Risheng Wang

Missouri University of Science and Technology

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Wenyan Liu

Jiangxi Agricultural University

Nadrian C. Seeman

New York University

Shalom J. Wind

Columbia University

Shuo Yang

Shanghai Jiao Tong University

James W. Canary

New York University

Ruojie Sha

New York University

Tao Lei

Shaanxi University of Science and Technology

Asoke K. Nandi

Brunel University of London

Erika Penzo

Molecular Foundry

Fang FengXue

Guangxi Academy of Agricultural Science

Cooperative Institutions

Chinese Academy of Agricultural Sciences

Ministry of Agriculture and Rural Affairs

Missouri University of Science and Technology

Chinese Academy of Sciences

Institute of Vegetables and Flowers

China University of Petroleum, East China

Sun Yat-sen University

Guangxi Academy of Agricultural Science

Fudan University

University of Chinese Academy of Sciences

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MFP‐Net: Multi‐scale feature pyramid network for crowd counting

IET Image Processing (2021)

Tao Lei Dong Zhang Risheng Wang Shuying Li Weijiang Zhang

Abstract Although deep learning has been widely used for dense crowd counting, it still faces two challenges. Firstly, the popular network models are sensitive to scale variance of human head, human occlusions, and complex background due to repeated utilization of vanilla convolution kernels. Secondly, the vanilla feature fusion often depends on summation or concatenation, which ignores the correlation of different features leading to information redundancy and low robustness to background noise. To address these issues, a multi‐scale feature pyramid network (MFP‐Net) for dense crowd counting is proposed in this paper. The proposed MFP‐Net makes two contributions. Firstly, the feature pyramid fusion module is designed that adopts rich convolutions with different depths and scales, not only to expand the receptive field, but also to improve the inference speed of models by using parallel group convolution. Secondly, a feature attention‐aware module is added in the feature fusion stage. The module can achieve local and global information fusion by capturing the importance of the spatial and channel domains to improve model robustness. The proposed MFP‐Net is evaluated on five publicly available datasets, and experiments show that the MFP‐Net not only provides better crowd counting results than comparative models, but also requires fewer parameters.

Pyramid (geometry)

Net (polyhedron)

Feature (linguistics)

10.1049/ipr2.12230

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Citations (8)

Cost effective surface functionalization of gold nanoparticles with a mixed DNA and PEG monolayer for nanotechnology applications

RSC Advances (2017)

Risheng Wang Isabella Bowling Wenyan Liu

We report a cost effective and generally applicable method for co-functionalization of gold nanoparticles with a mixed DNA and PEG polymer layer.

Surface Modification

10.1039/c6ra26791b

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Citations (16)

Crystalline Two‐Dimensional DNA‐Origami Arrays

Angewandte Chemie (2010)

Wenyan Liu Hong Zhong Risheng Wang Nadrian C. Seeman

DNA-Origami im großen Stil: Eine doppellagige DNA-Origamikachel mit zwei orthogonalen Domänen bildete durch Selbstorganisation hoch reguläre 2D-DNA-Anordnungen mit Kantenlängen von 2–3 μm (siehe Schema und AFM-Bild). Diese Größe dürfte vermutlich ausreichen, um Bottom-up-Methoden der Mustererzeugung mit Top-down-Ansätzen zu verknüpfen. Detailed facts of importance to specialist readers are published as "Supporting Information". Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Schema (genetic algorithms)

10.1002/ange.201005911

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Citations (86)

DefED-Net: Deformable Encoder-Decoder Network for Liver and Liver Tumor Segmentation

IEEE Transactions on Radiation and Plasma Medical Sciences (2021)

Tao Lei Risheng Wang Yuxiao Zhang Yong Wan Chang Liu

Deep convolutional neural networks have been widely used for medical image segmentation due to their superiority in feature learning. Although these networks are successful for simple object segmentation tasks, they suffer from two problems for liver and liver tumor segmentation in CT images. One is that convolutional kernels of fixed geometrical structure are unmatched with livers and liver tumors of irregular shapes. The other is that pooling and strided convolutional operations easily lead to the loss of spatial contextual information of images. To address these issues, we propose a deformable encoder-decoder network (DefED-Net) for liver and liver tumor segmentation. The proposed network makes two contributions. The first is that the deformable convolution is used to enhance the feature representation capability of DefED-Net, which can help the network to learn convolution kernels with adaptive spatial structuring information. The second is that we design a Ladder-atrous-spatial-pyramid-pooling module using multi-scale dilation rate (Ladder-ASPP) and apply the module to learn better context information than the atrous spatial pyramid pooling (ASPP) for CT image segmentation. The proposed DefED-Net is evaluated on two public benchmark datasets, the LiTS and the 3DIRCADb. Experiments demonstrate that the DefED-Net has better capability of feature representation as well as provides higher accuracy on liver and liver tumor segmentation than stateof-the art networks. The available code of DefED-Net we propose can be found from https://github.com/SUST-reynole/DefED-Net.

Pyramid (geometry)

Pooling

Feature (linguistics)

Convolution (computer science)

10.1109/trpms.2021.3059780

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Citations (96)

DNA折り紙上のプラズモニックメタ分子への不均一形状ナノ粒子の自己集合【Powered by NICT】

Chemistry - European Journal (2017)

Wenyan Liu Ling Li Shuo Yang Jie Gao Risheng Wang

Source

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PISA Printing Microneedles with Controllable Aqueous Dissolution Kinetics

ACS Applied Polymer Materials (2024)

Aaron Priester Jimmy Yeng Yuwei Zhang Krista Hilmas Risheng Wang

This study focused on the development of high-resolution polymeric structures using polymer-induced self-assembly (PISA) printing with commercially available digital light-processing (DLP) printers. Significantly, soluble solids could be 3D-printed using this methodology with controllable aqueous dissolution rates. This was achieved using a highly branched macrochain transfer agent (macro-CTA) containing multiple covalently attached CTA groups. In this work, the use of acrylamide as the self-assembling monomer in isopropyl alcohol was explored with the addition of N-(butoxymethyl)acrylamide to modulate the aqueous dissolution kinetics. PISA-printed microneedles were observed to have feature sizes as small as 27 μm, which was close to the resolution limit of the DLP printer. Atomic force measurements confirm the presence of a complex mixture of PISA morphologies, including spheres and worms. Additionally, "poke and release" microneedles were fabricated; their base dissolved rapidly in physiological fluids, leaving behind more slowly dissolving tips, thereby demonstrating the potential for sustained drug delivery.

Isopropyl alcohol

10.1021/acsapm.3c02796

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Control of DNA origami inter-tile connection with vertical linkers

Chemical Communications (2015)

Risheng Wang Kent Gorday Colin Nuckolls Shalom J. Wind

This communication describes a new method that enables high yield assembly along both of the two-dimensional edges of DNA origami tiles by controlling the Mg(2+) concentration; high Mg(2+) concentrations promote linkage connections between the vertical edges of the tiles. As a demonstration, DNA origami dimers assembled from two rectangular origami along the vertical edges are used as scaffolds for the double sided assembly of gold nanoparticles with different inter-particle spacings.

DNA origami

10.1039/c5cc08185h

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Citations (9)

Six-Helix and Eight-Helix DNA Nanotubes Assembled from Half-Tubes

Nano Letters (2007)

Akinori Kuzuya Risheng Wang Ruojie Sha Nadrian C. Seeman

DNA nanotubes are cylinder-like structures formed from DNA double-helical molecules whose helix axes are fused at least twice by crossovers. It is potentially useful to use such tubes as sheaths around rodlike species that arise in biological systems and in nanotechnology. It seems easiest to obtain such sheathing by joining two or more components around an object rather than attempting to thread the object through a cavity in the tube. We report two examples of tubes containing a specific number of helices that are assembled from half-tube components. These tubes are a six-helix bundle and an eight-helix bundle, constructed respectively from two bent triple-crossover (BTX) molecules and from two four-helix arched motifs. Both species contain single strands in one molecule that are missing in its mate. The six-helix bundle is formed from two different BTX molecules, whereas the eight-helix species is a closed cyclic dimer of the same molecule. We demonstrate the formation of these species by gel electrophoresis, and we examine their arrangement into long one-dimensional arrays by means of atomic force microscopy.

Helix (gastropod)

Helix bundle

Alpha helix

10.1021/nl070828k

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Citations (114)

Bio-inspired Polydopamine Surface Modification of Nanodiamonds and Its Reduction of Silver Nanoparticles

Journal of Visualized Experiments (2018)

Yun Zeng Wenyan Liu Risheng Wang

Surface functionalization of nanodiamonds (NDs) is still challenging due to the diversity of functional groups on the ND surfaces. Here, we demonstrate a simple protocol for the multifunctional surface modification of NDs by using mussel-inspired polydopamine (PDA) coating. In addition, the functional layer of PDA on NDs could serve as a reducing agent to synthesize and stabilize metal nanoparticles. Dopamine (DA) can self-polymerize and spontaneously form PDA layers on ND surfaces if the NDs and dopamine are simply mixed together. The thickness of a PDA layer is controlled by varying the concentration of DA. A typical result shows that a thickness of ~5 to ~15 nm of the PDA layer can be reached by adding 50 to 100 µg/mL of DA to 100 nm ND suspensions. Furthermore, the PDA-NDs are used as a substrate to reduce metal ions, such as Ag[(NH3)2]+, to silver nanoparticles (AgNPs). The sizes of the AgNPs rely on the initial concentrations of Ag[(NH3)2]+. Along with an increase in the concentration of Ag[(NH3)2]+, the number of NPs increases, as well as the diameters of the NPs. In summary, this study not only presents a facile method for modifying the surfaces of NDs with PDA, but also demonstrates the enhanced functionality of NDs by anchoring various species of interest (such as AgNPs) for advanced applications.

Surface Modification

Silver nanoparticle

Nanometre

10.3791/58458

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Citations (5)

Research on the new model of "Internet + education" based on artificial intelligence

Risheng Wang Zijun Sun Yuxi Zhou

China's "Internet + education" respects the essence of education at the same time, based on the Internet mode of thinking and behavior, re-create the teaching model and teaching methods, it does not belong to a simple online education, but the Internet into the whole process of teaching. Therefore, in the context of the new era, after introducing the concept of artificial intelligence technology into the field of education, the new information technology with artificial intelligence as the core can not only balance the processing of educational resources, gradually improve the teaching efficiency, but also present students with personalized and autonomous learning mode. In this article, therefore, artificial intelligence and Internet + education development model, on the basis of deeply discussed with artificial intelligence as the core "Internet + education" of the new mode, and connecting with the new era under the trend of the development of artificial intelligence, has been clear about the Internet + education the main content of the new model, in order to optimize the comprehensive level of education in our country.

Traditional education

10.1117/12.2670426

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Citations (6)