Nankai University

About: Nankai University is a education organization based out in Tianjin, China. It is known for research contribution in the topics: Catalysis & Enantioselective synthesis. The organization has 42964 authors who have published 51866 publications receiving 1127896 citations. The organization is also known as: Nánkāi Dàxué.

Revisiting Video Saliency Prediction in the Deep Learning Era

Abstract: Predicting where people look in static scenes, a.k.a visual saliency, has received significant research interest recently. However, relatively less effort has been spent in understanding and modeling visual attention over dynamic scenes. This work makes three contributions to video saliency research. First, we introduce a new benchmark, called DHF1K (Dynamic Human Fixation 1K), for predicting fixations during dynamic scene free-viewing, which is a long-time need in this field. DHF1K consists of 1K high-quality elaborately-selected video sequences annotated by 17 observers using an eye tracker device. The videos span a wide range of scenes, motions, object types and backgrounds. Second, we propose a novel video saliency model, called ACLNet (Attentive CNN-LSTM Network), that augments the CNN-LSTM architecture with a supervised attention mechanism to enable fast end-to-end saliency learning. The attention mechanism explicitly encodes static saliency information, thus allowing LSTM to focus on learning a more flexible temporal saliency representation across successive frames. Such a design fully leverages existing large-scale static fixation datasets, avoids overfitting, and significantly improves training efficiency and testing performance. Third, we perform an extensive evaluation of the state-of-the-art saliency models on three datasets : DHF1K, Hollywood-2, and UCF sports. An attribute-based analysis of previous saliency models and cross-dataset generalization are also presented. Experimental results over more than 1.2K testing videos containing 400K frames demonstrate that ACLNet outperforms other contenders and has a fast processing speed (40 fps using a single GPU). Our code and all the results are available at https://github.com/wenguanwang/DHF1K .

Outlier detection for high-dimensional data

Abstract: Outlier detection is an integral component of statistical modelling and estimation. For high-dimensional data, classical methods based on the Mahalanobis distance are usually not applicable. We propose an outlier detection procedure that replaces the classical minimum covariance determinant estimator with a high-breakdown minimum diagonal product estimator. The cut-off value is obtained from the asymptotic distribution of the distance, which enables us to control the Type I error and deliver robust outlier detection. Simulation studies show that the proposed method behaves well for high-dimensional data.

Mitochondrion-Anchoring Photosensitizer with Aggregation-Induced Emission Characteristics Synergistically Boosts the Radiosensitivity of Cancer Cells to Ionizing Radiation.

Abstract: The first mitochondrion-anchoring photosensitizer that specifically generates singlet oxygen (1 O2 ) in mitochondria under white light irradiation that can serve as a highly effective radiosensitizer is reported here, significantly sensitizing cancer cells to ionizing radiation. An aggregation-induced emission luminogen (AIEgen), namely DPA-SCP, is rationally designed with α-cyanostilbene as a simple building block to reveal AIE, diphenylamino (DPA) group as a strong electron donating group to benefit red emission and efficient light-controlled 1 O2 generation, as well as a pyridinium salt as the targeting moiety to ensure specific mitochondrial localization. The AIE signature endows DPA-SCP with the capacity to visualize mitochondria in a fluorescence turn-on mode. It is found that under optimized experimental condition, DPA-SCP with white light does not lead to apoptosis/death of cancer cells, whereas provides an elevated 1 O2 environment in the mitochondria. More importantly, increasing intracellular level of 1 O2 originated from mitochondria is demonstrated to be a generic method to enhance the radiosensitivity of cancer cells with a supra-additive synergistic effect of "0 + 1 > 1." Noteworthy is that "DPA-SCP + white light" achieves a high SER10 value of 1.62, which is much larger than that of the most popularly used radiosensitizers, gold nanoparticles (1.19), and paclitaxel (1.32).

Neural Network-Based Adaptive Antiswing Control of an Underactuated Ship-Mounted Crane With Roll Motions and Input Dead Zones

Abstract: As a type of indispensable oceanic transportation tools, ship-mounted crane systems are widely employed to transport cargoes and containers on vessels due to their extraordinary flexibility. However, various working requirements and the oceanic environment may cause some uncertain and unfavorable factors for ship-mounted crane control. In particular, to accomplish different control tasks, some plant parameters (e.g., boom lengths, payload masses, and so on) frequently change; hence, most existing model-based controllers cannot ensure satisfactory control performance any longer. For example, inaccurate gravity compensation may result in positioning errors. Additionally, due to ship roll motions caused by sea waves, residual payload swing generally exists, which may result in safety risks in practice. To solve the above-mentioned issues, this paper designs a neural network-based adaptive control method that can provide effective control for both actuated and unactuated state variables based on the original nonlinear ship-mounted crane dynamics without any linearizing operations. In particular, the proposed update law availably compensates parameter/structure uncertainties for ship-mounted crane systems. Based on a 2-D sliding surface, the boom and rope can arrive at their preset positions in finite time, and the payload swing can be completely suppressed. Furthermore, the problem of nonlinear input dead zones is also taken into account. The stability of the equilibrium point of all state variables in ship-mounted crane systems is theoretically proven by a rigorous Lyapunov-based analysis. The hardware experimental results verify the practicability and robustness of the presented control approach.

Flexible meso-Bis(sulfinyl) Ligands as Building Blocks for Copper(II) Coordination Polymers: Cavity Control by Varying the Chain Length of Ligands.

Abstract: Fillings and cavities: Three novel pseudo-octahedral metal-organic frameworks, 1-3, consisting of macrometallacyclic noninterpenetrating meso networks and exhibiting weak antiferromagnetic interactions, have been constructed from CuII centers and structurally flexible R,S-bis(sulfinyl) ligands. Varying the chain length of ligands is found to control the cavity sizes of the networks.