Decentralized H ∞-controller design for nonlinear systems

This paper considers the decentralized H ∞-controller design problem for nonlinear systems. Sufficient conditions for the solution of the problem are presented in terms of solutions of Hamilton-Jacobi inequalities. The resulting design guarantees local asymptotic stability and ensures a predetermined L 2-gain bound on the closed-loop system.published_or_final_versio

Decentralized H∞ controller design for nonlinear systems

published_or_final_versio

Design of reliable controllers for symmetric composite systems:primary contingency case

This paper discusses the reliable controller design problem for symmetric composite systems composed of several identical subsystems. A reliable controller design procedure is presented in terms of the solutions to algebraic Riccati equations. The order of these AREs is much lower than that of the symmetric composite system. The resulting closed-loop system is reliable in that it provide guaranteed internal stability and H∞ performance when all sensors and actuators are operational as well as when the sensors or actuators of a prescribed subsystem experiences an outage.published_or_final_versio

The role of oncogene in mycobacteria-induced antophagy in human macrophages

Poster PresentationMacrophages are the major immunocytes to initiate both innate and adaptive immune responses against Mycobacterium tuberculosis (Mtb), a causative agent of tuberculosis. Upon mycoabcteria infection, macrophages could eliminate the intracellular bacteria through different cell death pathways, including apoptosis and autophagy. c-Myc is a transcription factor that regulates a variety of target genes and control different cellular functions such as proliferation and immune resposnse. Recently, our group revealed that c-Myc has a potential role in regulating the antimicrobial responses in macrophages. Here we use BCG, a live attenuated strain of Mycobacterium bovis, which is similar to Mtb in antigenic composition, as a model to study the role of c-Myc in regulating mycobacteria-induced autophagy. We first investigated the role of c-Myc in BCG-induced LC3BII levels. Knocking down c-Myc by siRNA could decrease BCG-induced LC3BII levels. We found that BCG-induced autophagy is dependent on JNK and p38 and independent on PI3K or ERK pathways. And knocking down of c-Myc could significantly inhibit phosphorylation of p38. In conclusion, c-Myc may play a positive role in mycobacteria-induced autophagy in human macrophages.published_or_final_versio

Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors

The impressive performance of deep convolutional neural networks in single-view 3D reconstruction suggests that these models perform non-trivial reasoning about the 3D structure of the output space. However, recent work has challenged this belief, showing that complex encoder-decoder architectures perform similarly to nearest-neighbor baselines or simple linear decoder models that exploit large amounts of per category data in standard benchmarks. On the other hand settings where 3D shape must be inferred for new categories with few examples are more natural and require models that generalize about shapes. In this work we demonstrate experimentally that naive baselines do not apply when the goal is to learn to reconstruct novel objects using very few examples, and that in a \emph{few-shot} learning setting, the network must learn concepts that can be applied to new categories, avoiding rote memorization. To address deficiencies in existing approaches to this problem, we propose three approaches that efficiently integrate a class prior into a 3D reconstruction model, allowing to account for intra-class variability and imposing an implicit compositional structure that the model should learn. Experiments on the popular ShapeNet database demonstrate that our method significantly outperform existing baselines on this task in the few-shot setting

The use of kurtosis de-noising for EEG analysis of patients suffering from Alzheimer's disease.

The use of electroencephalograms (EEGs) to diagnose and analyses Alzheimer’s disease (AD) has received much attention in recent years. The sample entropy (SE) has been widely applied to the diagnosis of AD. In our study, nine EEGs from 21 scalp electrodes in 3 AD patients and 9 EEGs from 3 age-matched controls are recorded. The calculations show that the kurtoses of the AD patients’ EEG are positive and much higher than that of the controls. This finding encourages us to introduce a kurtosis-based de-noising method. The 21-electrode EEG is first decomposed using independent component analysis (ICA), and second sort them using their kurtoses in ascending order. Finally, the subspace of EEG signal using back projection of only the last five components is reconstructed. SE will be calculated after the above de-noising preprocess. The classifications show that this method can significantly improve the accuracy of SE-based diagnosis. The kurtosis analysis of EEG may contribute to increasing the understanding of brain dysfunction in AD in a statistical way

Investigating the role of interleukin-17A on cytokines production by macrophages in response to bacterial infections

Poster PresentationInterleukin-17A (IL-17A) has been shown to associate with a variety of infection diseases. In this study, we investigate whether IL-17A affects cytokines production of human peripheral blood-derived macrophages during Mycobacteriun bovis BCG or Klebsiella pneumoniae infection. We observed that IL-17A-treated macrophages exhibited suppressed productions of TNF-α and IL-6 in response to BCG infection. The reduction of cytokines production was not associated with cell death. On the other hand, IL-17A promoted TNF-α and IL-6 production by macrophages during K. pneumoniae infection. Furthermore, IL-17A did not affect TNF-α production induced by LPS and Pam3 Cys, which are TLR4 and TLR2 agonists, respectively. The data suggest that the differential regulation of cytokines production by IL-17A requires whole bacterium infection.published_or_final_versio

The effect of glutamine supplement on small intestinal morphology and xylose absorptive ability of weaned piglets

The purpose of this study is to demonstrate the effects of glutamine (Gln) supplement on small intestinal  morphology, xylose absorptive and growth performance of weaned piglets. Forty eight piglets weaned at 28 ± 2 days of age were randomly allotted to three treatment groups. A basal corn-soybean diet was formulated to contain 20.3% protein and 3450 kcal DE/kg diet. Glutamine was supplemented to the basal diet at 0% (control), 1% (Gln 1%) and 2% (Gln 2%). Pigs were fed experimental diets for three weeks. The results  showed that the villous height of the Gln groups tended higher than the control group in duodenum and jejunum (P < 0.1). Glutamine supplementation increased plasma net xylose absorptive concentration from 0.78 to 1.20 and 0.95 to 1.23 in Gln 1% and Gln 2% group, respectively, which were better than the control group (0.86 to 0.97) in day 7 to 14 after weaning. Growth performance was not significantly affected by Gln supplement;  however, average daily gain was approximately improved from 21 to 28% by Gln supplement compared to the control group during 21 days of experimental period. In summary, the results suggested that dietary  supplementation of Gln could be beneficial in small intestinal villous morphology and xylose absorptive  capacity, and could have a slight contribution to the average daily gain of weaned piglets.Key words: Glutamine, growth performance, intestinal morphology, weaned piglets

Discrete Point Flow Networks for Efficient Point Cloud Generation

Generative models have proven effective at modeling 3D shapes and their statistical variations. In this paper we investigate their application to point clouds, a 3D shape representation widely used in computer vision for which, however, only few generative models have yet been proposed. We introduce a latent variable model that builds on normalizing flows with affine coupling layers to generate 3D point clouds of an arbitrary size given a latent shape representation. To evaluate its benefits for shape modeling we apply this model for generation, autoencoding, and single-view shape reconstruction tasks. We improve over recent GAN-based models in terms of most metrics that assess generation and autoencoding. Compared to recent work based on continuous flows, our model offers a significant speedup in both training and inference times for similar or better performance. For single-view shape reconstruction we also obtain results on par with state-of-the-art voxel, point cloud, and mesh-based methods.Comment: In ECCV'2

Quantifying drug-induced dyskinesias in the arms using digitised spiral-drawing tasks.

In this study, we quantify the severity of drug-induced dyskinesias in the arms of Parkinson's disease (PD) patients using digitised spiral-drawing tasks. Two spiral drawings, namely a circular and a square spiral, are designed to, respectively, represent the continuous and discrete arm motions, and the size of the spiral is decided so that both the distal and proximal arm joints are involved. Fifteen PD patients, average disease duration 14.4+/-7.4 years, were assessed 30 min after a levodopa challenge whilst performing circular and square spiral-drawing tasks. The velocity of drawing movements was computed and the amplitude of the involuntary dyskinetic movements was measured as the standard deviation of the drawing velocity (SD-DV). The mean amplitude of dyskinetic movements was compared between arms and tasks and was correlated with clinical measures including the Bain dyskinesia scale and the total unified Parkinson's disease rating scale (UPDRS) score. The results showed that there was no statistically significant difference in the amplitude of dyskinesias either between the arms or between the continuous (circular) and discrete (square) spiral drawings in this group of PD patients, but interestingly the interaction between arm and drawing pattern was significant. Significant correlations were found between the magnitude of dyskinesia measured from the spiral-drawing tasks and both the 'on' or 'off' UPDRS and also the Bain dyskinesia scale. We conclude that the drawing tasks may be used to provide an objective method of quantifying the severity of drug-induced dyskinesias in the arm in PD patients