patients. Long duration, a depressed state and severe motor symptoms are main risk factors for the development of pain in PD patients.
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- 2022
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23. Balanced Computing Offloading for Selfish IoT Devices in Fog Computing
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Sun Yu-Jie, Wang Hui, and Zhang Cheng-Xiang
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Internet of Things ,fog computing ,computation offloading ,Nash equilibrium ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
Fog computing, which provides low-latency computing services at the network edge, is an enabler for the emerging Internet of Things (IoT) systems. Offloading tasks to the fog that is closer to IoT users for processing has become a means to ensure that tasks are completed quickly. Fog computing cannot only reduce the congestion of the backbone network but also ensure that the task is completed within the specified time. Since fog resources are limited, there will be resource competition among IoT devices. How to quickly and efficiently make an optimal computation offloading decision for individual selfish IoT devices is a fundamental research issue. This article regards the process of multiple IoT devices competing for fog devices as a game and proposes a distributed computation offloading algorithm. The goal is to optimize the balance of computation delay, energy consumption, and cost for fog nodes. The competition between IoT nodes eventually reaches an equilibrium point, that is the Nash equilibrium point. We prove the existence of Nash equilibrium by Weighted Potential Game. In addition, if a large number of IoT devices select the same node for offloading, which will cause the fog node to run out of power and make some networks unable to work normally. Further, causing part of the network to be paralyzed. Therefore, the paper considers the fairness of offloading to extend the network life cycle. A calculation rate adjustment algorithm is designed for the fairness of offloading to ensure that fog nodes do not run out of power and fail. This paper not only fully considers the performance of the IoT device, but also considers the fairness of the fog. Numerous experiments proved the effectiveness of the proposed algorithm.
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- 2022
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24. Effect of cervical suspensory traction in the treatment of severe cervical kyphotic deformity
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Pan Shengfa, Chen Hongyu, Sun Yu, Zhang Fengshan, Zhang Li, Chen Xin, Diao Yinze, Zhao Yanbin, and Zhou Feifei
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severe cervical kyphosis ,traction ,correction ,cervical kyphotic deformity ,effect ,Surgery ,RD1-811 - Abstract
ObjectiveThis study aimed to investigate a new noninvasive traction method on the treatment of severe cervical kyphotic deformity.MethodsThe clinical data of patients with severe cervical kyphosis (Cobb > 40°) treated in Peking University Third Hospital from March 2004 to March 2020 were retrospectively summarized. 46 cases were enrolled, comprising 27 males and 19 females. Fifteen patients underwent skull traction, and 31 patients underwent suspensory traction. Among them, seven used combined traction after one week of suspensory traction. Bedside lateral radiographs were taken every two or three days during traction. The cervical kyphosis angle was measured on lateral radiographs in and extended position at each point in time. The correction rate and evaluated Japanese Orthopedic Association (JOA) scoring for the function of the spinal cord were also measured. The data before and after the operation were compared with paired sample t-test or Wilcoxon signed-rank test.ResultsNo neurological deterioration occurred during the skull traction and the cervical suspensory traction. There were 12 patients with normal neurological function, and the JOA score of the other 34 patients improved from 11.5 ± 2.8 to 15.4 ± 1.8 at the end of follow up (P
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- 2023
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25. Identification of Chemical Constituents of Rheum Lhasa A. J. Liet P. K. Hsiao by Liquid Chromatography-High Resolution Mass Spectrometry
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SUN Yu-ming, XU Meng, LI Wen-hui, WANG Jing, ZHANG Hua, and WANG Yu-lin
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rheum lhasaense a. j. li et p. k. hsiao ,high performance liquid chromatography tandem high resolution mass spectrometry (hplc-hrms) ,tannins ,stilbenes ,butyrophenones ,flavonoids ,Chemistry ,QD1-999 - Abstract
A method of high performance liquid chromatography tandem high resolution mass spectrometry (HPLC-HRMS) was developed for the separation and identification of chemical components in Rheum lhasaense A. J. Li et P. K. Hsiao extract. The separation of compounds was carried out on an Agilent Zorbax SBC18 column (150 mm×4.6 mm×5 μm). The mobile phase was composed with acetonitrile and water with the flow rate of 0.5 mL/min. Electrospray ionisation source (ESI) was used, and Rheum lhasaense A. J. Li et P. K. Hsiao extract was analyzed by MS and MSn full scan at positive and negative ion modes. Through comprehensive analysis of the mass spectra and chromatographic behaviors of the compounds, and comparing with the related data from standard substrates, literatures and database, the main chemical components of Rheum lhasaense A. J. Li et P. K. Hsiao extract were deduced and identified. A total of 63 compounds are identified from Rheum lhasaense A. J. Li et P. K. Hsiao extract at negative ion mode, and 54 compounds are identified at positive ionization mode. These compounds contain 22 tannins, 28 stilbenes, 6 flavonoids, 3 phenylpropanoids, 2 butyrophenones and 2 organic acids, which of 53 compounds are firstly discovered in Rheum lhasaense A. J. Li et P. K. Hsiao. And as reported in the literature, enquinones are not found. This method is fast and sensitive, which not only improves the identification efficiency of trace compounds in Rheum lhasaense A. J. Li et P. K. Hsiao complex matrix, but also achieves the analysis and identification of different types of compounds. It is helpful to provide scientific basis for further clarifying the material basisand quality control standards of Rheum lhasaense A. J. Li et P. K. Hsiao.
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- 2021
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26. Design of Josephson diode based on magnetic impurity
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Sun, Yu-Fei, Mao, Yue, and Sun, Qing-Feng
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Condensed Matter - Superconductivity - Abstract
We theoretically propose a mechanism to realize the superconducting diode effect (SDE): The current can generate a magnetic field, affecting the magnetic moment of magnetic impurity. When the connection region of the Josephson junction is coupled with the magnetic impurity, the supercurrents in positive and negative directions have different influences on the magnetic moment. This results in a phenomenon that the critical supercurrents in these opposite directions are unequal, which is called SDE. We model the Josephson connection region by a quantum dot. Then the critical supercurrents are investigated by the non-equilibrium Green's function method, and we carry out a detailed symmetry analysis on the supercurrent relations. The calculation results confirm that the SDE does exist in this system. Besides, the SDE is significant in a wide parameter space and can be effectively adjusted in various ways. Our design only demands a magnetic impurity and conventional superconductors. The unconventional finite-momentum Cooper pair and spin-orbit coupling are not required, and there is also no need for the existence of chirality or an external magnetic field. Our work provides a universal device structure for the development of superconducting electronics., Comment: 10 pages, 6 figures
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- 2024
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27. DeepMuon: Accelerating Cosmic-Ray Muon Simulation Based on Optimal Transport
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Wang, Ao-Bo, Pan, Chu-Cheng, Dong, Xiang, Sun, Yu-Chang, Hu, Yu-Xuan, Cheng, Ao-Yan, Cai, Hao, and Fan, Xi-Long
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High Energy Physics - Experiment - Abstract
Cosmic muon imaging technology is increasingly being applied in various fields. However, simulating cosmic muons typically requires the rapid generation of a large number of muons and tracking their complex trajectories through intricate structures. This process is highly computationally demanding and consumes significant CPU time. To address these challenges, we introduce DeepMuon, an innovative deep learning model designed to efficiently and accurately generate cosmic muon distributions. In our approach, we employ the inverse Box-Cox transformation to reduce the kurtosis of the muon energy distribution, making it more statistically manageable for the model to learn. Additionally, we utilize the Sliced Wasserstein Distance (SWD) as a loss function to ensure precise simulation of the high-dimensional distributions of cosmic muons. We also demonstrate that DeepMuon can accurately learn muon distribution patterns from a limited set of data, enabling it to simulate real-world cosmic muon distributions as captured by detectors. Compared to traditional tools like CRY, DeepMuon significantly increases the speed of muon generation at sea level. Furthermore, we have developed a pipeline using DeepMuon that directly simulates muon distributions in underwater environments, dramatically accelerating simulations for underwater muon radiography and tomography. For more details on our open-source project, please visit https://github.com/wangab0/deepmuon.
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- 2024
28. MA-RLHF: Reinforcement Learning from Human Feedback with Macro Actions
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Chai, Yekun, Sun, Haoran, Fang, Huang, Wang, Shuohuan, Sun, Yu, and Wu, Hua
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Computer Science - Computation and Language - Abstract
Reinforcement learning from human feedback (RLHF) has demonstrated effectiveness in aligning large language models (LLMs) with human preferences. However, token-level RLHF suffers from the credit assignment problem over long sequences, where delayed rewards make it challenging for the model to discern which actions contributed to successful outcomes. This hinders learning efficiency and slows convergence. In this paper, we propose MA-RLHF, a simple yet effective RLHF framework that incorporates macro actions -- sequences of tokens or higher-level language constructs -- into the learning process. By operating at this higher level of abstraction, our approach reduces the temporal distance between actions and rewards, facilitating faster and more accurate credit assignment. This results in more stable policy gradient estimates and enhances learning efficiency within each episode, all without increasing computational complexity during training or inference. We validate our approach through extensive experiments across various model sizes and tasks, including text summarization, dialogue generation, question answering, and program synthesis. Our method achieves substantial performance improvements over standard RLHF, with performance gains of up to 30% in text summarization and code generation, 18% in dialogue, and 8% in question answering tasks. Notably, our approach reaches parity with vanilla RLHF 1.7x to 2x faster in terms of training time and continues to outperform it with further training. We will make our code and data publicly available at https://github.com/ernie-research/MA-RLHF .
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- 2024
29. Upcycling Instruction Tuning from Dense to Mixture-of-Experts via Parameter Merging
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Hui, Tingfeng, Zhang, Zhenyu, Wang, Shuohuan, Sun, Yu, Wu, Hua, and Su, Sen
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
Mixture-of-Experts (MoE) shines brightly in large language models (LLMs) and demonstrates outstanding performance in plentiful natural language processing tasks. However, existing methods transforming LLMs from dense to MoE face significant data requirements and typically rely on large-scale post-training. In this paper, we propose Upcycling Instruction Tuning (UpIT), a data-efficient approach for tuning a dense pre-trained model into a MoE instruction model. Specifically, we first point out that intermediate checkpoints during instruction tuning of the dense model are naturally suitable for specialized experts, and then propose an expert expansion stage to flexibly achieve models with flexible numbers of experts, where genetic algorithm and parameter merging are introduced to ensure sufficient diversity of new extended experts. To ensure that each specialized expert in the MoE model works as expected, we select a small amount of seed data that each expert excels to pre-optimize the router. Extensive experiments with various data scales and upcycling settings demonstrate the outstanding performance and data efficiency of UpIT, as well as stable improvement in expert or data scaling. Further analysis reveals the importance of ensuring expert diversity in upcycling., Comment: work in progress
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- 2024
30. Orthogonal Finetuning for Direct Preference Optimization
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Yang, Chenxu, Jia, Ruipeng, Gu, Naibin, Lin, Zheng, Chen, Siyuan, Pang, Chao, Yin, Weichong, Sun, Yu, Wu, Hua, and Wang, Weiping
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
DPO is an effective preference optimization algorithm. However, the DPO-tuned models tend to overfit on the dispreferred samples, manifested as overly long generations lacking diversity. While recent regularization approaches have endeavored to alleviate this issue by modifying the objective function, they achieved that at the cost of alignment performance degradation. In this paper, we innovatively incorporate regularization from the perspective of weight updating to curb alignment overfitting. Through the pilot experiment, we discovered that there exists a positive correlation between overfitting and the hyperspherical energy fluctuation. Hence, we introduce orthogonal finetuning for DPO via a weight-Rotated Preference Optimization (RoPO) method, which merely conducts rotational and magnitude-stretching updates on the weight parameters to maintain the hyperspherical energy invariant, thereby preserving the knowledge encoded in the angle between neurons. Extensive experiments demonstrate that our model aligns perfectly with human preferences while retaining the original expressive capacity using only 0.0086% of the trainable parameters, suggesting an effective regularization against overfitting. Specifically, RoPO outperforms DPO by up to 10 points on MT-Bench and by up to 2.8 points on AlpacaEval 2, while enhancing the generation diversity by an average of 6 points.
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- 2024
31. Melting Reduction Auto-Encoder
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SUN Yu, WEI Benzheng, LIU Chuan, ZHANG Kuixing, CONG Jinyu
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auto-encoder (ae) ,feature extraction ,melting reduction auto-encoder (mrae) ,ablation network structure ,loss function of joint reconstruction ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Auto-encoder (AE) is one of the simple and widely used unsupervised feature extraction algorithms of deep learning. Existing automatic encoders for image feature extraction remain some problems such as insufficient feature extraction and excessive model parameters, etc. Aiming at above problems, MRAE (melting reduction auto-encoder) is proposed for image feature extraction in this paper. Firstly, an “ablation network structure” is proposed in the algorithm. It can realize feature enrichment through feature cross fusion in the encoder and reduce feature loss and parameters of model by optimizing the decoding structure in the decoder. Secondly, a joint reconstruction loss function is designed. It calculates the reconstruction loss between feature layers to increase the relationship between feature layers and avoid the prematurity of the model. The experimental results show that the accuracy of the feature extracted by MRAE using different classifiers, such as SVM (support vector machine), K-means, and CART (classification and regression tree), is more than 97% on lung CT image datasets. The accuracy of the feature extracted by MRAE using fully connection is more than 90% on the CvD (cats vs. dogs) dataset.
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- 2021
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32. Preparation and tribological property of nano-G/Fe3O4 composites
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YANG Li-he, CHEN Xu-wang, ZHANG Jian-guo, and SUN Yu-de
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g/fe3o4 ,magnetic composite material ,lubricant additive ,tribological property ,Materials of engineering and construction. Mechanics of materials ,TA401-492 - Abstract
Graphene loaded ferric oxide (G/Fe3O4) composites were prepared by chemical modification using graphene and nano-Fe3O4 as raw materials. The composites were characterized by transmission electron microscope, X-ray diffractometer and Fourier infrared spectrometer, and G/Fe3O4 composites were added to SN 5W-30 lubricating oil, and the dispersion stability and tribological properties of composites in lubricating oil were studied by plasma spectrometer and four ball friction tester. The results show that G/Fe3O4 composite materials generated by the co-modification of oleic acid and silane coupling KH570 are better dispersed on the graphene surface than with oleic acid modification alone; precipitation stability experiments show 10 days later,iron content in the lubricating oil is decreased by 48.3% without composite added,iron content is decreased by 39% with oleic acid modified composite added, and iron content is decreased by 31.1% with oleic acid and KH570 jointly modified composite; four-ball experiments show that G/Fe3O4 composites acting as lubricating oil additives have good tribological properties, the use of oleic acid and KH570 joint modification effect is better than the use of oleic acid modification, the maximum card-free bite load PB is increased by 6.5%, the diameter of the mocha is decreased by 4.4% and the coefficient of friction is decreased by 4.8%.
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- 2021
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33. A Lightweight Model of VGG-16 for Remote Sensing Image Classification
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Mu Ye, Ni Ruiwen, Zhang Chang, Gong He, Hu Tianli, Li Shijun, Sun Yu, Zhang Tong, and Guo Ying
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Vgg-16 ,less feature points ,nonlinear correction layer ,zero padding ,Ocean engineering ,TC1501-1800 ,Geophysics. Cosmic physics ,QC801-809 - Abstract
In planetary science, it is an important basic work to recognize and classify the features of topography and geomorphology from the massive data of planetary remote sensing. Therefore, this article proposes a lightweight model based on VGG-16, which can selectively extract some features of remote sensing images, remove redundant information, and recognize and classify remote sensing images. This model not only ensures the accuracy, but also reduces the parameters of the model. According to our experimental results, our model has a great improvement in remote sensing image classification, from the original accuracy of 85%–98% now. At the same time, the model has a great improvement in convergence speed and classification performance. By inputting the remote sensing image data of ultra-low pixels (64 * 64) into our model, we prove that our model still has a high accuracy rate of 95% for the remote sensing image with ultra-low pixels and less feature points. Therefore, the model has a good application prospect in remote sensing image fine classification, very low pixel, and less image classification.
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- 2021
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34. Prevalence and influencing factors of low back pain among nurses in China: a systematic review and meta-analysis
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Wang Dong-Yang and Sun Yu-Yan
- Subjects
low back pain ,nurse ,meta-analysis ,china ,chronic disease ,Nursing ,RT1-120 - Abstract
Low back pain (LBP) is one of the most common occupational injuries that nurses experience in their daily work, which ultimately causes disability or difficulty in performing heavy physical activity. There is scarce information that presents a direct figure about the prevalence of LBP in Chinese nurses.
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- 2021
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35. Sequence-aware Pre-training for Echocardiography Probe Guidance
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Jiang, Haojun, Sun, Zhenguo, Sun, Yu, Jia, Ning, Li, Meng, Luo, Shaqi, Song, Shiji, and Huang, Gao
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence - Abstract
Cardiac ultrasound probe guidance aims to help novices adjust the 6-DOF probe pose to obtain high-quality sectional images. Cardiac ultrasound faces two major challenges: (1) the inherently complex structure of the heart, and (2) significant individual variations. Previous works have only learned the population-averaged 2D and 3D structures of the heart rather than personalized cardiac structural features, leading to a performance bottleneck. Clinically, we observed that sonographers adjust their understanding of a patient's cardiac structure based on prior scanning sequences, thereby modifying their scanning strategies. Inspired by this, we propose a sequence-aware self-supervised pre-training method. Specifically, our approach learns personalized 2D and 3D cardiac structural features by predicting the masked-out images and actions in a scanning sequence. We hypothesize that if the model can predict the missing content it has acquired a good understanding of the personalized cardiac structure. In the downstream probe guidance task, we also introduced a sequence modeling approach that models individual cardiac structural information based on the images and actions from historical scan data, enabling more accurate navigation decisions. Experiments on a large-scale dataset with 1.36 million samples demonstrated that our proposed sequence-aware paradigm can significantly reduce navigation errors, with translation errors decreasing by 15.90% to 36.87% and rotation errors decreasing by 11.13% to 20.77%, compared to state-of-the-art methods., Comment: Tech Report
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- 2024
36. Learning to Optimally Stop Diffusion Processes, with Financial Applications
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Dai, Min, Sun, Yu, Xu, Zuo Quan, and Zhou, Xun Yu
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Mathematics - Optimization and Control ,Quantitative Finance - Mathematical Finance ,Quantitative Finance - Pricing of Securities - Abstract
We study optimal stopping for diffusion processes with unknown model primitives within the continuous-time reinforcement learning (RL) framework developed by Wang et al. (2020), and present applications to option pricing and portfolio choice. By penalizing the corresponding variational inequality formulation, we transform the stopping problem into a stochastic optimal control problem with two actions. We then randomize controls into Bernoulli distributions and add an entropy regularizer to encourage exploration. We derive a semi-analytical optimal Bernoulli distribution, based on which we devise RL algorithms using the martingale approach established in Jia and Zhou (2022a), and prove a policy improvement theorem. We demonstrate the effectiveness of the algorithms in pricing finite-horizon American put options and in solving Merton's problem with transaction costs, and show that both the offline and online algorithms achieve high accuracy in learning the value functions and characterizing the associated free boundaries., Comment: 35 pages, 9 figures
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- 2024
37. NACL: A General and Effective KV Cache Eviction Framework for LLMs at Inference Time
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Chen, Yilong, Wang, Guoxia, Shang, Junyuan, Cui, Shiyao, Zhang, Zhenyu, Liu, Tingwen, Wang, Shuohuan, Sun, Yu, Yu, Dianhai, and Wu, Hua
- Subjects
Computer Science - Computation and Language - Abstract
Large Language Models (LLMs) have ignited an innovative surge of AI applications, marking a new era of exciting possibilities equipped with extended context windows. However, hosting these models is cost-prohibitive mainly due to the extensive memory consumption of KV Cache involving long-context modeling. Despite several works proposing to evict unnecessary tokens from the KV Cache, most of them rely on the biased local statistics of accumulated attention scores and report performance using unconvincing metric like perplexity on inadequate short-text evaluation. In this paper, we propose NACL, a general framework for long-context KV cache eviction that achieves more optimal and efficient eviction in a single operation during the encoding phase. Due to NACL's efficiency, we combine more accurate attention score statistics in PROXY TOKENS EVICTION with the diversified random eviction strategy of RANDOM EVICTION, aiming to alleviate the issue of attention bias and enhance the robustness in maintaining pivotal tokens for long-context modeling tasks. Notably, our method significantly improves the performance on short- and long-text tasks by 80% and 76% respectively, reducing KV Cache by up to 50% with over 95% performance maintenance. The code is available at https://github.com/PaddlePaddle/Research/tree/master/NLP/ACL2024-NACL., Comment: Accepted by ACL 2024 (main conference, long paper)
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- 2024
38. Automated Sperm Morphology Analysis Based on Instance-Aware Part Segmentation
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Chen, Wenyuan, Song, Haocong, Dai, Changsheng, Jiang, Aojun, Shan, Guanqiao, Liu, Hang, Zhou, Yanlong, Abdalla, Khaled, Dhanani, Shivani N, Moosavi, Katy Fatemeh, Pathak, Shruti, Librach, Clifford, Zhang, Zhuoran, and Sun, Yu
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
Traditional sperm morphology analysis is based on tedious manual annotation. Automated morphology analysis of a high number of sperm requires accurate segmentation of each sperm part and quantitative morphology evaluation. State-of-the-art instance-aware part segmentation networks follow a "detect-then-segment" paradigm. However, due to sperm's slim shape, their segmentation suffers from large context loss and feature distortion due to bounding box cropping and resizing during ROI Align. Moreover, morphology measurement of sperm tail is demanding because of the long and curved shape and its uneven width. This paper presents automated techniques to measure sperm morphology parameters automatically and quantitatively. A novel attention-based instance-aware part segmentation network is designed to reconstruct lost contexts outside bounding boxes and to fix distorted features, by refining preliminary segmented masks through merging features extracted by feature pyramid network. An automated centerline-based tail morphology measurement method is also proposed, in which an outlier filtering method and endpoint detection algorithm are designed to accurately reconstruct tail endpoints. Experimental results demonstrate that the proposed network outperformed the state-of-the-art top-down RP-R-CNN by 9.2% [AP]_vol^p, and the proposed automated tail morphology measurement method achieved high measurement accuracies of 95.34%,96.39%,91.2% for length, width and curvature, respectively., Comment: Accepted to ICRA 2024
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- 2024
39. Spatial-Temporal Attention Model for Traffic State Estimation with Sparse Internet of Vehicles
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Xue, Jianzhe, Yuan, Dongcheng, Sun, Yu, Zhang, Tianqi, Xu, Wenchao, Zhou, Haibo, Xuemin, and Shen
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
The growing number of connected vehicles offers an opportunity to leverage internet of vehicles (IoV) data for traffic state estimation (TSE) which plays a crucial role in intelligent transportation systems (ITS). By utilizing only a portion of IoV data instead of the entire dataset, the significant overheads associated with collecting and processing large amounts of data can be avoided. In this paper, we introduce a novel framework that utilizes sparse IoV data to achieve cost-effective TSE. Particularly, we propose a novel spatial-temporal attention model called the convolutional retentive network (CRNet) to improve the TSE accuracy by mining spatial-temporal traffic state correlations. The model employs the convolutional neural network (CNN) for spatial correlation aggregation and the retentive network (RetNet) based on the attention mechanism to extract temporal correlations. Extensive simulations on a real-world IoV dataset validate the advantage of the proposed TSE approach in achieving accurate TSE using sparse IoV data, demonstrating its cost effectiveness and practicality for real-world applications., Comment: need further improvement
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- 2024
40. Learning to (Learn at Test Time): RNNs with Expressive Hidden States
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Sun, Yu, Li, Xinhao, Dalal, Karan, Xu, Jiarui, Vikram, Arjun, Zhang, Genghan, Dubois, Yann, Chen, Xinlei, Wang, Xiaolong, Koyejo, Sanmi, Hashimoto, Tatsunori, and Guestrin, Carlos
- Subjects
Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language - Abstract
Self-attention performs well in long context but has quadratic complexity. Existing RNN layers have linear complexity, but their performance in long context is limited by the expressive power of their hidden state. We propose a new class of sequence modeling layers with linear complexity and an expressive hidden state. The key idea is to make the hidden state a machine learning model itself, and the update rule a step of self-supervised learning. Since the hidden state is updated by training even on test sequences, our layers are called Test-Time Training (TTT) layers. We consider two instantiations: TTT-Linear and TTT-MLP, whose hidden state is a linear model and a two-layer MLP respectively. We evaluate our instantiations at the scale of 125M to 1.3B parameters, comparing with a strong Transformer and Mamba, a modern RNN. Both TTT-Linear and TTT-MLP match or exceed the baselines. Similar to Transformer, they can keep reducing perplexity by conditioning on more tokens, while Mamba cannot after 16k context. With preliminary systems optimization, TTT-Linear is already faster than Transformer at 8k context and matches Mamba in wall-clock time. TTT-MLP still faces challenges in memory I/O, but shows larger potential in long context, pointing to a promising direction for future research.
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- 2024
41. Structure-aware World Model for Probe Guidance via Large-scale Self-supervised Pre-train
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Jiang, Haojun, Li, Meng, Sun, Zhenguo, Jia, Ning, Sun, Yu, Luo, Shaqi, Song, Shiji, and Huang, Gao
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence - Abstract
The complex structure of the heart leads to significant challenges in echocardiography, especially in acquisition cardiac ultrasound images. Successful echocardiography requires a thorough understanding of the structures on the two-dimensional plane and the spatial relationships between planes in three-dimensional space. In this paper, we innovatively propose a large-scale self-supervised pre-training method to acquire a cardiac structure-aware world model. The core innovation lies in constructing a self-supervised task that requires structural inference by predicting masked structures on a 2D plane and imagining another plane based on pose transformation in 3D space. To support large-scale pre-training, we collected over 1.36 million echocardiograms from ten standard views, along with their 3D spatial poses. In the downstream probe guidance task, we demonstrate that our pre-trained model consistently reduces guidance errors across the ten most common standard views on the test set with 0.29 million samples from 74 routine clinical scans, indicating that structure-aware pre-training benefits the scanning., Comment: Accepted by MICCAI 2024 ASMUS Workshop
- Published
- 2024
42. Cardiac Copilot: Automatic Probe Guidance for Echocardiography with World Model
- Author
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Jiang, Haojun, Sun, Zhenguo, Jia, Ning, Li, Meng, Sun, Yu, Luo, Shaqi, Song, Shiji, and Huang, Gao
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Artificial Intelligence ,Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Robotics - Abstract
Echocardiography is the only technique capable of real-time imaging of the heart and is vital for diagnosing the majority of cardiac diseases. However, there is a severe shortage of experienced cardiac sonographers, due to the heart's complex structure and significant operational challenges. To mitigate this situation, we present a Cardiac Copilot system capable of providing real-time probe movement guidance to assist less experienced sonographers in conducting freehand echocardiography. This system can enable non-experts, especially in primary departments and medically underserved areas, to perform cardiac ultrasound examinations, potentially improving global healthcare delivery. The core innovation lies in proposing a data-driven world model, named Cardiac Dreamer, for representing cardiac spatial structures. This world model can provide structure features of any cardiac planes around the current probe position in the latent space, serving as an precise navigation map for autonomous plane localization. We train our model with real-world ultrasound data and corresponding probe motion from 110 routine clinical scans with 151K sample pairs by three certified sonographers. Evaluations on three standard planes with 37K sample pairs demonstrate that the world model can reduce navigation errors by up to 33\% and exhibit more stable performance., Comment: Accepted by MICCAI2024
- Published
- 2024
43. DHA: Learning Decoupled-Head Attention from Transformer Checkpoints via Adaptive Heads Fusion
- Author
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Chen, Yilong, Zhang, Linhao, Shang, Junyuan, Zhang, Zhenyu, Liu, Tingwen, Wang, Shuohuan, and Sun, Yu
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language - Abstract
Large language models (LLMs) with billions of parameters demonstrate impressive performance. However, the widely used Multi-Head Attention (MHA) in LLMs incurs substantial computational and memory costs during inference. While some efforts have optimized attention mechanisms by pruning heads or sharing parameters among heads, these methods often lead to performance degradation or necessitate substantial continued pre-training costs to restore performance. Based on the analysis of attention redundancy, we design a Decoupled-Head Attention (DHA) mechanism. DHA adaptively configures group sharing for key heads and value heads across various layers, achieving a better balance between performance and efficiency. Inspired by the observation of clustering similar heads, we propose to progressively transform the MHA checkpoint into the DHA model through linear fusion of similar head parameters step by step, retaining the parametric knowledge of the MHA checkpoint. We construct DHA models by transforming various scales of MHA checkpoints given target head budgets. Our experiments show that DHA remarkably requires a mere 0.25\% of the original model's pre-training budgets to achieve 97.6\% of performance while saving 75\% of KV cache. Compared to Group-Query Attention (GQA), DHA achieves a 5$\times$ training acceleration, a maximum of 13.93\% performance improvement under 0.01\% pre-training budget, and 4\% relative improvement under 0.05\% pre-training budget., Comment: 10 pages, 9 figures, 3 tables
- Published
- 2024
44. SwdFold:A Reweighting and Unfolding method based on Optimal Transport Theory
- Author
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Pan, Chu-Cheng, Dong, Xiang, Sun, Yu-Chang, Cheng, Ao-Yan, Wang, Ao-Bo, Hu, Yu-Xuan, and Cai, Hao
- Subjects
Physics - Data Analysis, Statistics and Probability ,High Energy Physics - Experiment - Abstract
High-energy physics experiments rely heavily on precise measurements of energy and momentum, yet face significant challenges due to detector limitations, calibration errors, and the intrinsic nature of particle interactions. Traditional unfolding techniques have been employed to correct for these distortions, yet they often suffer from model dependency and stability issues. We present a novel method, SwdFold, which utilizes the principles of optimal transport to provide a robust, model-independent framework to estimate the probability density ratio for data unfolding. It not only unfold the toy experimental event by reweighted simulated data distributions closely with true distributions but also maintains the integrity of physical features across various observables. We can expect it can enable more reliable predictions and comprehensive analyses as a high precision reweighting and unfolding tool in high-energy physics.
- Published
- 2024
45. Study on online soft sensor method of total sugar content in chlorotetracycline fermentation tank
- Author
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Sun Yu-mei, Han Xiang, Zhang Dong-xiang, Sun Qiao-yan, Chen Xiang-guang, Yao Min-pu, Huang Su-yi, Ma De-shou, and Zhou Biao
- Subjects
chlortetracycline fermentation ,total sugar content ,output recursive wavelet neural network ,gaussian process regression ,soft sensor modeling ,Chemistry ,QD1-999 - Abstract
In order to solve the problem that the total sugar content of the chlortetracycline fermentation tank can not be automatically detected online, a prediction method which combines the output recursive wavelet neural network and the Gauss process regression is proposed in this paper. A soft sensor model between the measurable parameters (inputs) and the total sugar content (output) of the chlortetracycline fermentation tank was established. The soft sensor model was trained by self updating algorithm. Based on field data, the accuracy and generalization ability of the soft sensor model were analyzed. It is shown that the prediction accuracy of the combined model proposed in this paper is better than that of other single models. The results demonstrate the superiority of the method, and MRE and RMSE are used to evaluate the performance of the soft sensor model. It shows that the prediction precision of the soft sensor model based on ORWNN-GPR combination is relatively high in the long period of fermentation, and is suitable for on-line prediction of the total sugar content of the chlortetracycline fermentation tank. The soft sensor method can effectively reduce the labor intensity of the analysts and saves the production cost for enterprise.
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- 2020
- Full Text
- View/download PDF
46. Study on the Mechanical Properties and Damage Constitutive Model of Hybrid Fibre- Reinforced EPS Lightweight Aggregate Concrete
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Huang Wei, Miao Xin-Wei, Sun Yu-Jiao, and Reng Shanshan
- Subjects
damage constitutive model ,EPS lightweight aggregate concrete ,hybrid fibre ,polypropylene fibre ,wood fibre ,Engineering (General). Civil engineering (General) ,TA1-2040 - Abstract
The mechanical properties of hybrid fibre (polypropylene and wood)-reinforced expanded polystyrene (EPS) lightweight aggregate concrete was studied under various sand contents. Cubic and prismatic compression tests were carried out, through which the basic mechanical properties and stress-strain curves of the specimens were obtained. Moreover, the microstructures of the fibre-reinforced concrete with different sand proportions were analysed via scanning electron microscopy (SEM). The test results showed that as the sand proportion increased, the cubic compressive strength and prismatic compressive strength of the EPS lightweight aggregate concrete increased. The optimal slump was obtained when the sand ratio was 25%, after which the slump declined. The EPS lightweight aggregate concrete exhibited obvious elastoplastic behaviour during compression, and the corresponding stress-strain curve could be divided into four stages: the elastic stage, strengthening stage, softening stage and collapse platform stage. Moreover, based on the test results and the damage theory and considering the coupling relationship between plasticity and damage, a damage constitutive model was proposed for hybrid fibre-reinforced EPS lightweight aggregate concrete under uniaxial compression.
- Published
- 2020
- Full Text
- View/download PDF
47. Improving stigma and psychosocial outcomes among post-abortion Kenyan women attending private clinics: A randomized controlled trial of a person-centered mobile phone-based intervention.
- Author
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May Sudhinaraset, Amanda Landrian, Sun Yu Cotter, Ginger Golub, James Opot, C Avery Seefeld, Beth Phillips, and Edward Ikiugu
- Subjects
Medicine ,Science - Abstract
ObjectivesThe objective of this study was to evaluate a person-centered abortion care mobile-based intervention on perceived social stigma, social support, mental health and post-abortion care experiences among Kenyan women who received abortion services at private clinics.MethodsThis randomized controlled study enrolled women who obtained an abortion from private clinics in Nairobi county, Kenya and randomized them into one of three study arms: 1) standard of care (follow-up by service provider call center); 2) post-abortion phone follow-up by a peer counselor (a woman who has had an abortion herself and is trained in person-centered abortion care); or 3) post-abortion phone follow-up by a nurse (a nurse who is trained in person-centered abortion care). All participants were followed-up at two- and four-weeks post-abortion to evaluate intervention effects on mental health, social support, and abortion-related stigma scores. A Kruskal-Wallis one-way ANOVA test was used to assess the effect of each intervention compared to the control group. In total, 371 women participated at baseline and were each randomized to the study arms.ResultsUsing Kruskal-Wallis tests, the nurse arm improved mental health scores from baseline to week two; however this was only marginally significant (p = 0.059). The nurse arm also lowered stigma scores from baseline to week four, and this was marginally significant (p = 0.099). No other differences were found between the study arms. This person-centered mobile phone-based intervention may improve mental health and decrease perceived stigma among Kenyan women who received abortion services in private clinics.ConclusionsNurses trained in person-centered abortion care, in particular, may improve women's experiences post-abortion and potentially reduce feelings of shame and stigma and improve mental health in this context.
- Published
- 2022
- Full Text
- View/download PDF
48. An Interscholastic Network To Generate LexA Enhancer Trap Lines in Drosophila
- Author
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Lutz Kockel, Catherine Griffin, Yaseen Ahmed, Lauren Fidelak, Arjun Rajan, Ethan P. Gould, Myles Haigney, Benjamin Ralston, Rex J. Tercek, Lara Galligani, Sagar Rao, Lutfi Huq, Hersh K. Bhargava, Ailis C. Dooner, Emily G. Lemmerman, Ruby F. Malusa, Tran H. Nguyen, Julie S. Chung, Sara M. Gregory, Kiyomasa M. Kuwana, Jonathan T. Regenold, Alexander Wei, Jake Ashton, Patrick Dickinson, Kate Martel, Connie Cai, Carissa Chen, Stephen Price, Jeffrey Qiao, David Shepley, Joanna Zhang, Meghana Chalasani, Khanh Nguyen, August Aalto, ByungJun Kim, Erik Tazawa-Goodchild, Amanda Sherwood, Ahmad Rahman, Sum Ying Celeste Wu, Joel Lotzkar, Serena Michaels, Hillary Aristotle, Antigone Clark, Grace Gasper, Evan Xiang, Frieda Luna Schlör, Melissa Lu, Kate Haering, Julia Friberg, Alyssa Kuwana, Jonathan Lee, Alan Liu, Emma Norton, Leena Hamad, Clara Lee, Dara Okeremi, Harry diTullio, Kat Dumoulin, Sun Yu Gordon Chi, Grayson S. Derossi, Rose E. Horowitch, Elias C. Issa, Dan T. Le, Bryce C. Morales, Ayush Noori, Justin Shao, Sophia Cho, Mai N. Hoang, Ian M. Johnson, Katherine C. Lee, Maria Lee, Elizabeth A. Madamidola, Katrina E. Schmitt, Gabriel Byan, Taeyoung Park, Jonathan Chen, Alexi Monovoukas, Madison J. Kang, Tanner McGowan, Joseph J. Walewski, Brennan Simon, Sophia J. Zu, Gregory P. Miller, Kate B. Fitzpatrick, Nicole Lantz, Elizabeth Fox, Jeanette Collette, Richard Kurtz, Chris Duncan, Ryan Palmer, Cheryl Rotondo, Eric Janicki, Townley Chisholm, Anne Rankin, Sangbin Park, and Seung K. Kim
- Subjects
Drosophila melanogaster ,Enhancer trap ,LexA - LexAop binary expression system ,StanEx ,High School - University genetics course collaboration ,STEM ,Genetics ,QH426-470 - Abstract
Binary expression systems like the LexA-LexAop system provide a powerful experimental tool kit to study gene and tissue function in developmental biology, neurobiology, and physiology. However, the number of well-defined LexA enhancer trap insertions remains limited. In this study, we present the molecular characterization and initial tissue expression analysis of nearly 100 novel StanEx LexA enhancer traps, derived from the StanEx1 index line. This includes 76 insertions into novel, distinct gene loci not previously associated with enhancer traps or targeted LexA constructs. Additionally, our studies revealed evidence for selective transposase-dependent replacement of a previously-undetected KP element on chromosome III within the StanEx1 genetic background during hybrid dysgenesis, suggesting a molecular basis for the over-representation of LexA insertions at the NK7.1 locus in our screen. Production and characterization of novel fly lines were performed by students and teachers in experiment-based genetics classes within a geographically diverse network of public and independent high schools. Thus, unique partnerships between secondary schools and university-based programs have produced and characterized novel genetic and molecular resources in Drosophila for open-source distribution, and provide paradigms for development of science education through experience-based pedagogy.
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- 2019
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- View/download PDF
49. A Skill Vocabulary Normalization Method for Recruitment Webpage Combing Literal and Context Similarity
- Author
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Sun Yu and Jiang Jinde
- Subjects
recruitment webpage ,Bibliography. Library science. Information resources - Abstract
[Purpose/significance] This paper proposes a skill vocabulary normalization method for recruitment webpages, it aims to solve the problem that many English skill word spelling errors exist in the recruitment webpages. [Method/process] The method combines literal similarity and context similarity to measure the similarity of skill word and form a similar skill word network to normalize the skill words in the recruitment webpages. [Result/conclusion] One week’s computer recruitment information was obtained from domestic mainstream recruitment website 51job to evaluate the proposed method. The experiment results show that the proposed method can automatically, accurately and quickly normalize the skill vocabulary in the recruitment webpages.
- Published
- 2018
- Full Text
- View/download PDF
50. Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors
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Wu, Zihui, Sun, Yu, Chen, Yifan, Zhang, Bingliang, Yue, Yisong, and Bouman, Katherine L.
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition ,Statistics - Machine Learning - Abstract
Diffusion models (DMs) have recently shown outstanding capabilities in modeling complex image distributions, making them expressive image priors for solving Bayesian inverse problems. However, most existing DM-based methods rely on approximations in the generative process to be generic to different inverse problems, leading to inaccurate sample distributions that deviate from the target posterior defined within the Bayesian framework. To harness the generative power of DMs while avoiding such approximations, we propose a Markov chain Monte Carlo algorithm that performs posterior sampling for general inverse problems by reducing it to sampling the posterior of a Gaussian denoising problem. Crucially, we leverage a general DM formulation as a unified interface that allows for rigorously solving the denoising problem with a range of state-of-the-art DMs. We demonstrate the effectiveness of the proposed method on six inverse problems (three linear and three nonlinear), including a real-world black hole imaging problem. Experimental results indicate that our proposed method offers more accurate reconstructions and posterior estimation compared to existing DM-based imaging inverse methods., Comment: Accepted to NeurIPS 2024
- Published
- 2024
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