Wenshuo Wang

Anhui University of Science and Technology

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

Ding Zhao

Carnegie Mellon University

Junqiang Xi

Beijing Institute of Technology

Jiacheng Zhu

Carnegie Mellon University

Xiaotian Sun

Fudan University

Shutao Wang

University of Chinese Academy of Sciences

Lai Wei

Xinxiang Medical University

Ye Yang

Nanjing University of Chinese Medicine

Jian Liu

Qingdao Institute of Bioenergy and Bioprocess Technology

Jianwei Gong

Beijing Institute of Technology

Hongyue Tao

Huashan Hospital

Cooperative Institutions

Thermal Technologies (United States)

176

Chinese Academy of Sciences

150

Fudan University

114

Sun Yat-sen University

University of Chinese Academy of Sciences

Huazhong University of Science and Technology

Zhongshan Hospital

Zhejiang University

Chinese Academy of Medical Sciences & Peking Union Medical College

Shanghai Jiao Tong University

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

Ivy-like electrospun block copolymer fibers supported polymer solid electrolytes with wide electrochemical stability window for all-solid-state Li-metal battery

European Polymer Journal (2025)

Shanshan Gao Wenshuo Wang Dayang Yu Pengju Pan Yongzhong Bao

Organic radical battery

Lithium metal

Electrochemical window

10.1016/j.eurpolymj.2025.113808

Cite

Citations (0)

Advances in Polymeric Micelles: Responsive and Targeting Approaches for Cancer Immunotherapy in the Tumor Microenvironment

Pharmaceutics (2023)

Li-Chun Cheng Jiankun Yu Tangna Hao Wenshuo Wang Minjie Wei

In recent years, to treat a diverse array of cancer forms, considerable advancements have been achieved in the field of cancer immunotherapies. However, these therapies encounter multiple challenges in clinical practice, such as high immune-mediated toxicity, insufficient accumulation in cancer tissues, and undesired off-target reactions. To tackle these limitations and enhance bioavailability, polymer micelles present potential solutions by enabling precise drug delivery to the target site, thus amplifying the effectiveness of immunotherapy. This review article offers an extensive survey of recent progress in cancer immunotherapy strategies utilizing micelles. These strategies include responsive and remodeling approaches to the tumor microenvironment (TME), modulation of immunosuppressive cells within the TME, enhancement of immune checkpoint inhibitors, utilization of cancer vaccine platforms, modulation of antigen presentation, manipulation of engineered T cells, and targeting other components of the TME. Subsequently, we delve into the present state and constraints linked to the clinical utilization of polymeric micelles. Collectively, polymer micelles demonstrate excellent prospects in tumor immunotherapy by effectively addressing the challenges associated with conventional cancer immunotherapies.

Cancer Immunotherapy

10.3390/pharmaceutics15112622

Cite

Citations (7)

A linkable signature scheme supporting batch verification for privacy protection in crowd-sensing

Digital Communications and Networks (2023)

Xu Li Gwanggil Jeon Wenshuo Wang Jindong Zhao

The maturity of 5G technology enabled crowd-sensing services to collect multimedia data via wireless network, so it promoted the applications of crowd-sensing services in different fields, but also brings more privacy security challenges, most general of which is privacy leakage. As a privacy protection technology combining data integrity check and identity anonymity, ring signature is widely used in the field of privacy protection. However, introducing signature technology leads to additional signature verification overhead. In the scenario of crowd-sensing, the existing signature schemes have low efficiency in multi-signature verification. Therefore, it is necessary to design an efficient multi-signature verification scheme while ensuring security. In this paper, a batch-verifiable signature scheme is proposed based on the crowd-sensing background, which supports the sensing platform to verify the uploaded multiple signature data efficiently, so as to overcoming the defects of the traditional signature scheme in verifying multiple signatures. In our proposal, a method for linking homologous data was presented, which was valuable for incentive mechanism and data analysis. Simulation results showed that the proposed scheme has good performance in terms of security and efficiency in crowd-sensing applications with a large number of users and data.

Signature (topology)

Security Analysis

Ring signature

Upload

10.1016/j.dcan.2023.02.015

Cite

Citations (0)

Evaluation of a semi-autonomous lane departure correction system using naturalistic driving data

2022 IEEE Intelligent Vehicles Symposium (IV) (2017)

Ding Zhao Wenshuo Wang David J. LeBlanc

Evaluating the effectiveness and benefits of driver assistance systems is essential for improving the system performance. In this paper, we propose an efficient evaluation method for a semi-autonomous lane departure correction system. To achieve this, we apply a bounded Gaussian mixture model to describe drivers' stochastic lane departure behavior learned from naturalistic driving data, which can regenerate departure behaviors to evaluate the lane departure correction system. In the stochastic lane departure model, we conduct a dimension reduction to reduce the computation cost. Finally, to show the advantages of our proposed evaluation approach, we compare steering systems with and without lane departure assistance based on the stochastic lane departure model. The simulation results show that the proposed method can effectively evaluate the lane departure correction system.

10.1109/ivs.2017.7995834

Cite

Citations (4)

Probabilistic Trajectory Prediction for Autonomous Vehicles with Attentive Recurrent Neural Process

arXiv (Cornell University) (2019)

Jiacheng Zhu Shenghao Qin Wenshuo Wang Ding Zhao

Predicting surrounding vehicle behaviors are critical to autonomous vehicles when negotiating in multi-vehicle interaction scenarios. Most existing approaches require tedious training process with large amounts of data and may fail to capture the propagating uncertainty in interaction behaviors. The multi-vehicle behaviors are assumed to be generated from a stochastic process. This paper proposes an attentive recurrent neural process (ARNP) approach to overcome the above limitations, which uses a neural process (NP) to learn a distribution of multi-vehicle interaction behavior. Our proposed model inherits the flexibility of neural networks while maintaining Bayesian probabilistic characteristics. Constructed by incorporating NPs with recurrent neural networks (RNNs), the ARNP model predicts the distribution of a target vehicle trajectory conditioned on the observed long-term sequential data of all surrounding vehicles. This approach is verified by learning and predicting lane-changing trajectories in complex traffic scenarios. Experimental results demonstrate that our proposed method outperforms previous counterparts in terms of accuracy and uncertainty expressiveness. Moreover, the meta-learning instinct of NPs enables our proposed ARNP model to capture global information of all observations, thereby being able to adapt to new targets efficiently.

10.48550/arxiv.1910.08102

Cite

Citations (10)

A Strategy for Precise Treatment of Cardiac Malignant Neoplasms

Scientific Reports (2017)

Wenshuo Wang JinQiang Shen Hongyue Tao Yun Zhao Hui Nian

Abstract The prevalence of cardiac malignant neoplasms in the general population has been shown to be significant higher than what was previously estimated, yet their treatment has remained difficult and effective therapies are lacking. In the current study, we developed a novel thermotherapy in which PEG-functionalized carbon nanotubes were injected into the tumor regions to assist in the targeted delivery of infrared radiation energy with minimal hyperthermic damage to the surrounding normal tissues. In a mouse model of cardiac malignant neoplasms, the injected carbon nanotubes could rapidly induce coagulative necrosis of tumor tissues when exposed to infrared irradiation. In accordance, the treatment was also found to result in a restoration of heart functions and a concomitant increase of survival rate in mice. Taken together, our carbon nanotube-based thermotherapy successfully addressed the difficulty facing conventional laser ablation methods with regard to off-target thermal injury, and could pave the way for the development of more effective therapies against cardiac malignant neoplasms.

10.1038/srep46168

Cite

Citations (2)

Short-Term Outcomes After Transcatheter Aortic Valve Replacement in Predominant Aortic Regurgitation with Left Ventricular Dysfunction

International Heart Journal (2022)

Yuntao Lu Ye Yang Huan Liu Wenshuo Wang Jinmiao Chen

Patients with aortic stenosis and low left ventricular ejection fraction (LVEF) would benefit from transcatheter aortic valve replacement. However, the safety and efficacy of transcatheter aortic valve replacement in patients with aortic regurgitation and left ventricular dysfunction remains unknown.

Valve replacement

10.1536/ihj.21-360

Cite

Citations (1)

Research on a method of wireless sensor network

Haoming Qu S. Li N.-W. Chen Wenshuo Wang Dianzhe Zhao

Today's wireless sensor networks are limited in the computing power, data storage and communication bandwidth of nodes, so the research on ultra-bandwidth wireless sensor network technology, media access control and routing protocol has important application value. An important application of wireless sensor networks is real-time monitoring of mine safety. In this paper, the wireless sensor network method based on real-time system is studied, and the effectiveness of the wireless sensor network technology based on real-time system is studied and verified.

10.1117/12.2675401

Cite

Citations (1)

Shareable Driving Style Learning and Analysis with a Hierarchical Latent Model

arXiv (Cornell University) (2023)

Chaopeng Zhang Wenshuo Wang Zhaokun Chen Jian Zhang Lijun Sun

Driving style is usually used to characterize driving behavior for a driver or a group of drivers. However, it remains unclear how one individual's driving style shares certain common grounds with other drivers. Our insight is that driving behavior is a sequence of responses to the weighted mixture of latent driving styles that are shareable within and between individuals. To this end, this paper develops a hierarchical latent model to learn the relationship between driving behavior and driving styles. We first propose a fragment-based approach to represent complex sequential driving behavior, allowing for sufficiently representing driving behavior in a low-dimension feature space. Then, we provide an analytical formulation for the interaction of driving behavior and shareable driving style with a hierarchical latent model by introducing the mechanism of Dirichlet allocation. Our developed model is finally validated and verified with 100 drivers in naturalistic driving settings with urban and highways. Experimental results reveal that individuals share driving styles within and between them. We also analyzed the influence of personalities (e.g., age, gender, and driving experience) on driving styles and found that a naturally aggressive driver would not always keep driving aggressively (i.e., could behave calmly sometimes) but with a higher proportion of aggressiveness than other types of drivers.

Driving factors

Feature (linguistics)

10.48550/arxiv.2310.15057

Cite

Citations (0)

Transapical transcatheter aortic valve replacement for aortic regurgitation with a second-generation heart valve

Journal of Thoracic and Cardiovascular Surgery (2018)

Huan Liu Ye Yang Wenshuo Wang Da Zhu Lai Wei

Valve replacement

Stroke

Aortic valve regurgitation

10.1016/j.jtcvs.2017.12.150

Cite

Citations (44)