8,648 results on '"FENG HAO"'
Search Results
2. An intelligent control method based on artificial neural network for numerical flight simulation of the basic finner projectile with pitching maneuver
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Yiming Liang, Guangning Li, Min Xu, Junmin Zhao, Feng Hao, and Hongbo Shi
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Numerical virtual flight ,Intelligent control ,BP neural network ,PID ,Moving chimera grid ,Military Science - Abstract
In this paper, an intelligent control method applying on numerical virtual flight is proposed. The proposed algorithm is verified and evaluated by combining with the case of the basic finner projectile model and shows a good application prospect. Firstly, a numerical virtual flight simulation model based on overlapping dynamic mesh technology is constructed. In order to verify the accuracy of the dynamic grid technology and the calculation of unsteady flow, a numerical simulation of the basic finner projectile without control is carried out. The simulation results are in good agreement with the experiment data which shows that the algorithm used in this paper can also be used in the design and evaluation of the intelligent controller in the numerical virtual flight simulation. Secondly, combined with the real-time control requirements of aerodynamic, attitude and displacement parameters of the projectile during the flight process, the numerical simulations of the basic finner projectile’s pitch channel are carried out under the traditional PID(Proportional-Integral-Derivative) control strategy and the intelligent PID control strategy respectively. The intelligent PID controller based on BP(Back Propagation) neural network can realize online learning and self-optimization of control parameters according to the acquired real-time flight parameters. Compared with the traditional PID controller, the concerned control variable overshoot, rise time, transition time and steady state error and other performance indicators have been greatly improved, and the higher the learning efficiency or the inertia coefficient, the faster the system, the larger the overshoot, and the smaller the stability error. The intelligent control method applying on numerical virtual flight is capable of solving the complicated unsteady motion and flow with the intelligent PID control strategy and has a strong promotion to engineering application.
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- 2024
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3. Preparation of meter-scale Cu foils with decimeter grains and the use for the synthesis of graphene films
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Ruitao Jia, Fangzhu Qing, Shurong Wang, Yuting Hou, Changqing Shen, Feng Hao, Yang Yang, Hongwei Zhu, and Xuesong Li
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Graphene ,Single-crystal Cu ,Chemical vapor deposition ,Synthesis ,Materials of engineering and construction. Mechanics of materials ,TA401-492 - Abstract
Chemical vapor deposition (CVD) is the most promising method for the preparation of high-quality and large-area graphene films, especially the epitaxial growth of graphene on large-area single-crystal Cu foils. While single-crystal Cu foils are normally achieved by thermally annealing the commercial polycrystalline Cu foils, their size and therefore the size of graphene films grown on them are limited to the size of the reaction chamber. We report a simple and feasible method to prepare large-area Cu foils with decimeter grains by thermally annealing the rolled-up Cu foils, where the Cu layers are separated by thin porous carbon fiber cloths. The carbon fiber cloths prevent Cu layers from sticking to each other at high temperatures while do not block the gas transportation. In such a way, the utilization efficiency of the reaction chamber is significantly improved, e.g., 0.2 m × (1–2) m Cu foils can be processed even in a 5 cm diameter quartz tube chamber. High-quality graphene films grown on such Cu foils are then demonstrated. This method may be suitable for the annealing of other metal foils to enlarge grain size and the synthesis of other two-dimensional materials on them such as h-BN.
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- 2024
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4. An optimal allocation method of receiving-end power grid energy storage considering demand-side response capability
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FENG Hao, XU Haidong, SUN Feifei, DING Yifan, WANG Cenfeng, WANG Renshun, and JIANG Quanyuan
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demand response ,energy storage substitution ,optimal allocation ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
Receiving-end power grids are characterized by substantial loads and demand-side responsiveness. Considering demand-side response during energy storage allocation can reduce allocation capacity, thereby enhancing the economy and feasibility of the allocation. The paper focuses on energy storage within the receiving-end grid and introduces an energy storage allocation method that takes account of the grid’s demand-side response capacity. This method aims to analyze the potential for replacing energy storage with demand-side response. The optimal allocation of multiple energy storage is achieved by minimizing the storage allocation cost, cost of wind and solar PV generation curtailment, demand response compensation cost, and load shedding cost as the objective functions. The impact of demand-side response on energy storage capacity allocation is analyzed by controlling the capacity and pricing parameters of demand-side response. It is revealed through a numerical analysis that the demand-side response plays a significant role in substituting lithium iron phosphate battery energy storage, and that the pricing parameter of demand-side response exerts a more substantial impact on energy storage capacity allocation.
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- 2023
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5. Social Network, Trust, Approval of President Biden, Risk Perception, and Annual COVID-19 Booster Intention
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Feng Hao and Stephen R. Neely
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Social Sciences ,Sociology (General) ,HM401-1281 - Abstract
The aim of this study is to understand the American public’s attitudes toward the annual coronavirus disease booster vaccination, administered beginning in the fall of 2023. The authors carried out a national survey in the spring of 2023, with 40 percent of respondents saying that they are “very likely” to receive the regular booster when it becomes available. Several underlying predictors are identified through structural equation modeling analyses. People with more vaccine takers in their social circles, greater trust in others, higher approval of President Biden’s performance, and greater perceived risk of the pandemic are more likely to receive regular boosters. The social network has the most considerable influence, with the largest coefficient size after comparing all standardized coefficients. The effect of trust is enhanced through social networks, and there is a combined effect of President Biden’s approval and risk perception. These findings contribute to the literature and have policy implications for leveraging interventions and optimizing the vaccination campaign.
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- 2024
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6. Diffusion probabilistic model based accurate and high-degree-of-freedom metasurface inverse design
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Zhang Zezhou, Yang Chuanchuan, Qin Yifeng, Feng Hao, Feng Jiqiang, and Li Hongbin
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deep learning ,metasurfaces ,inverse design ,diffusion probabilistic model ,Physics ,QC1-999 - Abstract
Conventional meta-atom designs rely heavily on researchers’ prior knowledge and trial-and-error searches using full-wave simulations, resulting in time-consuming and inefficient processes. Inverse design methods based on optimization algorithms, such as evolutionary algorithms, and topological optimizations, have been introduced to design metamaterials. However, none of these algorithms are general enough to fulfill multi-objective tasks. Recently, deep learning methods represented by generative adversarial networks (GANs) have been applied to inverse design of metamaterials, which can directly generate high-degree-of-freedom meta-atoms based on S-parameters requirements. However, the adversarial training process of GANs makes the network unstable and results in high modeling costs. This paper proposes a novel metamaterial inverse design method based on the diffusion probability theory. By learning the Markov process that transforms the original structure into a Gaussian distribution, the proposed method can gradually remove the noise starting from the Gaussian distribution and generate new high-degree-of-freedom meta-atoms that meet S-parameters conditions, which avoids the model instability introduced by the adversarial training process of GANs and ensures more accurate and high-quality generation results. Experiments have proven that our method is superior to representative methods of GANs in terms of model convergence speed, generation accuracy, and quality.
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- 2023
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7. Biden’s approval, record inflation, economic recovery, COVID-19 mortality, and vaccination rate among Americans—A longitudinal study of state-level data from April 2021 to January 2022
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Feng Hao
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COVID-19 vaccination ,Biden’s approval ,Inflation ,Economic recovery ,Mortality ,Panel data ,Medicine - Abstract
The COVID-19 pandemic has brought an unprecedented impact on Americans for over three years. One effective strategy to mitigate the pandemic’s damage lies in the vaccine. This study aims to investigate the effects of state-level predictors that vary month-by-month on changes in vaccination rates. Panel data of state-level indicators are built for all 50 states from April 2021 to January 2022. The dependent variable is the monthly increase in vaccination rate, and the independent variables include measures of Biden’s approval, inflation, economic recovery, and COVID-19 mortality for each month of this study period. Fixed-effects regression is adopted for longitudinal statistical estimation. Findings show that over time Biden’s approval and COVID-19 death are positively associated with the growth in the vaccination rate, while inflation and economic recovery are negatively associated with the vaccination rate. Significant interactions are identified among these predictors. The findings from analyzing panel indicators at the state level complement the current literature dominated by examining cross-sectional data and provide public health officials with fresh insights to promote the vaccine rollout.
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- 2023
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8. Ligand Engineering in Tin-Based Perovskite Solar Cells
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Peizhou Li, Xiangrong Cao, Jingrui Li, Bo Jiao, Xun Hou, Feng Hao, Zhijun Ning, Zuqiang Bian, Jun Xi, Liming Ding, Zhaoxin Wu, and Hua Dong
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Perovskite ,Solar cells ,Lead-free ,Ligand engineering ,Defects ,Stability ,Technology - Abstract
Highlights Systematic summary of ligand engineering in Sn-based perovskite solar cells at the molecular level (oxidation-suppression), crystal structural level (bulk-defect passivation and crystal orientation optimization), and film level (film stability). The classification and composition of ligand engineering in the review are the same as the actual preparation process, which will help researchers to understand the role of ligands in combination with the actual experiment process. Description of ligands focuses on the function of each functional group; the relevant conclusion can be universal.
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- 2023
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9. Establishing an ANO1-Based Cell Model for High-Throughput Screening Targeting TRPV4 Regulators
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Kai Zheng, Jiang Hu, Cheng Hu, Xueying Liu, Yanyan Wang, Haojian Han, Wenzhu Xing, Liu Yang, Junran Zhang, Qiyuan Hong, Feng Hao, and Wenliang Li
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cell model ,TRPV4 ,ANO1 ,high-throughput screening ,drug screening ,YFP-H148Q/I152L ,Organic chemistry ,QD241-441 - Abstract
Transient receptor potential vanilloid 4 (TRPV4) is a widely expressed cation channel that plays an important role in many physiological and pathological processes. However, most TRPV4 drugs carry a risk of side effects. Moreover, existing screening methods are not suitable for the high-throughput screening (HTS) of drugs. In this study, a cell model and HTS method for targeting TRPV4 channel drugs were established based on a calcium-activated chloride channel protein 1 Anoctamin 1 (ANO1) and a double mutant (YFP-H148Q/I152L) of the yellow fluorescent protein (YFP). Patch-clamp experiments and fluorescence quenching kinetic experiments were used to verify that the model could sensitively detect changes in intracellular Ca2+ concentration. The functionality of the TRPV4 cell model was examined through temperature variations and different concentrations of TRPV4 modulators, and the performance of the model in HTS was also evaluated. The model was able to sensitively detect changes in the intracellular Ca2+ concentration and also excelled at screening TRPV4 drugs, and the model was more suitable for HTS. We successfully constructed a drug cell screening model targeting the TRPV4 channel, which provides a tool to study the pathophysiological functions of TRPV4 in vitro.
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- 2024
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10. Diagnosis Disclosure and Peer-to-Peer Information Seeking Among COVID-19–Infected Social Media Users: Survey of US-Based Adults
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Stephen Neely and Feng Hao
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Medicine - Abstract
BackgroundResearch examining online health communities suggests that individuals affected by chronic health conditions can obtain valuable information and social support through participation in peer-to-peer web-based information exchanges, including information sharing and seeking behaviors. The risks and rewards of these same behaviors in the case of acute illnesses, such as COVID-19, are less well understood, though there is reason to believe that individuals with COVID-19 and other acute illnesses may accrue similar benefits. ObjectiveThis study examines the propensity of American adults to disclose and discuss their COVID-19 diagnosis and symptoms on social media while actively infected with the SARS-CoV-2 virus, as well as to engage in peer-to-peer information seeking in order to better understand the illness that they are experiencing. Additionally, this study seeks to identify the motivations for these behaviors as well as their subsequent impacts on perceived social connectedness and health anxiety in patients with COVID-19. MethodsWe conducted a representative survey of 2500 US-based adults using a sample purchased through an industry-leading market research provider. Participants were selected through a stratified quota sampling approach to ensure a representative sample of the US population. Balanced quotas were determined (by region of the country) for gender, age, race, ethnicity, and political affiliation. Responses were analyzed from 946 participants who reported having an active social media account and testing positive for COVID-19 at least once since the start of the pandemic. ResultsThe results show that only a small portion of social media users (166/946, 18%) chose to disclose and discuss their COVID-19 diagnosis while infected with the virus. However, among those who did, an overwhelming majority (206/251, 82%) said that doing so helped them feel more connected and supported while infected with the virus. A larger percentage of the 946 respondents (n=319, 34%) engaged in peer-to-peer information seeking while infected with COVID-19. Among those who did, a large majority (301/319, 94%) said that doing so was “helpful,” but more than one-third (115/319, 36%) said that reading about other people’s experiences made them “more worried” about having COVID-19, while 33% (108/319) said that it made them “less worried.” Illness severity and political affiliation were significant predictors of both information sharing and seeking. ConclusionsThe findings suggest that the benefits (and risks) associated with online health communities are germane to patients with acute illnesses such as COVID-19. It is recommended that public health officials and health care providers take a proactive approach to cultivating professionally moderated forums supporting peer-to-peer engagement during future outbreaks of COVID-19 and other acute illnesses in order to improve patient outcomes and promote social support and connectedness among infected patients.
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- 2023
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11. Low Trace-Count Template Attacks on 32-bit Implementations of ASCON AEAD
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Shih-Chun You, Markus G. Kuhn, Sumanta Sarkar, and Feng Hao
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ASCON ,power analysis ,template attack ,SASCA ,Computer engineering. Computer hardware ,TK7885-7895 ,Information technology ,T58.5-58.64 - Abstract
The recently adopted Ascon standard by NIST offers a lightweight authenticated encryption algorithm for use in resource-constrained cryptographic devices. To help assess side-channel attack risks of Ascon implementations, we present the first template attack based on analyzing power traces, recorded from an STM32F303 microcontroller board running Weatherley’s 32-bit implementations of Ascon-128. Our analysis combines a fragment template attack with belief-propagation and key-enumeration techniques. The main results are three-fold: (1) we reached 100% success rate from a single trace if the C compiler optimized the unmasked implementation for space, (2) the success rate was about 95% after three traces if the compiler optimized instead for time, and (3) we also attacked a masked version, where the success rate was over 90% with 20 traces of executions with the same key, all after enumerating up to 224 key candidates. These results show that suitably-designed template attacks can pose a real threat to Ascon implementations, even if protected by first-order masking, but we also learnt how some differences in programming style, and even compiler optimization settings, can significantly affect the result.
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- 2023
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12. 4-Terminal Inorganic Perovskite/Organic Tandem Solar Cells Offer 22% Efficiency
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Ling Liu, Hanrui Xiao, Ke Jin, Zuo Xiao, Xiaoyan Du, Keyou Yan, Feng Hao, Qinye Bao, Chenyi Yi, Fangyang Liu, Wentao Wang, Chuantian Zuo, and Liming Ding
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4-Terminal tandem solar cells ,Inorganic perovskite solar cells ,Organic solar cells ,Semitransparent ,Drop-coating ,Technology - Abstract
Highlights 4-Terminal inorganic perovskite/organic tandem solar cells were made by using semi-transparent inorganic perovskite solar cells and narrow-bandgap organic solar cells as the sub-cells, yielding a power conversion efficiency of 22.34%, which is the highest efficiency for inorganic perovskite/organic tandem solar cells. Inorganic perovskite solar cells made by drop-coating (self-spreading) gave much higher power conversion efficiency than the cells made by spin-coating, enabling perovskite/organic tandem solar cells with higher efficiency.
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- 2022
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13. Effect of lncRNA TUG1 on osteogenic/odontogenic differentiation of human dental pulp stem cells
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JIANG Yaxin, ZHANG Hua, SUN Linghan, LI Shiting, and FENG Hao
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long non-coding rna, ,gene silencing, ,taurine upregulated 1, ,human dental pulp stem cells, ,osteogenic differentiation, ,odontoblast differentiation, ,mineralized nodules, ,alkaline phosphatase, ,dentin sialophosphoprotein, ,dentine matrix protein 1, ,runt-related transcription factor 2, ,osteocalcin, ,osteopontin, ,Medicine - Abstract
Objective To explore the effects of long noncoding-RNA (lncRNA) taurine upregulated gene 1 (TUG1) on the proliferation and osteogenic/odontoblast differentiation of human dental pulp stem cells (hDPSCs). Methods hDPSCs were isolated and cultured. The surface antigens CD44, CD45, CD73, CD90, CD133 and STRO-1 were detected by flow cytometry. Alkaline phosphatase (ALP) staining and alizarin red staining were used to identify the ability of cells to differentiate. RNA was collected on Days 0, 7 and 14 of the osteogenic induction of hDPSCs, and qRT-PCR was used to detect the relative expression of TUG1. The hDPSCs were stably transfected with a lentiviral vector containing the TUG1-silenced pSLenti-U6-shRNA(TUG1)-CMV-EGFP-F2A-Puro-WPRE to silence TUG1. The ability of hDPSCs to proliferate was assessed with the CCK-8 method. ALP and alizarin red staining and quantitative detection were used to detect the ALP activity and formation of mineralized nodules of hDPSCs. The expression levels of dentin sialophosphoprotein (DSPP), dentin matrix protein-1 (DMP-1), Runt-associated transcription factor 2 (Runx2), osteocalcin (OCN) and osteopontin (OPN) genes and proteins were measured by qRT-PCR and Western blot. Results The hDPSCs were successfully isolated and cultured, and TUG1 expression was significantly increased during osteogenic differentiation (P
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- 2022
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14. Environmental regulation promotes green development in China: from the perspective of technological innovation
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Feng Hao, Yuan Zang, Bokai Fan, and Yuan Zhang
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green development ,environmental regulation ,technological innovation ,sustainable development ,threshold effects ,General Works - Abstract
Based on panel data of 286 prefecture-level cities in China, this study analyzes the direct impact of environmental regulation and its classified policies on green development, while exploring the indirect effects and threshold effects of technological innovation in the green development effect of environmental regulation. There are four main findings in this study. 1) The impact of environmental regulation on green development follows a U shaped pattern and its mode varies with the type of environmental regulation and the type of cities. 2) Environmental regulation can promote green development through technological innovation, and the industrial structure has a positive moderating effect. 3) Technological innovation is a threshold variable in the impact of environmental regulation on green development: when technological innovation surpasses the threshold value, the green development effect of environmental regulation changes from negative to positive. Therefore, governments should strengthen environmental regulation, effectively play the driving role of different environmental regulation policies, and transform the development driving force through strengthened technological innovation to achieve regional green development.
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- 2023
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15. Isolation and characterization of porcine epidemic diarrhea virus with a novel continuous mutation in the S10 domain
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Xueying Han, Yangkun Liu, Yan Wang, Tiejun Wang, Ning Li, Feng Hao, Lunguang Yao, and Kangkang Guo
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porcine epidemic diarrhea virus ,S10 domain ,continuous mutation ,pathogenicity ,isolation ,Microbiology ,QR1-502 - Abstract
Porcine epidemic diarrhea virus (PEDV), which re-emerged in China in 2010, has caused severe economic losses to the global pig industry. In this study, a PEDV strain, designated PEDV WMB, was isolated from piglets with severe diarrhea on a pig farm in Henan Province of China. Whole-genome sequencing and analysis revealed that the PEDV WMB strain belongs to subtype G2c and has a unique continuous mutation in the S10 antigenic epitope of the S protein. Moreover, the virus-neutralization (VN) test indicated that polyclonal antibodies against the S10 protein of other G1 and G2 strains showed reduced VN reactivity to PEDV WMB. The pathogenicity of PEDV WMB was further investigated in 3 day-old piglets. PEDV infection-related clinical symptoms and morphological lesions were observed and confirmed by histopathological and immunohistochemical examination (IHC). These results illustrated that continuous mutation of the S10 epitope might affect the immunogenicity or pathogenicity of PEDV, providing evidence of the need to monitor the genetic diversity of the virus and develop effective measures to prevent and control PEDV.
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- 2023
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16. Liver transplantation in treatment of hepatocellular carcinoma: management of whole⁃process and progress in treatment
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FENG Hao, LÜ Zicheng, XIA Qiang
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Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 ,Surgery ,RD1-811 - Published
- 2022
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17. Multifunctional anchoring of O‐ligands for high‐performance and stable inverted perovskite solar cells
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Lisha Xie, Xuhong Zhao, Jianwei Wang, Jun Li, Chang Liu, Shurong Wang, Qinye Bao, Mengjin Yang, Xiaobin Niu, Feng Hao, and Ziyi Ge
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additive engineering ,carrier non‐radiative recombination ,defects passivation ,formamidine‐cesium ,inverted perovskite solar cells ,Materials of engineering and construction. Mechanics of materials ,TA401-492 ,Information technology ,T58.5-58.64 - Abstract
Abstract Functional additives have recently been regarded as emerging candidates to improve the performance and stability of perovskite solar cells (PSCs). Herein, nicotinamide (N), 2‐chloronicotinamide (2Cl), and 6‐chloronicotinamide (6Cl) were employed as O‐ligands to facilitate the deposition of MAPbI3 (MA = methylammonium) and MA‐free FA0.88Cs0.12PbI2.64Br0.36 (FA = formamidinium) perovskite films by multifunctional anchoring. By density functional theory (DFT) calculations and ultraviolet photoelectron spectroscopy (UPS) measurements, it is identified that the highest occupied molecular orbital (HOMO) level for additive modified MAPbI3 perovskite could reduce the voltage deficit for hole extraction. Moreover, due to the most favorable charge distribution and significant improvements in charge mobility and defect passivation, the power conversion efficiency (PCE) of 2Cl‐MAPbI3 PSCs was significantly improved from 19.32% to 21.12%. More importantly, the two‐dimensional grazing‐incidence wide‐angle X‐ray scattering (GIWAXS) analysis showed that PbI2 defects were effectively suppressed and femtosecond transient absorption (TA) spectroscopy demonstrated that the trap‐assisted recombination at grain boundaries was effectively inhibited in the 2Cl‐MA‐free film. As a result, the thermally stable 2Cl‐MA‐free PSCs achieved a remarkable PCE of 23.13% with an open‐circuit voltage (Voc) of 1.164 V and an ultrahigh fill factor (FF) of 85.7%. Our work offers a practical strategy for further commercializing stable and efficient PSCs.
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- 2023
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18. GTKO rabbit: A novel animal model for preclinical assessment of decellularized xenogeneic grafts via in situ implantation
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Yufeng Mu, Yu Zhang, Lina Wei, Liang Chen, Feng Hao, Anliang Shao, Shuxin Qu, and Liming Xu
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α-Gal ,GTKO rabbit ,Xenograft ,anti-Gal antibody ,Graft material-specific antibody ,In situ implantation ,Medicine (General) ,R5-920 ,Biology (General) ,QH301-705.5 - Abstract
Wild type (WT) animals cannot be used to objectively assess the immunogenicity of animal tissue-derived biomaterials when used as recipients due to difference with human in α-Gal expression. The purpose of this study is to compare the differences of immunological responses between the GGTA1 gene-knockout (GTKO) rabbits and WT rabbits after implantation with animal tissue-derived biomaterials. The porcine-derived decellularized bone matrix (natural bone material, NBM) and fresh porcine cancellous bone (PCB) were implanted in GTKO rabbits and WT rabbits, respectively, and sham operation was used as control (Con). At 2- and 6-week post-implantation, the related immunological items including antibody levels, serum-mediated cell lysis, cytokines, lymphocyte subtypes, and histopathological changes were assessed.GTKO rabbits exhibited more sensitive immune responses than WT rabbits after PCB implantation, resulted from a significant increase of antibodies (except total antibodies) and cytokines levels, cell lysis ratios, CD4/CD8 proportions, and inflammatory cells infiltration. Immunological factors and inflammatory cells infiltrate in GTKO rabbits after NBM implantation were significantly lower than those in the PCB group. Among the three groups, the NBM group showed the highest contents of new bone formation elements.In conclusion, the GTKO rabbit is a more sensitive alternative model than WT rabbit for preclinical study of xenografts via in situ implantation. Studies on multiple gene-edited animals are also necessary for more comprehensively evaluating xenoimmunologen risks of animal tissue-derived biomaterials in the future. Additionally, the immunogenicity of NBM was remarkably decreased compared to PCB.
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- 2023
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19. Association between vitamin A and asthma: A meta-analysis with trial sequential analysis
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Jun Hu, Jiajia Sang, Feng Hao, and Li Liu
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vitamin A ,retinol ,asthma ,intake ,serum concentration ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Objective: To explore the association between vitamin A (vit A) status and risk of asthma.Methods: PubMed, Web of Science, Embase and the Cochrane Library were electronically searched to identify related studies that reported the association between vit A status and asthma. All databases were searched from inception to November 2022. Two reviewers independently screened literature, extracted data, and assessed risk bias of included studies. Meta-analysis was performed on R software Version 4.1.2 and STATA Version 12.0.Results: A total of 19 observational studies were included. A pooled analysis showed that the serum vit A concentrations in patients with asthma was lower than that in healthy controls (standard mean difference (SMD)= −2.479, 95% confidence interval (CI): −3.719, −.239, 95% prediction interval (PI): −7.510, 2.552), and relatively higher vit A intake in pregnancy was associated with an increased risk of asthma at age 7 years (risk ratio (RR)= 1.181, 95% CI: 1.048, 1.331). No significant correlation was observed between serum vit A levels or vit A intake and the risk of asthma.Conclusion: Our meta-analysis confirms that serum vit A levels are lower in patients with asthma than in healthy controls. Relatively higher vit A intake during pregnancy is associated with an increased risk of asthma at age 7 years. There is no significant correlation between vit A intake and asthma risk in children, nor between serum vit A levels and asthma risk. The effect of vit A may depend on age or developmental stage, diet and genetics. Therefore, further studies are needed to explore the association of vit A and asthma.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/CRD42022358930, identifier CRD42022358930
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- 2023
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20. Spatiotemporal evolution of investment-carbon emission coupling coordination in China’s electricity market
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Yuan Zhang, Hongyuan Zhang, and Feng Hao
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electricity industry ,carbon emission (CE) ,spatiotemporal evolution characteristic ,coupling coordination degree ,gray system analysis ,General Works - Abstract
Promoting the low-carbon development of the electricity market is the key to controlling CO2 emissions and achieving carbon neutrality in China. It requires the coordinated development between investment and carbon emissions in the electricity industry. Based on the panel data on electricity investment and carbon emissions from 2000 to 2019, this study systematically explains the coupling coordination mechanism between electricity investment and carbon emissions. We use the coupling coordination model to calculate the coupling coordination degree of each province. Then, the research uses the GM (1, 1) model to predict the coupling coordination development from 2020 to 2030. The study finds that the development of China’s electricity industry is in good shape. Although the coupling coordination degree has entered barely or primary coordination in most provinces, there are certain fluctuations in recent years; there are spatial differences in coupling and coordinated development among regions: the central region has a high coupling coordination degree, while the eastern and northeastern regions are relatively lagging behind. In the next 10 years, the coupling coordination degree will continue to grow, and all regions will reach the primary coordination. Among them, the central region will reach the intermediate coordination.
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- 2023
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21. Association between high-dose methotrexate-induced toxicity and polymorphisms within methotrexate pathway genes in acute lymphoblastic leukemia
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Meng Xu, Shuangshuang Wu, Yue Wang, Yundong Zhao, Ximin Wang, Changhong Wei, Xueying Liu, Feng Hao, and Cheng Hu
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acute lymphoblastic leukemia ,high-dose methotrexate ,toxicity ,gene polymorphisms ,mutation ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Methotrexate (MTX) is a folic acid antagonist, the mechanism of action is to inhibit DNA synthesis, repair and cell proliferation by decreasing the activities of several folate-dependent enzymes. It is widely used as a chemotherapy drug for children and adults with malignant tumors. High-dose methotrexate (HD-MTX) is an effective treatment for extramedullary infiltration and systemic consolidation in children with acute lymphoblastic leukemia (ALL). However, significant toxicity results in most patients treated with HD-MTX, which limits its use. HD-MTX-induced toxicity is heterogeneous, and this heterogeneity may be related to gene polymorphisms in related enzymes of the MTX intracellular metabolic pathway. To gain a deeper understanding of the differences in toxicity induced by HD-MTX in individuals, the present review examines the correlation between HD-MTX-induced toxicity and the gene polymorphisms of related enzymes in the MTX metabolic pathway in ALL. In this review, we conclude that only the association of SLCO1B1 and ARID5B gene polymorphisms with plasma levels of MTX and MTX-related toxicity is clearly described. These results suggest that SLCO1B1 and ARID5B gene polymorphisms should be evaluated before HD-MTX treatment. In addition, considering factors such as age and race, the other exact predictor of MTX induced toxicity in ALL needs to be further determined.
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- 2022
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22. Role of green energy technology on ecological footprint in China: Evidence from Beijing-Tianjin-Hebei region
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Huiqing Zhao, Yuling Li, Feng Hao, and Tahseen Ajaz
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green energy technology ,ecological footprint ,STIRPAT model ,partial least squares regression ,Beijing-Tianjin-Hebei ,Environmental sciences ,GE1-350 - Abstract
In order to investigate the impact of green energy technology on the environmental sustainability of China, take the Beijing-Tianjin-Hebei region as an example, this paper first calculates the per capita ecological footprint (ef), ecological carrying capacity (ec) and ecological deficit (ed) of China and Beijing-Tianjin-Hebei region from 1990 to 2019 by using the ecological footprint (EF) model, and then uses an expanded STIRPAT model and Partial Least Squares (PLS) regression to explore the impact and importance of green energy technology on EF in China and Beijing-Tianjin-Hebei region. It is found that the ec of China and Beijing-Tianjin-Hebei region is much lower than that of the ef from 1990 to 2019. It is always in the state of ecological deficit, and the sustainable development is faced with severe challenges. Progress in green energy technology can significantly reduce the EF of China and Beijing-Tianjin-Hebei region. The importance of each factor on the EF of China and Beijing-Tianjin-Hebei region is different. The degree of dependence on foreign trade and urbanization rate are important influencing factors of Beijing’s EF. Urbanization rate, per capita GDP, population size, energy consumption per unit GDP and built-up area are the important influencing factors of EF in Tianjin and Hebei. Therefore, to reduce the EF of Beijing, Tianjin and Hebei, it is necessary to accelerate the progress of green energy technology, develop compact ecological city and change people’s consumption patterns.
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- 2022
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23. The crystal structure of (Z)-6-(((5-chloro-2-hydroxyphenyl)amino)methylene)- 4-nitrocyclohexa, C13H9ClN2O4
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Zhang Zhijian, Xiao Xiyuan, Jiang Wujiu, and Feng Hao
- Subjects
2194022 ,Physics ,QC1-999 ,Crystallography ,QD901-999 - Abstract
C13H9ClN2O4, monoclinic, P21/n (no. 14), a = 11.1882(11) Å, b = 8.0672(8) Å, c = 14.0813(15) Å, β = 94.084(2)°, V = 1267.7(2) Å3, Z = 4, R gt(F) = 0.0427, wR ref(F 2) = 0.1104, T = 296(2) K.
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- 2022
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24. Accelerating Communication in Deep Learning Recommendation Model Training with Dual-Level Adaptive Lossy Compression
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Feng, Hao, Zhang, Boyuan, Ye, Fanjiang, Si, Min, Chu, Ching-Hsiang, Tian, Jiannan, Yin, Chunxing, Zhaoxia, Deng, Hao, Yuchen, Balaji, Pavan, Geng, Tong, and Tao, Dingwen
- Subjects
Computer Science - Machine Learning ,Computer Science - Distributed, Parallel, and Cluster Computing - Abstract
DLRM is a state-of-the-art recommendation system model that has gained widespread adoption across various industry applications. The large size of DLRM models, however, necessitates the use of multiple devices/GPUs for efficient training. A significant bottleneck in this process is the time-consuming all-to-all communication required to collect embedding data from all devices. To mitigate this, we introduce a method that employs error-bounded lossy compression to reduce the communication data size and accelerate DLRM training. We develop a novel error-bounded lossy compression algorithm, informed by an in-depth analysis of embedding data features, to achieve high compression ratios. Moreover, we introduce a dual-level adaptive strategy for error-bound adjustment, spanning both table-wise and iteration-wise aspects, to balance the compression benefits with the potential impacts on accuracy. We further optimize our compressor for PyTorch tensors on GPUs, minimizing compression overhead. Evaluation shows that our method achieves a 1.38$\times$ training speedup with a minimal accuracy impact., Comment: accepted by SC '24
- Published
- 2024
25. A Bounding Box is Worth One Token: Interleaving Layout and Text in a Large Language Model for Document Understanding
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Lu, Jinghui, Yu, Haiyang, Wang, Yanjie, Ye, Yongjie, Tang, Jingqun, Yang, Ziwei, Wu, Binghong, Liu, Qi, Feng, Hao, Wang, Han, Liu, Hao, and Huang, Can
- Subjects
Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Multimedia - Abstract
Recently, many studies have demonstrated that exclusively incorporating OCR-derived text and spatial layouts with large language models (LLMs) can be highly effective for document understanding tasks. However, existing methods that integrate spatial layouts with text have limitations, such as producing overly long text sequences or failing to fully leverage the autoregressive traits of LLMs. In this work, we introduce Interleaving Layout and Text in a Large Language Model (LayTextLLM)} for document understanding. In particular, LayTextLLM projects each bounding box to a single embedding and interleaves it with text, efficiently avoiding long sequence issues while leveraging autoregressive traits of LLMs. LayTextLLM not only streamlines the interaction of layout and textual data but also shows enhanced performance in Key Information Extraction (KIE) and Visual Question Answering (VQA). Comprehensive benchmark evaluations reveal significant improvements, with a 27.0% increase on KIE tasks and 24.1% on VQA tasks compared to previous state-of-the-art document understanding MLLMs, as well as a 15.5% improvement over other SOTA OCR-based LLMs on KIE tasks.
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- 2024
26. CaFNet: A Confidence-Driven Framework for Radar Camera Depth Estimation
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Sun, Huawei, Feng, Hao, Ott, Julius, Servadei, Lorenzo, and Wille, Robert
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence ,Electrical Engineering and Systems Science - Signal Processing - Abstract
Depth estimation is critical in autonomous driving for interpreting 3D scenes accurately. Recently, radar-camera depth estimation has become of sufficient interest due to the robustness and low-cost properties of radar. Thus, this paper introduces a two-stage, end-to-end trainable Confidence-aware Fusion Net (CaFNet) for dense depth estimation, combining RGB imagery with sparse and noisy radar point cloud data. The first stage addresses radar-specific challenges, such as ambiguous elevation and noisy measurements, by predicting a radar confidence map and a preliminary coarse depth map. A novel approach is presented for generating the ground truth for the confidence map, which involves associating each radar point with its corresponding object to identify potential projection surfaces. These maps, together with the initial radar input, are processed by a second encoder. For the final depth estimation, we innovate a confidence-aware gated fusion mechanism to integrate radar and image features effectively, thereby enhancing the reliability of the depth map by filtering out radar noise. Our methodology, evaluated on the nuScenes dataset, demonstrates superior performance, improving upon the current leading model by 3.2% in Mean Absolute Error (MAE) and 2.7% in Root Mean Square Error (RMSE)., Comment: Accepted by IROS 2024
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- 2024
27. RoFIR: Robust Fisheye Image Rectification Framework Impervious to Optical Center Deviation
- Author
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Liao, Zhaokang, Feng, Hao, Liu, Shaokai, Zhou, Wengang, and Li, Houqiang
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
Fisheye images are categorized fisheye into central and deviated based on the optical center position. Existing rectification methods are limited to central fisheye images, while this paper proposes a novel method that extends to deviated fisheye image rectification. The challenge lies in the variant global distortion distribution pattern caused by the random optical center position. To address this challenge, we propose a distortion vector map (DVM) that measures the degree and direction of local distortion. By learning the DVM, the model can independently identify local distortions at each pixel without relying on global distortion patterns. The model adopts a pre-training and fine-tuning training paradigm. In the pre-training stage, it predicts the distortion vector map and perceives the local distortion features of each pixel. In the fine-tuning stage, it predicts a pixel-wise flow map for deviated fisheye image rectification. We also propose a data augmentation method mixing central, deviated, and distorted-free images. Such data augmentation promotes the model performance in rectifying both central and deviated fisheye images, compared with models trained on single-type fisheye images. Extensive experiments demonstrate the effectiveness and superiority of the proposed method.
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- 2024
28. Human-free Prompted Based Anomaly Detection: prompt optimization with Meta-guiding prompt scheme
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Chen, Pi-Wei, Lin, Jerry Chun-Wei, Ji, Jia, Yeh, Feng-Hao, and Chen, Chao-Chun
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
Pre-trained vision-language models (VLMs) are highly adaptable to various downstream tasks through few-shot learning, making prompt-based anomaly detection a promising approach. Traditional methods depend on human-crafted prompts that require prior knowledge of specific anomaly types. Our goal is to develop a human-free prompt-based anomaly detection framework that optimally learns prompts through data-driven methods, eliminating the need for human intervention. The primary challenge in this approach is the lack of anomalous samples during the training phase. Additionally, the Vision Transformer (ViT)-based image encoder in VLMs is not ideal for pixel-wise anomaly segmentation due to a locality feature mismatch between the original image and the output feature map. To tackle the first challenge, we have developed the Object-Attention Anomaly Generation Module (OAGM) to synthesize anomaly samples for training. Furthermore, our Meta-Guiding Prompt-Tuning Scheme (MPTS) iteratively adjusts the gradient-based optimization direction of learnable prompts to avoid overfitting to the synthesized anomalies. For the second challenge, we propose Locality-Aware Attention, which ensures that each local patch feature attends only to nearby patch features, preserving the locality features corresponding to their original locations. This framework allows for the optimal prompt embeddings by searching in the continuous latent space via backpropagation, free from human semantic constraints. Additionally, the modified locality-aware attention improves the precision of pixel-wise anomaly segmentation.
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- 2024
29. TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy
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Zhao, Weichao, Feng, Hao, Liu, Qi, Tang, Jingqun, Wei, Shu, Wu, Binghong, Liao, Lei, Ye, Yongjie, Liu, Hao, Li, Houqiang, and Huang, Can
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
Tables contain factual and quantitative data accompanied by various structures and contents that pose challenges for machine comprehension. Previous methods generally design task-specific architectures and objectives for individual tasks, resulting in modal isolation and intricate workflows. In this paper, we present a novel large vision-language model, TabPedia, equipped with a concept synergy mechanism. In this mechanism, all the involved diverse visual table understanding (VTU) tasks and multi-source visual embeddings are abstracted as concepts. This unified framework allows TabPedia to seamlessly integrate VTU tasks, such as table detection, table structure recognition, table querying, and table question answering, by leveraging the capabilities of large language models (LLMs). Moreover, the concept synergy mechanism enables table perception-related and comprehension-related tasks to work in harmony, as they can effectively leverage the needed clues from the corresponding source perception embeddings. Furthermore, to better evaluate the VTU task in real-world scenarios, we establish a new and comprehensive table VQA benchmark, ComTQA, featuring approximately 9,000 QA pairs. Extensive quantitative and qualitative experiments on both table perception and comprehension tasks, conducted across various public benchmarks, validate the effectiveness of our TabPedia. The superior performance further confirms the feasibility of using LLMs for understanding visual tables when all concepts work in synergy. The benchmark ComTQA has been open-sourced at https://huggingface.co/datasets/ByteDance/ComTQA. The source code and model will be released later., Comment: 20 pages, 8 figures
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- 2024
30. MTVQA: Benchmarking Multilingual Text-Centric Visual Question Answering
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Tang, Jingqun, Liu, Qi, Ye, Yongjie, Lu, Jinghui, Wei, Shu, Lin, Chunhui, Li, Wanqing, Mahmood, Mohamad Fitri Faiz Bin, Feng, Hao, Zhao, Zhen, Wang, Yanjie, Liu, Yuliang, Liu, Hao, Bai, Xiang, and Huang, Can
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
Text-Centric Visual Question Answering (TEC-VQA) in its proper format not only facilitates human-machine interaction in text-centric visual environments but also serves as a de facto gold proxy to evaluate AI models in the domain of text-centric scene understanding. Nonetheless, most existing TEC-VQA benchmarks have focused on high-resource languages like English and Chinese. Despite pioneering works to expand multilingual QA pairs in non-text-centric VQA datasets through translation engines, the translation-based protocol encounters a substantial "visual-textual misalignment" problem when applied to TEC-VQA. Specifically, it prioritizes the text in question-answer pairs while disregarding the visual text present in images. Moreover, it fails to address complexities related to nuanced meaning, contextual distortion, language bias, and question-type diversity. In this work, we tackle multilingual TEC-VQA by introducing MTVQA, the first benchmark featuring high-quality human expert annotations across 9 diverse languages, consisting of 6,778 question-answer pairs across 2,116 images. Further, by comprehensively evaluating numerous state-of-the-art Multimodal Large Language Models (MLLMs), including GPT-4o, GPT-4V, Claude3, and Gemini, on the MTVQA dataset, it is evident that there is still a large room for performance improvement, underscoring the value of MTVQA. Additionally, we supply multilingual training data within the MTVQA dataset, demonstrating that straightforward fine-tuning with this data can substantially enhance multilingual TEC-VQA performance. We aspire that MTVQA will offer the research community fresh insights and stimulate further exploration in multilingual visual text comprehension. The project homepage is available at https://bytedance.github.io/MTVQA/.
- Published
- 2024
31. How Green Organizational Strategy and Environmental CSR Affect Organizational Sustainable Performance Through Green Technology Innovation Amid COVID-19
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Maoran Ye, Feng Hao, Mohsin Shahzad, and Hafiz Waqas Kamran
- Subjects
green organizational strategy ,environmental CSR ,organizational sustainable performance ,green technology innovation ,structural equation modeling ,Environmental sciences ,GE1-350 - Abstract
The growth of green-oriented businesses for sustainable development (SD) is no longer optional in the current dynamic world, especially for manufacturing businesses in general. Accordingly, the present study investigates the interlinkages between green organizational strategy (GOS), environmental corporate social responsibility (ECSR), and organizational sustainable performance (OSP) by exploring the key mediating role of green technology innovation (GTI). This study uses a quantitative method to gather data from Chinese manufacturing industries, employing a well-structured questionnaire. Senior and middle-level managers were the intended respondents. From the primary survey, 264 valid responses were gathered. The final data were analyzed using SmartPLS (version 3.3.9) by adopting structural equation modeling (SEM) to examine the associations between the targeted constructs, and the results add to the recent literature by offering a cohesive model of GOS, ECSR, GTI, and OSP. The findings revealed that GOS has a strong positive effect on ECSR, GTI, and OSP. Further, ECSR has a strong positive impact on GTI and OSP. Meanwhile, GTI is a key mediating variable in these relationships, which previous studies have not explored. This study innovatively integrates the three green traits, namely, GOS, ECSR, and GTI, into a comprehensive model that is understudied in existing literature in order to help businesses improve their sustainable competitive advantage. The ultimate aim is to help businesses improve their environmental performance and achieve solid sustainability over the long term.
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- 2022
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32. Determinants of Carbon Dioxide Emissions and Their Peaking Prospect: Evidence From China
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Huiqing Zhao, Jian Hu, Feng Hao, and Hongyuan Zhang
- Subjects
carbon dioxide emissions ,STIRPAT model ,scenario analysis ,peaking carbon dioxide emissions ,China ,Environmental sciences ,GE1-350 - Abstract
In order to examine the key determinants of carbon dioxide emissions and judge whether China’s carbon dioxide emissions can reach their peak value before 2030, this study first uses the extended STIRPAT model to analyze the determinants of China’s carbon dioxide emissions from 1995 to 2019 and then uses the model regression result to forecast the carbon dioxide emissions from 2020 to 2040 under six scenarios to investigate their prospect. It is found that population size, GDP per capita, energy intensity, the share of coal consumption, urbanization level, the share of secondary industry, and investment have significant positive effects on carbon dioxide emissions. Among them, the influence of population size is the biggest and energy intensity is the weakest. China’s carbon dioxide emissions can reach their peak in 2029 under the baseline scenario. Increasing the rate of population growth, energy intensity, and share of coal consumption will push back the peak year. A lower rate of economic growth and share of the secondary industry will bring the peak year forward. Therefore, it is necessary to optimize the industrial structure and energy consumption structure, reduce the energy intensity, and control the population size in order to achieve the goal of peaking carbon dioxide emissions as soon as possible.
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- 2022
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33. The Impact of the COVID-19 Pandemic on China's Airline Industry
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Yuan Zhang, LinChuang Zhu, and Feng Hao
- Subjects
China ,airline industry ,COVID-19 ,full-service airline ,low-cost airline ,stock prices ,Public aspects of medicine ,RA1-1270 - Abstract
BackgroundThe COVID-19 pandemic has posed a great challenge to the development of China's airline industry. Although the existing literature has analyzed the economic impact of the pandemic on the airline industry from different perspectives, it remains to be further studied given the operating characteristics of different types of airlines in China.MethodsUsing a new perspective of heterogeneous airline service models, this study collects high-frequency data on stock prices on six sample airline companies (including both full-service airlines and low-cost airlines) in China over 519 trading days, from August 1, 2019 to September 15, 2021, and identifies structural change points for each company's stock price using the Quandt-Andrews test. The outcome is used to construct an econometric model to quantify the economic impact of the pandemic on different airlines' stock prices under different structural changes.ResultsAll results have passed the Quandt-Andrews test. The impact coefficient of full-service airlines is negative, while that of low-cost airlines is positive. Most of them have passed the test at the significance level of 10%.ConclusionsAll Chinese airlines experienced significant sudden changes in stock prices due to the pandemic, but there are sectoral differences in the order of the sudden changes, with full-service airlines experiencing structural changes much earlier than low-cost airlines. In addition, the impact of the pandemic on stock prices varies across airline types, with a negative impact on full-service airlines and a significant positive effect on most low-cost airlines.
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- 2022
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34. Development of nitrogen efficiency screening system in alfalfa (Medicago sativa L.) and analysis of alfalfa nitrogen efficiency types
- Author
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Xiaojing Liu, Yajiao Zhao, and Feng Hao
- Subjects
Alfalfa ,N efficiency ,Screening system ,NRT2 and AMT1 genes ,Medicine ,Biology (General) ,QH301-705.5 - Abstract
Screening high nitrogen (N) efficiency crops is crucial to utilize resources rationally and reduce N losses. In this research, the biomass, morphological and N-related parameters of 28 alfalfa (Medicago sativa L.) cultivars were assessed at seedling stage. Then, we selected representative materials to compare the changes in stem-leaf dry weight (SDW), total root length (RL) and plant N accumulation (PNA) during whole period. Lastly, we analyzed the expressions of NRT2 and AMT1 genes of alfalfa cultivars. The correlation coefficients between SDW, PDW, RL, RV, SNA, RNA, and PNA were all in the range of 0.522∼0.996. The coefficient of variations of SDW, PDW, RL, RV, SNA and PNA were all more than 20% under low and medium N levels. Though the comprehensive evaluation and cluster analysis, the comprehensive value of LW6010, Gannong NO.5, Longmu 806, Giant 2, Giant 601, Zhaodong, Crown were greater than 0.5 under low and medium N levels; the comprehensive value of Gannong NO.3, Gannong NO.4, Xinjiangdaye, Xinmu NO.1 were less than 0.5 under low N level, but were greater than 0.5 under medium N level. The comprehensive value of Gannong NO.7 Gannong NO.9, Longmu 801, Gongnong NO.3, Elite, Sadie 10, Giant 551 were greater than 0.5 under low N level, but were lesser than 0.5 under medium N level; and those of Longdong, Gannong NO.8, Gongnong NO.1, Reindee, Goldqueen, Weston, Tourists, Giant 6, Algonquin, Sadie 7 were lesser than 0.5 under low and medium N levels. Four N efficiency types of alfalfa cultivars were classified: (1) Very efficient; (2) Efficient; (3) Anti-efficient; and (4) Inefficient.The SDW, RL and PNA of LW6010 were higher than Longdong in each growth period. The expressions of NRT2 and AMT1 genes were highest for LW6010, and lowest for Longdong. So, N efficiency parameters assessed at seedling stage include: SDW, PDW, RL, RV, SNA and PNA. We developed new classification system of N efficiency types of alfalfa cultivars. It proved its effectiveness on 28 alfalfa in China.
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- 2022
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35. Experimental Investigations on the Chemo-Mechanical Coupling in Solid-State Batteries and Electrode Materials
- Author
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Jiaxuan Wang and Feng Hao
- Subjects
solid-state batteries ,electrode materials ,chemo-mechanical coupling ,in situ experiment ,Technology - Abstract
Increasing attention has been paid to the safety and efficiency of batteries due to the rapid development and widespread use of electric vehicles. Solid-state batteries have the advantages of good safety, high energy density, and strong cycle performance, and are recognized as the next generation of power batteries. However, solid-state batteries generate large stress changes due to the volume change of electrode materials during cycling, resulting in pulverization and exfoliation of active materials, fracture of solid-electrolyte interface films, and development of internal cracks in solid electrolytes. As a consequence, the cycle performance of the battery is degraded, or even a short circuit can occur. Therefore, it is important to study the stress changes of solid-state batteries or electrode materials during cycling. This review presents a current overview of chemo-mechanical characterization techniques applied to solid-state batteries and experimental setups. Moreover, some methods to improve the mechanical properties by changing the composition or structure of the electrode materials are also summarized. This review aims to highlight the impact of the stress generated inside solid-state batteries and summarizes a part of the research methods used to study the stress of solid-state batteries, which help improve the design level of solid-state batteries, thereby improving battery performance and safety.
- Published
- 2023
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36. Estimation of Genetic Parameters for Conformation Traits and Milk Production Traits in Chinese Holsteins
- Author
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Xiaoshu Xue, Honghong Hu, Junxing Zhang, Yanfen Ma, Liyun Han, Feng Hao, Yu Jiang, and Yun Ma
- Subjects
Holstein dairy cows ,conformation traits ,milk production traits ,genetic parameters ,Veterinary medicine ,SF600-1100 ,Zoology ,QL1-991 - Abstract
The objective of this study was to explore the genetic parameters of conformation traits and milk production traits in Chinese Holstein cattle and to provide a reference for dairy cattle breeding. We collected the phenotypic data of 23 conformation traits and five milk production traits of Chinese Holsteins and used animal models to estimate the genetic parameters of conformation traits and milk production traits. The estimated heritability of conformation traits ranged from 0.11 (angularity) to 0.37 (heel depth) and the genetic correlation between conformation traits ranged from −0.73 (bone quality and rear leg-rear view) to 0.76 (chest width and loin strength). The heritability of milk production traits ranged from 0.23 (somatic cell score) to 0.50 (305-d milk yield). The estimated values of genetic correlation between conformation traits and milk production traits ranged from −0.56 (heel depth and 305-d milk yield) to 0.57 (udder texture and milk fat percentage). There was a positive genetic correlation between most conformation traits and milk fat percentage, but a weak negative genetic correlation with milk yield. Strengthening the moderately and highly heritable milk production and conformation traits, especially the selection of rear udder traits and body shape total score, will be beneficial in improving the performance of dairy cows.
- Published
- 2022
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37. Effect of compressed pre-deformation on precipitation behavior of 7050 aluminum alloy during non-isothermal aging
- Author
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FENG Hao, FU Dian-bao, CHENG Jia-le, TANG Yin-lin, CHEN Jun-feng, WANG Chen, and ZOU Lin-chi
- Subjects
7050 aluminum alloy ,pre-deformation ,heating aging ,precipitate kinetics ,phase transfor-mation activation energy ,Materials of engineering and construction. Mechanics of materials ,TA401-492 - Abstract
TEM, DSC and other techniques were used to characterize the heating aging precipitation behavior of 7050 aluminum alloy under compression pre-deformation conditions, and the influence law and mechanism of pre-deformation on heating aging precipitation were investigated. The results show that 7050 aluminum alloy can obtain excellent strength and corrosion resistance after pre-deformation heating aging, which can significantly shorten time and reduce energy consumption compared with traditional aging process. The pre-deformation greatly promotes the aging precipitation of 7050 aluminum alloy. The precipitate size increases rapidly as the increase of deformation during the same heating aging process, and its size distribution range increases rapidly too. The pre-deformation during heating aging process not only reduces the phase transformation activation energy of η' and η phases of 7050 aluminum alloy, but also accelerates the diffusion of solute atoms, which intensifies the Ostwald ripening and promotes the growth of precipitates. The calculation results show that the phase transformation activation energy of 7050 aluminum alloy gradually decreases with the increase of deformation. When the deformation amount increases from 0% to 18%, the phase transition activ-ation energy of η' and η phases decreases from 116.0 kJ/mol to 101.7 kJ/mol and 120.8 kJ/mol to 107.5 kJ/mol, respectively.
- Published
- 2020
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38. Toward stable lead halide perovskite solar cells: A knob on the A/X sites components
- Author
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Shurong Wang, Aili Wang, and Feng Hao
- Subjects
Physics ,Photon-electron interaction ,Engineering ,Science - Abstract
Summary: Hybrid lead halide ABX3 perovskite solar cells (PSCs) have emerged as a strong competitor to the traditional solar cells with a certified power conversion efficiency beyond 25% and other remarkable features such as light weight, solution processability, and low manufacturing cost. Further development on the efficiency and stability brings forth increasing attention in the component regulation, such as partial or entire substitution of A/B/X sites by alternative elements with similar size. However, the relationships between composition, property, and performance are poorly understood. Here, the instability of PSCs from the photon-, moisture-, thermal-, and mechanical-induced degradation was first summarized and discussed. In addition, the component regulation from the A/X sites is highlighted from the aspects of band level alignment, charge-carrier dynamics, ion migration, crystallization behavior, residual strain, stoichiometry, and dimensionality control. Finally, the perspectives and future outlooks are highlighted to guide the rational design and practical application of PSCs.
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- 2022
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39. Inhibiting octahedral tilting for stable CsPbI2Br solar cells
- Author
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Aili Wang, Jianwei Wang, Xiaobin Niu, Chuantian Zuo, Feng Hao, and Liming Ding
- Subjects
CsPbI2Br perovskite ,octahedral tilting ,phase stability ,solar cells ,thermal cycle ,Materials of engineering and construction. Mechanics of materials ,TA401-492 ,Information technology ,T58.5-58.64 - Abstract
Abstract The intrinsic phase instability of CsPbI2Br perovskite hinders its development and application in solar cells. Herein, we adopt 1‐butyl‐3‐methylimidazolium hexafluorophosphate (BMIMPF6), a hydrophobic ionic liquid (IL), to improve the phase stability of CsPbI2Br. Density functional theory calculation reveals that the formation energy of CsPbI2Br with BMIMPF6 is reduced, thereby restraining the [PbX6]4− octahedral tilting. The reduced structural distortion and relaxed lattice strain result in improved phase stability of CsPbI2Br. In addition, the interfacial dipole moment increases after introducing BMIMPF6, which facilitates the charge transfer. Consequently, the CsPbI2Br solar cells with BMIMPF6 deliver a power conversion efficiency (PCE) of 16.2% along with excellent stability. The unencapsulated devices with BMIMPF6 maintain 98.9%, 88.6%, and 99.5% of the initial PCEs after 1200 h storage in N2, 1000 h storage in air (30% relative humidity), and 200 thermal cycles (25–100°C), respectively.
- Published
- 2022
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40. Genetic Diversity and Prevalence of Porcine Circovirus Type 2 in China During 2000-2019
- Author
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Ning Li, Jing Liu, Jiali Qi, Feng Hao, Lei Xu, and Kangkang Guo
- Subjects
PCV2 ,nucleotide sequence ,genetic analysis ,cap protein ,vaccine ,Veterinary medicine ,SF600-1100 - Abstract
As the major pathogen for porcine circovirus-associated disease (PCVAD), porcine circovirus type 2 (PCV2) is no longer treated as an emerging virus anymore. The wide distribution of PCV2 infection in China causes huge economic losses in the swine industry. Currently, it is generally believed that PCV2 has eight genotypes (PCV2a to PCV2h), with PCV2a, PCV2b, and PCV2d being widely distributed. To comprehensively explore the genetic diversity and prevalence of PCV2 in China, PCV-2 sequences submitted from China in the GenBank database were retrieved. With a total of 714 PCV2 strains were retrieved, we found that early-submitted PCV2 sequences were mainly collected from coastal provinces in the southeast part of China, which may indicate PCV2 was initially circulating in those regions. From 2002 to 2008, PCV2b was the dominant prevalent genotype in those retrieved sequences. From 2009, PCV2d became the dominant genotype in those sequences, dropping a hint that a potential shift of PCV2b to PCV2d might occur in 2009, which is similar to the patterns at the global level. In addition to the PCV2a, PCV2b, and PCV2d genotypes, novel strains were also characterized. We further revealed that the amino acid sequences consistency of PCV2a Cap is higher than those in other genotypes. Together, this study provided clues for the possible prevalent genotypes and dynamics of genetic diversity in China from 2000 to 2019.
- Published
- 2021
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41. Acupuncture Synergized With Bortezomib Improves Survival of Multiple Myeloma Mice via Decreasing Metabolic Ornithine
- Author
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Mengying Ke, Jinjun Qian, Feng Hao, Xinying Li, Hongjie Wu, Xian Luo, Bin Xu, Chunyan Gu, and Ye Yang
- Subjects
ornithine ,metabolomics ,multiple myeloma ,acupuncture ,ODC1 ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Multiple myeloma (MM) is a hematological malignancy worldwide in urgent need for novel therapeutic strategies. Since Velcade (bortezomib) was approved for the treatment of relapsed/refractory MM in 2003, we have seen considerable improvement in extending MM patient survival. However, most patients are fraught with high recurrence rate and incurability. Acupuncture is known for alleviating patient symptoms and improving the quality of life, but it is not well investigated in MM, especially in combination with bortezomib. In this study, we employed LC-MS and UHPLC-MS together with bioinformatics methods to test serum samples from 5TMM3VT MM murine model mice with four different treatments [control (C) group, bortezomib (V) treatment group, acupuncture (A) group, and combined (VA) group]. MM mice in group VA had longer survival time than mice in group A or group V. Joint pathway analysis indicated the underlying arginine and proline metabolism pathway among the 32 significantly decreased metabolites in group VA. CCK-8 assay and in vivo experiments validated that ornithine, the metabolite of arginine, promoted MM cell proliferation. In addition, gene expression omnibus (GEO) database analysis suggested that MM patients with higher ornithine decarboxylase 1 (ODC1) expression were evidently associated with poor overall survival. In summary, this study demonstrates the synergistic effects of acupuncture and bortezomib on extending the survival of MM model mice and provides potential therapeutic targets in the treatment of MM.
- Published
- 2021
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42. TextSquare: Scaling up Text-Centric Visual Instruction Tuning
- Author
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Tang, Jingqun, Lin, Chunhui, Zhao, Zhen, Wei, Shu, Wu, Binghong, Liu, Qi, Feng, Hao, Li, Yang, Wang, Siqi, Liao, Lei, Shi, Wei, Liu, Yuliang, Liu, Hao, Xie, Yuan, Bai, Xiang, and Huang, Can
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning - Abstract
Text-centric visual question answering (VQA) has made great strides with the development of Multimodal Large Language Models (MLLMs), yet open-source models still fall short of leading models like GPT4V and Gemini, partly due to a lack of extensive, high-quality instruction tuning data. To this end, we introduce a new approach for creating a massive, high-quality instruction-tuning dataset, Square-10M, which is generated using closed-source MLLMs. The data construction process, termed Square, consists of four steps: Self-Questioning, Answering, Reasoning, and Evaluation. Our experiments with Square-10M led to three key findings: 1) Our model, TextSquare, considerably surpasses open-source previous state-of-the-art Text-centric MLLMs and sets a new standard on OCRBench(62.2%). It even outperforms top-tier models like GPT4V and Gemini in 6 of 10 text-centric benchmarks. 2) Additionally, we demonstrate the critical role of VQA reasoning data in offering comprehensive contextual insights for specific questions. This not only improves accuracy but also significantly mitigates hallucinations. Specifically, TextSquare scores an average of 75.1% across four general VQA and hallucination evaluation datasets, outperforming previous state-of-the-art models. 3) Notably, the phenomenon observed in scaling text-centric VQA datasets reveals a vivid pattern: the exponential increase of instruction tuning data volume is directly proportional to the improvement in model performance, thereby validating the necessity of the dataset scale and the high quality of Square-10M.
- Published
- 2024
43. Progressive Multi-modal Conditional Prompt Tuning
- Author
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Qiu, Xiaoyu, Feng, Hao, Wang, Yuechen, Zhou, Wengang, and Li, Houqiang
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
Pre-trained vision-language models (VLMs) have shown remarkable generalization capabilities via prompting, which leverages VLMs as knowledge bases to extract information beneficial for downstream tasks. However, existing methods primarily employ uni-modal prompting, which only engages a uni-modal branch, failing to simultaneously adjust vision-language (V-L) features. Additionally, the one-pass forward pipeline in VLM encoding struggles to align V-L features that have a huge gap. Confronting these challenges, we propose a novel method, Progressive Multi-modal conditional Prompt Tuning (ProMPT). ProMPT exploits a recurrent structure, optimizing and aligning V-L features by iteratively utilizing image and current encoding information. It comprises an initialization and a multi-modal iterative evolution (MIE) module. Initialization is responsible for encoding images and text using a VLM, followed by a feature filter that selects text features similar to image. MIE then facilitates multi-modal prompting through class-conditional vision prompting, instance-conditional text prompting, and feature filtering. In each MIE iteration, vision prompts are obtained from filtered text features via a vision generator, promoting image features to focus more on target object during vision prompting. The encoded image features are fed into a text generator to produce text prompts that are more robust to class shifts. Thus, V-L features are progressively aligned, enabling advance from coarse to exact prediction. Extensive experiments are conducted in three settings to evaluate the efficacy of ProMPT. The results indicate that ProMPT outperforms existing methods on average across all settings, demonstrating its superior generalization and robustness. Code is available at https://github.com/qiuxiaoyu9954/ProMPT.
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- 2024
44. Integration of Self-Supervised BYOL in Semi-Supervised Medical Image Recognition
- Author
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Feng, Hao, Jia, Yuanzhe, Xu, Ruijia, Prasad, Mukesh, Anaissi, Ali, and Braytee, Ali
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
Image recognition techniques heavily rely on abundant labeled data, particularly in medical contexts. Addressing the challenges associated with obtaining labeled data has led to the prominence of self-supervised learning and semi-supervised learning, especially in scenarios with limited annotated data. In this paper, we proposed an innovative approach by integrating self-supervised learning into semi-supervised models to enhance medical image recognition. Our methodology commences with pre-training on unlabeled data utilizing the BYOL method. Subsequently, we merge pseudo-labeled and labeled datasets to construct a neural network classifier, refining it through iterative fine-tuning. Experimental results on three different datasets demonstrate that our approach optimally leverages unlabeled data, outperforming existing methods in terms of accuracy for medical image recognition., Comment: Accepted by ICCS 2024
- Published
- 2024
45. TextCoT: Zoom In for Enhanced Multimodal Text-Rich Image Understanding
- Author
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Luan, Bozhi, Feng, Hao, Chen, Hong, Wang, Yonghui, Zhou, Wengang, and Li, Houqiang
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Computer Science - Computer Vision and Pattern Recognition - Abstract
The advent of Large Multimodal Models (LMMs) has sparked a surge in research aimed at harnessing their remarkable reasoning abilities. However, for understanding text-rich images, challenges persist in fully leveraging the potential of LMMs, and existing methods struggle with effectively processing high-resolution images. In this work, we propose TextCoT, a novel Chain-of-Thought framework for text-rich image understanding. TextCoT utilizes the captioning ability of LMMs to grasp the global context of the image and the grounding capability to examine local textual regions. This allows for the extraction of both global and local visual information, facilitating more accurate question-answering. Technically, TextCoT consists of three stages, including image overview, coarse localization, and fine-grained observation. The image overview stage provides a comprehensive understanding of the global scene information, and the coarse localization stage approximates the image area containing the answer based on the question asked. Then, integrating the obtained global image descriptions, the final stage further examines specific regions to provide accurate answers. Our method is free of extra training, offering immediate plug-and-play functionality. Extensive experiments are conducted on a series of text-rich image question-answering benchmark datasets based on several advanced LMMs, and the results demonstrate the effectiveness and strong generalization ability of our method. Code is available at https://github.com/bzluan/TextCoT.
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- 2024
46. Enhanced Radar Perception via Multi-Task Learning: Towards Refined Data for Sensor Fusion Applications
- Author
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Sun, Huawei, Feng, Hao, Mauro, Gianfranco, Ott, Julius, Stettinger, Georg, Servadei, Lorenzo, and Wille, Robert
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Multimedia ,Electrical Engineering and Systems Science - Image and Video Processing ,Electrical Engineering and Systems Science - Signal Processing - Abstract
Radar and camera fusion yields robustness in perception tasks by leveraging the strength of both sensors. The typical extracted radar point cloud is 2D without height information due to insufficient antennas along the elevation axis, which challenges the network performance. This work introduces a learning-based approach to infer the height of radar points associated with 3D objects. A novel robust regression loss is introduced to address the sparse target challenge. In addition, a multi-task training strategy is employed, emphasizing important features. The average radar absolute height error decreases from 1.69 to 0.25 meters compared to the state-of-the-art height extension method. The estimated target height values are used to preprocess and enrich radar data for downstream perception tasks. Integrating this refined radar information further enhances the performance of existing radar camera fusion models for object detection and depth estimation tasks., Comment: Accepted by IEEE Intelligent Vehicles Symposium (IV 2024)
- Published
- 2024
47. DeepEraser: Deep Iterative Context Mining for Generic Text Eraser
- Author
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Feng, Hao, Wang, Wendi, Liu, Shaokai, Deng, Jiajun, Zhou, Wengang, and Li, Houqiang
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
In this work, we present DeepEraser, an effective deep network for generic text removal. DeepEraser utilizes a recurrent architecture that erases the text in an image via iterative operations. Our idea comes from the process of erasing pencil script, where the text area designated for removal is subject to continuous monitoring and the text is attenuated progressively, ensuring a thorough and clean erasure. Technically, at each iteration, an innovative erasing module is deployed, which not only explicitly aggregates the previous erasing progress but also mines additional semantic context to erase the target text. Through iterative refinements, the text regions are progressively replaced with more appropriate content and finally converge to a relatively accurate status. Furthermore, a custom mask generation strategy is introduced to improve the capability of DeepEraser for adaptive text removal, as opposed to indiscriminately removing all the text in an image. Our DeepEraser is notably compact with only 1.4M parameters and trained in an end-to-end manner. To verify its effectiveness, extensive experiments are conducted on several prevalent benchmarks, including SCUT-Syn, SCUT-EnsText, and Oxford Synthetic text dataset. The quantitative and qualitative results demonstrate the effectiveness of our DeepEraser over the state-of-the-art methods, as well as its strong generalization ability in custom mask text removal. The codes and pre-trained models are available at https://github.com/fh2019ustc/DeepEraser
- Published
- 2024
48. Hot-Casting Large-Grain Perovskite Film for Efficient Solar Cells: Film Formation and Device Performance
- Author
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Kejun Liao, Chengbo Li, Lisha Xie, Yuan Yuan, Shurong Wang, Zhiyuan Cao, Liming Ding, and Feng Hao
- Subjects
Perovskite film ,Hot-casting ,Temperature ,Precursor chemistry ,Grain size ,Technology - Abstract
Abstract Organic–inorganic metal halide perovskite solar cells (PSCs) have recently been considered as one of the most competitive contenders to commercial silicon solar cells in the photovoltaic field. The deposition process of a perovskite film is one of the most critical factors affecting the quality of the film formation and the photovoltaic performance. A hot-casting technique has been widely implemented to deposit high-quality perovskite films with large grain size, uniform thickness, and preferred crystalline orientation. In this review, we first review the classical nucleation and crystal growth theory and discuss those factors affecting the hot-casted perovskite film formation. Meanwhile, the effects of the deposition parameters such as temperature, thermal annealing, precursor chemistry, and atmosphere on the preparation of high-quality perovskite films and high-efficiency PSC devices are comprehensively discussed. The excellent stability of hot-casted perovskite films and integration with scalable deposition technology are conducive to the commercialization of PSCs. Finally, some open questions and future perspectives on the maturity of this technology toward the upscaling deposition of perovskite film for related optoelectronic devices are presented.
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- 2020
- Full Text
- View/download PDF
49. Role of transforming growth factor-β and extracellular regulated protein kinases in lipopolysaccharide-induced osteoblastic differentiation of porcine aortic valve interstitial cells
- Author
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FENG Hao, SHI Qiong, and JIANG Yingjiu
- Subjects
calcific aortic valve disease ,valve interstitial cells ,osteogenic differentiation ,transforming growth factor-β1 ,extracellular regulated protein kinases ,Medicine (General) ,R5-920 - Abstract
Objective To investigate the role of transforming growth factor-β (TGF-β1) and extracellular regulated protein kinases (ERK) in lipopolysaccharide (LPS)-induced osteoblastic differentiation of porcine aortic valve interstitial cells (PVICs). Methods In vitro cultured PVICs were treated with LPS (4 μg/mL) to induce their osteogenic differentiation, and early and late osteogenic differentiation abilities of the cells were assessed using alkaline phosphatase (ALP) staining and Alizarin red S staining. The expression levels of Runx2, OPN and OCN mRNAs in the cells were detected using RT-qPCR, and those of TGF-β1, TGF-βR, Bax, Smad2/3 and ERK1/2 proteins were determined using Western blotting. Results In cultured PVICs, LPS treatment significantly increased alkaline phosphatase activity, deposition of calcium salts, and the expression levels of Runx2, OPN and OCN mRNA (P < 0.01). In addition to the increase of the expression of osteoblastic differentiation markers, the protein expression of TGF-β1, TGF-βR, Smad2/3 and ERK1/2 were also significantly increased in LPS-treated PVICs (P < 0.05); treatment with PD98059, a specific ERK1/2 inhibitor, significantly abolished LPS-induced increase in the protein expression of ERK1/2, Bax, and Runx2 (P < 0.05). Conclusion LPS induces osteoblastic differentiation of PVICs probably by activating TGF-β1/Smads and ERK signaling pathways.
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- 2020
- Full Text
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50. Lateral Pipeline Buckling Detection via Demagnetization and Interior Magnetic Measurement
- Author
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Li Jian, Li Mingze, Huang Xinjing, Feng Hao, and Rui Xiaobo
- Subjects
Pipeline buckling ,detection ,spherical detector ,magnetic field ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
Thermal buckling of subsea pipelines often occurs and seriously threatens pipeline safety. The spherical detector (SD) can realize quasi real-time detection of pipeline buckling owing to its low blockage risk and convenient launch-retrieval deployment. Vertical buckling can be judged by the rolling speed of the SD, while lateral buckling can only be judged by the interior magnetic fields. However, irregular magnetic remanence of the pipeline seriously hinders the magnetic detection of lateral buckling. To against this problem, this paper proposes a method of detecting the lateral pipeline buckling via demagnetization and interior magnetic measurement. It is experimentally demonstrated that demagnetization can remove most of the remanence of the pipeline and make the interior magnetic fields more regular and uniform; After the pipe is demagnetized, both severe and weak lateral bucklings can be sensitively indicated by the single or double peaks of the interior magnetic fields measured by the SD. The interior magnetic fields are also experimentally demonstrated capable of indicating the first and recurring weak buckling through comparing with the previous detection data.
- Published
- 2020
- Full Text
- View/download PDF
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